Problematic Adjustments And Divergences (Now Includes June Data)

Guest Post by Professor Robert Brown of Duke University and Werner Brozek, Edited by Just The Facts:

CO2 versus adjustments
Image Credit: Steven Goddard

As can be seen from the graphic above, there is a strong correlation between carbon dioxide increases and adjustments to the United States Historical Climatology Network (USHCN) temperature record. And these adjustments to the surface data in turn result in large divergences between surface data sets and satellite data sets.

In the post with April data, the following questions were asked in the conclusion: “Why are the new satellite and ground data sets going in opposite directions? Is there any reason that you can think of where both could simultaneously be correct?”
Professor Robert Brown of Duke University had an excellent response the this question here.
To give it the exposure it deserves, his comment is reposted in full below. His response ends with rgb.

Rgbatduke June 10, 2015 at 5:52 am

The two data sets should not be diverging, period, unless everything we understand about atmospheric thermal dynamics is wrong. That is, I will add my “opinion” to Werner’s and point out that it is based on simple atmospheric physics taught in any relevant textbook.

This does not mean that they cannot and are not systematically differing; it just means that the growing difference is strong evidence of bias in the computation of the surface record. This bias is not really surprising, given that every new version of HadCRUT and GISS has had the overall effect of cooling the past and/or warming the present! This is as unlikely as flipping a coin (at this point) ten or twelve times each, and having it come up heads every time for both products. In fact, if one formulates the null hypothesis “the global surface temperature anomaly corrections are unbiased”, the p-value of this hypothesis is less than 0.01, let alone 0.05. If one considers both of the major products collectively, it is less than 0.001. IMO, there is absolutely no question that GISS and HadCRUT, at least, are at this point hopelessly corrupted.

One way in which they are corrupted with the well-known Urban Heat Island effect, wherein urban data or data from poorly sited weather stations shows local warming that does not accurately reflect the spatial average surface temperature in the surrounding countryside. This effect is substantial, and clearly visible if you visit e.g. Weather Underground and look at the temperature distributions from personal weather stations in an area that includes both in-town and rural PWSs. The city temperatures (and sometimes a few isolated PWSs) show a consistent temperature 1 to 2 C higher than the surrounding country temperatures. Airport temperatures often have this problem as well, as the temperatures they report come from stations that are deliberately sited right next to large asphalt runways, as they are primarily used by pilots and air traffic controllers to help planes land safely, and only secondarily are the temperatures they report almost invariably used as “the official temperature” of their location. Anthony has done a fair bit of systematic work on this, and it is a serious problem corrupting all of the major ground surface temperature anomalies.

The problem with the UHI is that it continues to systematically increase independent of what the climate is doing. Urban centers continue to grow, more shopping centers continue to be built, more roadway is laid down, more vehicle exhaust and household furnace exhaust and water vapor from watering lawns bumps greenhouse gases in a poorly-mixed blanket over the city and suburbs proper, and their perimeter extends, increasing the distance between the poorly sited official weather stations and the nearest actual unbiased countryside.

HadCRUT does not correct in any way for UHI. If it did, the correction would be the more or less uniform subtraction of a trend proportional to global population across the entire data set. This correction, of course, would be a cooling correction, not a warming correction, and while it is impossible to tell how large it is without working through the unknown details of how HadCRUT is computed and from what data (and without using e.g. the PWS field to build a topological correction field, as UHI corrupts even well-sited official stations compared to the lower troposphere temperatures that are a much better estimator of the true areal average) IMO it would knock at least 0.3 C off of 2015 relative to 1850, and would knock off around 0.1 C off of 2015 relative to 1980 (as the number of corrupted stations and the magnitude of the error is not linear — it is heavily loaded in the recent past as population increases exponentially and global wealth reflected in “urbanization” has outpaced the population).

GISS is even worse. They do correct for UHI, but somehow, after they got through with UHI the correction ended up being neutral to negative. That’s right, UHI, which is the urban heat island effect, something that has to strictly cool present temperatures relative to past ones in unbiased estimation of global temperatures ended up warming them instead. Learning that left me speechless, and in awe of the team that did it. I want them to do my taxes for me. I’ll end up with the government owing me money.
However, in science, this leaves both GISS and HadCRUT (and any of the other temperature estimates that play similar games) with a serious, serious problem. Sure, they can get headlines out of rewriting the present and erasing the hiatus/pause. They might please their political masters and allow them to convince a skeptical (and sensible!) public that we need to spend hundreds of billions of dollars a year to unilaterally eliminate the emission of carbon dioxide, escalating to a trillion a year, sustained, if we decide that we have to “help” the rest of the world do the same. They might get the warm fuzzies themselves from the belief that their scientific mendacity serves the higher purpose of “saving the planet”. But science itself is indifferent to their human wishes or needs! A continuing divergence between any major temperature index and RSS/UAH is inconceivable and simple proof that the major temperature indices are corrupt.

Right now, to be frank, the divergence is already large enough to be raising eyebrows, and is concealed only by the fact that RSS/UAH only have a 35+ year base. If the owners of HadCRUT and GISSTEMP had the sense god gave a goose, they’d be working feverishly to cool the present to better match the satellites, not warm it and increase the already growing divergence because no atmospheric physicist is going to buy a systematic divergence between the two, as Werner has pointed out, given that both are necessarily linked by the Adiabatic Lapse Rate which is both well understood and directly measurable and measured (via e.g. weather balloon soundings) more than often enough to validate that it accurately links surface temperatures and lower troposphere temperatures in a predictable way. The lapse rate is (on average) 6.5 C/km. Lower Troposphere temperatures from e.g. RSS sample predominantly the layer of atmosphere centered roughly 1.5 km above the ground, and by their nature smooth over both height and surrounding area (that is, they don’t measure temperatures at points, they directly measure a volume averaged temperature above an area on the surface. They by their nature give the correct weight to the local warming above urban areas in the actual global anomaly, and really should also be corrected to estimate the CO_2 linked warming, or rather the latter should be estimated only from unbiased rural areas or better yet, completely unpopulated areas like the Sahara desert (where it isn’t likely to be mixed with much confounding water vapor feedback).

RSS and UAH are directly and regularly confirmed by balloon soundings and, over time, each other. They are not unconstrained or unchecked. They are generally accepted as accurate representations of LTT’s (and the atmospheric temperature profile in general).
The question remains as to how accurate/precise they are. RSS uses a sophisticated Monte Carlo process to assess error bounds, and eyeballing it suggests that it is likely to be accurate to 0.1-0.2 C month to month (similar to error claims for HadCRUT4) but much more accurate than this when smoothed over months or years to estimate a trend as the error is generally expected to be unbiased. Again this ought to be true for HadCRUT4, but all this ends up meaning is that a trend difference is a serious problem in the consistency of the two estimators given that they must be linked by the ALR and the precision is adequate even month by month to make it well over 95% certain that they are not, not monthly and not on average.

If they grow any more, I would predict that the current mutter about the anomaly between the anomalies will grow to an absolute roar, and will not go away until the anomaly anomaly is resolved. The resolution process — if the gods are good to us — will involve a serious appraisal of the actual series of “corrections” to HadCRUT and GISSTEMP, reveal to the public eye that they have somehow always been warming ones, reveal the fact that UHI is ignored or computed to be negative, and with any luck find definitive evidence of specific thumbs placed on these important scales. HadCRUT5 might — just might — end up being corrected down by the ~0.3 C that has probably been added to it or erroneously computed in it over time.
rgb

See here for further information on GISS and UHI.

In the sections below, as in previous posts, we will present you with the latest facts. The information will be presented in three sections and an appendix. The first section will show for how long there has been no warming on some data sets. At the moment, only the satellite data have flat periods of longer than a year. The second section will show for how long there has been no statistically significant warming on several data sets. The third section will show how 2015 so far compares with 2014 and the warmest years and months on record so far. For three of the data sets, 2014 also happens to be the warmest year. The appendix will illustrate sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.

Section 1

This analysis uses the latest month for which data is available on WoodForTrees.com (WFT). All of the data on WFT is also available at the specific sources as outlined below. We start with the present date and go to the furthest month in the past where the slope is a least slightly negative on at least one calculation. So if the slope from September is 4 x 10^-4 but it is – 4 x 10^-4 from October, we give the time from October so no one can accuse us of being less than honest if we say the slope is flat from a certain month.
1. For GISS, the slope is not flat for any period that is worth mentioning.
2. For Hadcrut4, the slope is not flat for any period that is worth mentioning.
3. For Hadsst3, the slope is not flat for any period that is worth mentioning.
4. For UAH, the slope is flat since March 1997 or 18 years and 4 months. (goes to June using version 6.0)
5. For RSS, the slope is flat since January 1997 or 18 years and 6 months. (goes to June)

The next graph shows just the lines to illustrate the above. Think of it as a sideways bar graph where the lengths of the lines indicate the relative times where the slope is 0. In addition, the upward sloping blue line at the top indicates that CO2 has steadily increased over this period.

WoodForTrees.org – Paul Clark – Click the pic to view at source

When two things are plotted as I have done, the left only shows a temperature anomaly.

The actual numbers are meaningless since the two slopes are essentially zero. No numbers are given for CO2. Some have asked that the log of the concentration of CO2 be plotted. However WFT does not give this option. The upward sloping CO2 line only shows that while CO2 has been going up over the last 18 years, the temperatures have been flat for varying periods on the two sets.

Section 2

For this analysis, data was retrieved from Nick Stokes’ Trendviewer available on his website <a href=”http://moyhu.blogspot.com.au/p/temperature-trend-viewer.html”. This analysis indicates for how long there has not been statistically significant warming according to Nick’s criteria. Data go to their latest update for each set. In every case, note that the lower error bar is negative so a slope of 0 cannot be ruled out from the month indicated.

On several different data sets, there has been no statistically significant warming for between 11 and 22 years according to Nick’s criteria. Cl stands for the confidence limits at the 95% level.

The details for several sets are below.

For UAH6.0: Since October 1992: Cl from -0.009 to 1.742
This is 22 years and 9 months.
For RSS: Since January 1993: Cl from -0.000 to 1.676
This is 22 years and 6 months.
For Hadcrut4.3: Since July 2000: Cl from -0.017 to 1.371
This is 14 years and 11 months.
For Hadsst3: Since August 1995: Cl from -0.000 to 1.780
This is 19 years and 11 months.
For GISS: Since August 2003: Cl from -0.000 to 1.336
This is 11 years and 11 months.

Section 3

This section shows data about 2015 and other information in the form of a table. The table shows the five data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, Hadsst3, and GISS.
Down the column, are the following:
1. 14ra: This is the final ranking for 2014 on each data set.
2. 14a: Here I give the average anomaly for 2014.
3. year: This indicates the warmest year on record so far for that particular data set. Note that the satellite data sets have 1998 as the warmest year and the others have 2014 as the warmest year.
4. ano: This is the average of the monthly anomalies of the warmest year just above.
5. mon: This is the month where that particular data set showed the highest anomaly. The months are identified by the first three letters of the month and the last two numbers of the year.
6. ano: This is the anomaly of the month just above.
7. y/m: This is the longest period of time where the slope is not positive given in years/months. So 16/2 means that for 16 years and 2 months the slope is essentially 0. Periods of under a year are not counted and are shown as “0”.
8. sig: This the first month for which warming is not statistically significant according to Nick’s criteria. The first three letters of the month are followed by the last two numbers of the year.
9. sy/m: This is the years and months for row 8. Depending on when the update was last done, the months may be off by one month.
10. Jan: This is the January 2015 anomaly for that particular data set.
11. Feb: This is the February 2015 anomaly for that particular data set, etc.
16. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months.
17. rnk: This is the rank that each particular data set would have for 2015 without regards to error bars and assuming no changes. Think of it as an update 25 minutes into a game.

Source UAH RSS Had4 Sst3 GISS
1.14ra 6th 6th 1st 1st 1st
2.14a 0.170 0.255 0.564 0.479 0.75
3.year 1998 1998 2014 2014 2014
4.ano 0.483 0.55 0.564 0.479 0.75
5.mon Apr98 Apr98 Jan07 Aug14 Jan07
6.ano 0.742 0.857 0.832 0.644 0.97
7.y/m 18/4 18/6 0 0 0
8.sig Oct92 Jan93 Jul00 Aug95 Aug03
9.sy/m 22/9 22/6 14/11 19/11 11/11
Source UAH RSS Had4 Sst3 GISS
10.Jan 0.261 0.367 0.688 0.440 0.82
11.Feb 0.156 0.327 0.660 0.406 0.88
12.Mar 0.139 0.255 0.681 0.424 0.90
13.Apr 0.065 0.175 0.656 0.557 0.74
14.May 0.272 0.310 0.696 0.593 0.76
15.Jun 0.329 0.391 0.728 0.580 0.80
Source UAH RSS Had4 Sst3 GISS
16.ave 0.204 0.304 0.685 0.500 0.82
17.rnk 4th 6th 1st 1st 1st

If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0 was used. Note that WFT uses version 5.6. So to verify the length of the pause on version 6.0, you need to use Nick’s program.
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/tltglhmam_6.0beta2
For RSS, see: ftp://ftp.ssmi.com/msu/monthly_time_series/rss_monthly_msu_amsu_channel_tlt_anomalies_land_and_ocean_v03_3.txt
For Hadcrut4, see: http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.4.4.0.0.monthly_ns_avg.txt
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt

To see all points since January 2015 in the form of a graph, see the WFT graph below. Note that UAH version 5.6 is shown. WFT does not show version 6.0 yet.

WoodForTrees.org – Paul Clark – Click the pic to view at source

As you can see, all lines have been offset so they all start at the same place in January 2015. This makes it easy to compare January 2015 with the latest anomaly.

Appendix

In this part, we are summarizing data for each set separately.

RSS

The slope is flat since January 1997 or 18 years, 6 months. (goes to June)
For RSS: There is no statistically significant warming since January 1993: Cl from -0.000 to 1.676.
The RSS average anomaly so far for 2015 is 0.304. This would rank it as 6th place. 1998 was the warmest at 0.55. The highest ever monthly anomaly was in April of 1998 when it reached 0.857. The anomaly in 2014 was 0.255 and it was ranked 6th.

UAH6.0

The slope is flat since March 1997 or 18 years and 4 months. (goes to June using version 6.0)
For UAH: There is no statistically significant warming since October 1992: Cl from -0.009 to 1.742. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly so far for 2015 is 0.204. This would rank it as 4th place. 1998 was the warmest at 0.483. The highest ever monthly anomaly was in April of 1998 when it reached 0.742. The anomaly in 2014 was 0.170 and it was ranked 6th.

Hadcrut4.4

The slope is not flat for any period that is worth mentioning.
For Hadcrut4: There is no statistically significant warming since July 2000: Cl from -0.017 to 1.371.
The Hadcrut4 average anomaly so far for 2015 is 0.685. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.832. The anomaly in 2014 was 0.564 and this set a new record.

Hadsst3

For Hadsst3, the slope is not flat for any period that is worth mentioning. For Hadsst3: There is no statistically significant warming since August 1995: Cl from -0.000 to 1.780.
The Hadsst3 average anomaly so far for 2015 is 0.500. This would set a new record if it stayed this way. The highest ever monthly anomaly was in August of 2014 when it reached 0.644. The anomaly in 2014 was 0.479 and this set a new record.

GISS

The slope is not flat for any period that is worth mentioning.
For GISS: There is no statistically significant warming since August 2003: Cl from -0.000 to 1.336.
The GISS average anomaly so far for 2015 is 0.82. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.97. The anomaly in 2014 was 0.75 and it set a new record. (Note that the new GISS numbers this month are quite a bit higher than last month.)

If you are interested, here is what was true last month:
The slope is not flat for any period that is worth mentioning.
For GISS: There is no statistically significant warming since November 2000: Cl from -0.018 to 1.336.
The GISS average anomaly so far for 2015 is 0.77. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2014 was 0.68 and it set a new record.

Conclusion

Two months ago, NOAA was the odd man out. Since GISS has joined NOAA, HadCRUT4 apparently felt the need to fit in, as documented here.

431 thoughts on “Problematic Adjustments And Divergences (Now Includes June Data)

  1. Wow, the lapse rate mentioned for a change. The fact that we have a lapse rate should have given plenty opportunity to disprove the whole Greenhouse Effect completely. Top of The Grand Canyon compared to the bottom of it. Flat plains of Peru. The planet of Venus. The atmosphere of Jupiter.

  2. WOW. R^2 = 0.98 Unprecedented in climate science.

    Give those guys a Michelin star, Best. Data cooking. Ever.

    • Even better when the response should be proportional to the log(CO2). I guess they forgot to tell them that.

      • Every differentiable function looks roughly linear when you view it closely enough. One would have to plot the graph on a logarithmic scale to see if it truly seems to deviate from theory. Further, the logarithmic response is for a simple green-house effect, not the feedbacks.

      • The plot shows the adjustments, not to anomalies. One wouldn’t expect the adjustments to correspond in anyway with CO2, would one? If so, what is the physics that says the adjusment should vary with CO2?

      • One wouldn’t expect the adjustments to correspond in anyway with CO2, would one?

        No, that would not be expected.

        If so, what is the physics that says the adjustment should vary with CO2?

        Physics says that extra CO2 should cause some warming, but the extra warming should come without adjustments and not because of adjustments.

      • It’s clear from the graph that there is a correlation, but what is the direction of causation? Does CO2 cause data adjustment, or does data adjustment cause CO2?

      • RoHA:
        Co2 causes everything! It is the magical molecule from hell that gives us all life and yet is evil beyond words.

      • Adjustments are known to be anthropogenic – no one argues about that.
        CO2 rises are generally acknowledged to be anthropogenic.
        However just because two things have a common cause there is no reason to believe they will be correlated as shown here.

      • RoHa August 15, 2015 at 4:32 am
        It’s clear from the graph that there is a correlation, but what is the direction of causation? Does CO2 cause data adjustment, or does data adjustment cause CO2?

        The adjustment is increasing the CO2 level (since the CO2 level would have no impact on computer software).

        We can stop lethal CO2 levels and over 7.5°C of CGAGW by 2100 by making temperature data adjustment illegal with criminal and civil penalties.

        We could have prevented 0.23°C of warming by RIFing (firing) the data adjusters in 2008. We should fire them now and save ourselves while there is still time.

      • Menicholas
        August 14, 2015 at 1:26 pm

        Lets just call it an even 1.00000000000 and break for lunch and a few drinks, eh?
        _________________________
        No, it’s 2 sig figs. Skip the drinks and go back to school, eh?

      • Hey RD, this is called a joke.
        I can explain to you why it is a joke, but it might take a while, since you seem to have been born with nary an ounce of humor in your entire soul.
        You see, the climate establishment has long and widely been accused of not know the fist thing about sig figs…yadda yadda yadda… the horse says “No, it was the donkey!”

      • BTW, I have not had a drink in 13 years (part of the joke…), have never left “school” and also had already eaten lunch.
        Are you laughing yet?

  3. These folks just love to correct things in the wrong direction. UHI is not removed, it is increased! Sea surface temperatures are corrected to conform with the most convenient but least reliable measurements. Reminds me of the man behind the curtain frantically pulling levers to generate a ferocious but utterly false image designed only to terrify the children. Alice was not fooled.

  4. @rgb
    So you are basically stating that all major providers of temperature series of either
    1 being incompetent
    2 purposefully changing the data to match their belief.

    1. How can so many intelligent educated people be so incompetent. This seems very unlikely. Have you approached the scientists concerned and shown them where they are in error. If not, Why not?

    2. This is a serious accusation of scientific fraud. As such have you approached any of the scientists involved and asked for an explanation? If not, why not? You are, after all, part of the scientific community.
    Can you give reasons why you think 1000s of scientists over the whole globe would all be party to this fraud. I do not see climate scientists living in luxury mansions taking expensive family holidays – perhaps you know differently?. What manages to keep so many scientists in line – are there families/careers/lives threated to maintain the silence. why is there no Julian Assange or Edward Snowden, willing to expose the fraud?

    • “Bias” doesn’t mean a personal failing.
      In science it can mean something that skews the results away from the true mean.

      The example rgb gave, the effect of Urban Heat Islands (UHIs), is such a bias.

      And the idea that no-one ever makes a genuine mistake is as silly as that genuine mistake that UHIs cool the record as they expand.

      • intent does apply to the legal charge of fraud. Without intent, all you’re left with is sloppy, not careful work by a team of data scientists and statisticians. Becoming known for sloppy poor work by your peers in science is a path to lost funding and ostracization. That’s all assuming politics and ideologies are not in play. The social sciences have a long and sad history of bias against those not of a personal Liberal view point. Sadly, that has taken firm root in Climate Science as Drs. Soon, Legates and others can attest to.

    • Excellent questions SergeiMK. I hope that time will tell.

      At least the fabrication of the surface temperature record is now in the peer-reviewed literature. No more “It’s only on blogs”.

      Karl et al., (2015) was a seminal paper on how to fabricate the surface temperature record. Nobel Prize stuff (Peace Prize that would be).

    • You forgot:
      3. subject to confirmation bias and, due to their beliefs, unwittingly biasing the results.
      or my favorite,
      4. loyal to their corrupt political bosses and doing their part in the scam.

      Oh, and there aren’t 1,000’s of scientists involved in the scam. A few dozen well-placed ones would suffice.

      • Let me add another possibility-
        5. Just not actually doing any critical examinations of the data sets or their adjustments themselves. If you are an average scientist whose research or job does create a personal need or desire or reason to question what an “official “report says, you’re going to take what it declares as fact and move on.

        Example- if you’re an ocean scientist whose work doesn’t rely heavily (or at all) on CO2 in the atmosphere, or land and satellite data, you might have no clue what those data sets show. If you are writing a paper or doing research where that information is required in some fringe way, you pull up the latest data from your preferred source, jot down the numbers, and give it no further thought.

        It doesnt require a vast network of incompetent OR conspiring people to create mass delusion. It takes a very small number of well placed individuals who are either incompetent/conspiring or both, and a passive audience who simply believes they are neither one.

        The same idiotic sheep who believe that the Koch brothers are responsible for misleading the majority of the general public are the exact same people who mock and deny the idea that a few scientists could possibly be misleading the majority of scientists!
        THEIR conspiracy theory is perfectly sound and logical. But the exact same theory turned against them is absurd and borders on mental illnesses!

    • Well serge, I am hoping for a hero like Snowden (an insider) to inform the world of the shenanigans in the Alarmist community.
      However, it is fraud, IMO. Any critical thinking human that isn’t biased by their politics knows it is fraud. There are so many culprits to choose from, but I will give two: ClimateGate and my favorite, the Hockey Schtick.

    • The reasons that the 1000s of scientists are party to the fraud is called $$$$$. Just because you want $$$$ for research, doesn’t mean you’re a thief, it means you do what’s necessary to get to the trough. When getting to the trough means writing that the world is ending, that’s what you write. The threat of not receiving funding, tenure, recognition is enough to ensure their silence. Demonstrably they are changing the data. The disparity between the satellite data and the surface data demonstrates that clearly.

      Assange or Snowden? Ah, there is WUWT, without which we would still be thinking that NOAA’s measurements were all top quality instead of the siting nightmare they generally are. Without which the Climategate papers would have remained hidden on a few cognoscenti sites, without which the work that exposed Mann’s extremely inept hockeystick would have languished.

      • Just because you want $$$$ for research, doesn’t mean you’re a thief.

        Once the money has been green-laundered (through whichever grant-providing organization) – it’s all good, and the rest of us barely felt it leaving our wallets.

      • Give Tony Heller and Paul Homewood their due, as well. Fair is fair.
        Tony gets no respect, and I placed his graphs and ideas on this site any times before anyone picked up the ball and ran with it.

      • without which the work that exposed Mann’s extremely inept hockeystick would have languished.

        No that was down to Steve Mc and JeanS. BUT I am very appreciative of the work done at WUWT and have contributed on the odd occasion.

    • People are human. When the data don’t support the hypothesis, one might actively look for things that could justify adjusting the data in the right direction. That’s more convenient that discarding the hypothesis.

      But one doesn’t look (as aggressively) for things that might make the data look “worse”.

      This is bias.

      It gets worse. When a large group of folks, committed to a cause, are driving the process, a powerful groupthink sets in and they all reinforce each other and ultimately amplify the effect. Less than sound science is “forgiven” and justified because the groups motives are “oh so noble”.

      These people are not, in general, acting out of stupidity or malicious intent. They actually believe they “saving the world” and the groupthink reinforces that on a daily basis.

      BTW, great paper from Prof. Brown.

      • Mike S. Belief by scientists. I’ll go with Rod’s statement “Oh, and there aren’t 1,000’s of scientists involved in the scam. A few dozen well-placed ones would suffice.” In addition, it is the governments of the western developed countries that are encouraging not only these few dozen, but the Uni’s and Science org’s via prostitution by the gov’t funding.

      • Kokoda,
        add to the “a few dozen well-placed” is the fact that senior team leaders in those key sections get to select and edit who is on the team. Ensures only those loyal to cause are retained, have access to discussions, allowed meeting attendance, and promoted within the team.

      • A further observation is that the author list on the Karl, et al, 2015 Science paper is a pact of omerta. If evidence of purposeful data fraud is ever released (by an insider with access and knowledge) and Mr Karl’s reputation goes down, then they all go down (ruined reputations).They are in the gang for life, and its a reputational death sentence if they betray that fielty. And hence Mr Karl put the names of those “with knowledge” as authors, where the have to sign and acknowledge to the journal editor their parts in the submitted manuscript.

      • A further observation is that the author list on the Karl, et al, 2015 Science paper is a pact of omerta. If evidence of purposeful data fraud is ever released and Mr Karl’s reputation goes down, they all go down with him (ruined reputations) as each author has to submit a signed attestation to the Science editors for their role and review of the manuscript once it is accepted for publication.
        So the Karl et al, 2015 authors are in the gang for life, and its a reputational death sentence if they betray that fielty.

    • “So you are basically stating that all major providers of temperature series of either”

      No-one is saying that. Because the satellite and weather balloon sets don’t aren’t being criticized. Do you have an answer for why the data sets that havent been subject to thousands of adjustments aren’t matching up to those that are?

      • “Mark Buehner

        August 14, 2015 at 7:50 am
        Do you have an answer for why the data sets that havent been subject to thousands of adjustments aren’t matching up to those that are?”

        +1

    • @sergeiMK

      Do you have a plausible explanation for the increasing divergence of surface and satellite records? Unless you do, you can’t escape the choice.

      Actually, you don’t need to choose — there is no contradiction between incompetence and intentional data distortion. The climate science “community” seems to be overrun with people who are good with numbers and computers, but not with actual science. These people engage too much in data adjusting, mangling, and redigesting, and too little in designing novel experimental strategies and measurements to actually test, and potentially falsify, their hypotheses.

      • Perhaps too many of them grew up in the virtual world of computers, software and videogames and graduated from schools where everybody got trophies and nobody ever failed or was told they’re wrong. They can’t cope with being wrong and have built up defense mechanisms to avoid ever having to admit failure.

    • And lets set aside any accusations of bias, much less fraud. How do you explain the first graph in this post? All things being equal, shouldn’t adjustments to the dataset tend to even out between positive and negative over time? Or more simply- why is it that the farther back in time you go, the more net negative adjustments there are, while the farther forward, the more positive adjustments? Is there an explanation for that?

      • The first graph is not Time vs Adjustments, it’s Co2 Vs adjustments. Since Co2 is increasing, it’s similar to adjustments over time, but the adjustements over time graph would be much more noisy. The fact that this is less noisy, shows that it is more likely the actual source of adjustments: they are not just adding upward trends, they are tuning it to Co2.

      • Time and CO2 for the past 65 to 100 years are virtually identical.
        It was, IMO, the genius of Tony Heller to translate the time side of the graph into CO2 concentration. This cuts through the murk, and says two things at once in a way which is more impactful than either at a time.
        The graph is not appreciably different if done from a time perspective. In fact, do you know that it would be noisier?
        Was the sawtooth CO2 graph used, or the smoothed chart? It maters not anyway…the genius is using CO2 which makes it plain what the desired effect of the adjustments is.
        One cannot separate out that this was contrived. If it was not, there is no chance of the graph looking as it does.
        All of the Climategate and other emails, in which collusion was not just implied but discussed openly, together with the top graph, makes in obvious to anyone who is willing to be honest exactly what has occurred.

    • Given the methodic harassment of those raising critical questions.
      How likely do you think it is that someone will risk their job, career or professional position and give voice to an argument against misconduct?

      Here´s a comment which seems to be from an insider:
      “Supposedly, NOAA has a policy protecting scientist from retaliation if they express their scientific opinions on weather-related matters. Never the less, we who don’t buy into the AGW hypothesis are reluctant to test this. Just look at how NOAA treated Bill Proenza for being an iconoclast. So we scurry along the halls whispering to each other, “The Emperor has no clothes.” ”

      https://wattsupwiththat.com/2015/07/15/thanks-partly-to-noaas-new-adjusted-dataset-tommorrow-theyll-claim-that-may-was-the-hottest-ever/#comment-1985842

    • This is quite a whopper of a straw man argument for so early in the morning.

      What makes you think that 1000s of scientists all over the globe are in charge of producing temperature datasets? Could it actually be that 1000s of scientists all over the globe are looking at the data produced by a handful of guys and drawing conclusions from that? Since GISS and HadCRUT both use data accumulated from NOAA, could it be that any problems with the GISS and HadCRUT datasets are due to bad raw data going in (of course compounded with most likely poor algorythms). Do 1000s of climatologists need to be living in mansions for it to be a sign that they are on the take? Or could it be continued employment is enough to persuade them that global warming is a real concern? Do 1000s of people control who gets funding or is it simply a few government types deciding where the cash goes? What kind of person wants to be a climatologist these days – could it be that a high number of “save the world” environmentalists are now drawn to the field? Why do people insist there needs to be a giant conspiracy when a relatively small number of activists and carpetbaggers could be leading the CAGW charge?

      • Was it just a relatively small number of activists and carpetbaggers who produced what we are constantly reminded are “thousands of peer reviewed papers” which draw their conclusions with such universal aphorisms as “modeled, could, might, may, possibly, projected” and so forth? Or, is the entire process of paid research and grants through (mostly) universities, corrupt from top to bottom?

      • addenda: Aphorism was the wrong word to use in this context- should have been “descriptive term”, or some such.

      • BJ, that is some serious gathering of points to counter the Serg mis direction above. Thanks !

    • ” How can so many intelligent educated people be so incompetent? This seems very unlikely”

      I don’t really have an answer to this question but anyone who follows the news for any length of time can tell you this is not a rare event. So-called educated people believe all sorts of nonsense. Look at how many educated people went along with the post financial crisis solution to essentially “go into more debt to get back on our feet.” By the millions, educated people vote for idiots whose ideas fall apart with just a modicum of scrutiny. And certainly the history of science shows us that wrong turns and misunderstandings are apparently unavoidable. Not sure what in this world could lead someone into thinking that incompetence is “unlikely!”

      Frankly, I’m amazed that things work as well as they do on this earth!

      • Things that work have been largely done by engineers. Not only could they create instant disasters if they didn’t practice their craft diligently, skillfully and honestly. Mind you, they have the right kind of incentive. There are Engineering Acts in provinces (Canada) and states (US and other) in which an engineer can be disciplined all the way up to being barred from practice for not exercising good practice. They are specifically charged with a duty to public and worker health safety in their work and are obliged to refuse a request, even from a client, to alter design in anyway that compromises this. Further, they are obliged to report to their association where they detect unaccepable engineering practice, incompetence or fraud on the part of an engineer (usually they speak to the engineer in question or his supervisor first to point out these things).

        It is past time in this age of moral degradation to put these kinds of controls on scientists. We can no longer rely on the honesty and goodwill that science used to possess in simpler times (yes there were bad apples before, but with calculation methods at their disposal, it wasn’t difficult to scrutinize and rectify such work). Further, an upgrade of education for professors, graduates and undergraduates alike (they opened the doors and lowered standards because they received funding based on enrollment). And a corrupt funding process for research: first, we simply don’t need 10s of billions of dollars for away too many people doing the same job. The honey pot that climate science has been, resulted in a dozen different agencies in a government doing the same work, with the same equation (singular) for a third of a century. An association to control quality of work a la engineering would also prevent the coercion and bullying of young scientists into supporting a status quo. The hiring process should also be politically blind.

        The practice of climate science in the main is a disgrace. To use a word properly for once, it isn’t sustainable.

      • one should never confuse religion (faith) with science. CAGW is a religion. In the realm of science, one often finds a bit too much faith and not enough skepticism. Also, there is timidity present when one does an experiment and finds their results differ from earlier experiments. A case in point was Millikan’s oil drop experiment used to determine the charge of the electron. Apparently, Millikan’s air viscosity data was a little off and resulted in a slightly lower value. Subsequent duplication of the experiment gradually brought the number into better agreement with what we know now. However, it appears that people doing these subsequent experiments were afraid to go to the value their experiment should have provided. https://en.wikipedia.org/wiki/Oil_drop_experiment in the section about psychological effects in scientific methodology

      • It is past time in this age of moral degradation to put these kinds of controls on scientists.
        =================
        Unfortunately the courts are doing their best to ensure that engineers are exempt from public safety concerns.

        As a result of precedent (below), an engineer that is for example hired to examine a bridge or nuclear reactor and discovers that it is at grave risk of failure, has no responsibility to inform the public. Rather the courts have ruled that engineer’s responsibility is limited to informing the company that hired him/her.

        As such, the public can take no confidence in any structure or machine has been examined by engineers, because the engineers are only responsible to the company that hired them. The company that hired the engineers may have simply buried the engineer’s report because its findings would adversely affect the company’s bottom line.

        http://cenews.com/article/8359/structural-engineersmdash-legal-and-ethical-obligation-to-the-public-how-far-does-it-extend

    • sergeiMK – Haven’t you noticed that climate science takes action (almost) only when the data don’t match their expectations of warming? What I’m saying is, that if the data don’t comport with their expectations, then they do another study and that, miraculously, causes the (massaged) data, to show more warming. See Cowton and Way. GISS adjustments over time. There are more.

      But, OTOH, if the data confirm the expected warming, no additional studies are done.

      • Such as, up until 1996 while the temperature increase was closely tracking the CO2 increase, nobody felt any need to revise, homogenize, or otherwise alter historical data. The data (they felt) supported their hypotheses.

        But for about 18 years now, the data has not supported their hypotheses, and the fervor to alter data (going back to the 1880’s!) has been increasing every year. After all, their lavishly-funded hypotheses couldn’t be wrong, could they? To admit such would have shut off the gravy train.

    • Sorry, Sergei, but you’re missing the big picture here, which begins with whether you feel the surface records are accurate or not. If you believe they are, you must state your case why. If you believe they are not, you must also state why. If the latter case, then you must first offer your own explanation as to how the scientists could have gotten it wrong.

      Only after you’ve gone through these elementary – and eminently reasonable – steps, do you have much standing to make your demands of rgb. To take the position, implicitly or explicitly, that the records’ accuracy is not relevant is a non-starter, as everything in this post depends on that basic issue.

    • Many of the major providers of temperature series are bought and sold by inept, corrupt governments and green organizations, encouraged by usefool tools/fools, such as Pope..

      1 being incompetent.– Definitely not incompetent, definitely conniving.
      2 purposefully changing the data to match their belief. — Definitely data manipulation. Anything for a Grant buck and to contribute to the greatest fraud/theft in human history.

      Will these people/scumbags ever face justice???

    • I don’t think “purposefully changing the data to match their belief” necessarily means fraud (at least not in the sense of advancing a known falsehood). More likely is that these are true believers who understand that science requires that the data match their belief. When it doesn’t, they conclude that it’s the data that must be wrong, not the belief. So they find ways to make the data “right.”

      • Jeff.
        A kinder gentler Machine gun man, will still wilfully kill.
        So kinder gentler data massaging / manipulation is still fraud and definitely not scientific!

        Pol pot, Stalin, Hitler. etc.. were all true believers so the killing and mayhem match their belief, did that make it right?

        Scientific data fraud is still fraud full stop!

      • Really! To hand wave away any suggestion of willful manipulation with the intent to deceive is just ridiculous. Jeff and Phil, you are making a decision to let them off the hook.
        Ted is 100% correct.

    • SergeiMK:
      According to your analysis of RGB’s and Werner’s article they are either accusing the keeper’s of the land temperature series of incompetence, unlikely, or fraud, getting more likely.

      RGB and Werner Brozek with the aid of Steven Goddard have only calculated the odds that the land temperature series divergence with the satellite temperature series are natural or unnatural.

      There was not a claim that 1000’s of scientists are in a conspiracy.

      However, if you bother to brush up on your climategate emails, you’ll quickly learn that a few small teams running certain land temperature series are fully immersed and complicit in the global warming scam.

      It doesn’t needs 1000s or hundreds involved, it only needs a few willing to use any means to accomplish their goals; which are not the goals most people desire.

      Take a good long look at the consensus climate team. Read their email discussions. Take notice of their less than charitable condescending opinions of others along with their egos, self superiority and elitist notions.

      Look through their history of vicious public and private denunciation of any one who opposes them or, God forbid, entertains new thoughts of skepticism.

      Finally, read the article above again and then explain to yourself just how did the land temperature series get so bastardized.

      Remember, all of the owners and operators of temperature land series that have strong divergence issues have already admitted adjusting the temperature data bases; not just once, but repeatedly. Sounds like data rape to me.

    • All I can say is this. Look at Goddard’s plot above, taken in good faith (that is, I haven’t recomputed or checked his numbers and am assuming that it is a correct representation of the facts).

      It is, supposedly, the sum total of USHCN changes from all sources (as I understand it) as a function of carbon dioxide concentration, which means, since it goes back to maybe 280 ppm, that it spans a very long time interval. Over this interval, carbon dioxide has not increased linearly with time. It hasn’t even increased approximately linearly with time. It is following a hyperexponential curve (one slightly faster than exponential) in time.

      Here’s what statistics in general would have to say about this. Under ordinary circumstances, one would not expect there to be a causal connection of any sort between what a thermometer reads and atmospheric CO_2 concentration . Neither would one expect a distribution of method errors and their corrections to follow the same nonlinear curve as atmospheric CO2 concentration over time. One would not expect correctable errors in thermometry to be smoothly distributed in time at all, and it would be surprising, to say the least, if they were monotonic or nearly monotonic in their effect over time.

      Note well that all of “corrections” used by USHCN boil down to thermometric errors, specifically, a failure to correctly correct for thermal coupling between the actual measurement apparatus in intake values and the incoming seawater for the latest round, errors introduced by changing the kind of thermometric sensors used, errors introduced by moving observation sites around, errors introduced by changes in the time of day observations are made, and so on. In general one would expect changes of any sort to be as likely to cool the past relative to the present as warm it.

      Note well that the total correction is huge. The range above is almost the entire warming reported in the form of an anomaly from 1850 to the present.

      I would assert that the result above is statistically unlikely to arise by random chance or unforced human error. It appears to state that corrections to the temperature anomaly are directly proportional to the atmospheric CO2 at the time, and we are supposed to believe that this — literally — unbelievably good functional relationship arose from unbiased mechanical/electrical error and from unforced human errors in siting and so on. It just so happens that they line up perfectly. We are literally supposed to look at this graph and reject the obvious conclusion, that the corrections were in fact caused by carbon dioxide concentration through selection biases on the part of the correctors. Let’s examine this.

      First of all, let me state my own conclusions in the clearest possible terms. Let the null hypothesis be “USHCN corrections to the global temperature anomaly are not caused by carbon dioxide levels in the atmosphere”. That is simple enough, right? Now one can easily enough ask the following question. Does the graph above support the rejection of the null hypothesis, or does it fail to support the rejection of the null hypothesis?

      This one is not rocket science, folks. The graph above is very disturbing as far as the null hypothesis is concerned, especially with an overall correction almost as large as the total anomaly change being reported in the end.

      However, correlation is not causality. So we have to look at how we might falsely reject this null hypothesis.

      Would we expect the sum of all corrections to any good-faith dataset (not just the thermometric record, but say, the dow jones average) to be correlated, with, say, the height of my grandson (who is growing fast at age 3)? No, because there is no reasonable causal connection between my grandson’s height and an error in thermometry. However, correlation is not causality, so both of them could be correlated with time. My grandson has a monotonic growth over time. So does (on average, over a long enough time) the dow jones industrial average. So does carbon dioxide. So does the temperature anomaly. So does (obviously) the USHCN correction to the temperature anomaly. We would then observe a similar correlation between carbon dioxide in the atmosphere and my grandson’s height that wouldn’t necessarily mean that increasing CO2 causes growth of children. We would observe a correlation between CO2 in the atmosphere and the DJA that very likely would be at least partly causal in nature, as CO2 production produces energy as a side effect and energy produces economic prosperity and economic prosperity causes, among other things, a rise in the DJA.

      So the big question then is — why should a thermometric error in SSTs be time dependent (to address the latest set of changes)? Why would they not only be time dependent, but smoothly time dependent, precisely over the critical period known as “The Pause” where the major global temperature indices do not indicate strong warming or are openly flat (an interval that humorously enough spans almost the entire range from when “climate change” became front page news)? Why would changes in thermometry be not only time dependent, but smoothly produce errors in the anomaly that are curiously following the same curve as CO2 over that same time? Why would changes in the anomaly brought about by changes in the time of measurement both warm the present and cool the past and — you guessed it — occur smoothly over time in just the right hyperexponential way to match the rate the CO2 was independently increasing over that same interval. Why would people shifting measurement sites over time always manage to move them so that the average effect is to cool the past and warm the present, over time, in just the right way to cancel out everything and produce and overall correction that isn’t even linear in time — which might be somewhat understandable — but nonlinear in time in a way that precisely matches the way CO2 concentration is nonlinear in time.

      That’s the really difficult question. I might buy a monotonic overall correction over time, although that all by itself seems almost incredibly unlikely and, if true, might better have been incorporated by very significantly increasing the uncertainty of any temperatures at past times rather than by shifting those past temperatures and maintaining a comparatively tight error estimate. But a time dependent correction that precisely matches the curvature of CO2 as a function of time over the same interval? And why is there almost no scatter as one might expect from error corrections from any non-deliberate set of errors in good-faith measurements?

      In Nicholas Nassim Taleb’s book The Black Swan, he describes the analysis of an unlikely set of coin flips by a naive statistician and Joe the Cab Driver. A coin is flipped some large number of times, and it always comes up heads. The statistician starts with a strong Bayesian prior that a coin, flipped should produce heads and tails roughly equal numbers of times. When in a game of chance played with a friendly stranger he flips the coin (say) ten times and it turns up heads every time (so that he loses) he says “Gee, the odds of that were only one in a thousand (or so). How unusual!” and continues to bet on tails as if the coin is an unbiased coin because sooner or later the laws of averages will kick in and tails will occur as often as heads or more so, things will balance out.

      Joe the Cab Driver stopped at the fifth or sixth head. His analysis: “It’s a mug’s game. This joker slipped in a two headed coin, or a coin that it weighted to nearly aways land heads”. He stops betting, looks very carefully at the coin in question, and takes “measures” to recover his money if he was betting tails all along. Or perhaps (if the game has many players) he quietly starts to bet on heads to take money from the rest of the suckers, including the naive statistician.

      At this point, my own conclusion is this. It is long since time to look carefully at the coin, because the graph above very much makes it look like a mug’s game. At the very least, there is a considerable burden of proof on those that created and applied the corrections to explain how they just happened to be not just monotonic with time, not just monotonic with CO2, both of which are unlikely in and of themselves but to be monotonic with time precisely the same way CO2 is. They don’t shift with the actual anomaly. They don’t shift with aerosols. They don’t shift with some unlikely way ocean temperatures are supposedly altered and measured as they enter an intake valve relative to their true open ocean value verified by e.g. ARGO (which is also corrected) so that no matter what the final applied correction falls dead on the curve above.

      Sure. Maybe. Explain it to me. For each different source of a supposed error, explain how they all conspire to make it line up j-u-u-s-s-s-t right, smoothly, over time, while the Earth is warming, while the earth is cooling and — love this one — while the annual anomaly itself has more apparent noise than the correction!

      An alternative would be to do what any business would do when faced with an apparent linear correlation between the increasing monthly balance in the company presidents personal account and unexplained increasing shortfalls in total revenue. Sure, the latter have many possible causes — shoplifting, accounting errors, the fact that they changed accountants back in 1990 and changed accounting software back in 2005, theft on the manufacturing floor, inventory errors — but many of those changes (e.g. accounting or inventory) should be widely scattered and random, and while others might increase in time, an increase in time that matches the increase in time in the president’s personal account when the president’s actual salary plus bonuses went up and down according to how good a year the company had and so on seems unlikely.

      So what do you do when you see this, and can no longer trust even the accountants and accounting that failed to observe the correlation? You bring in an outside auditor, one that is employed to be professionally skeptical of this amazing coincidence. They then check the books with a fine toothed comb and determine if there is evidence sufficient to fire and prosecute (smoking gun of provable embezzlement), fire only (probably embezzled, but can’t prove it beyond all doubt in a court of law, continue observing (probably embezzled, but there is enough doubt to give him the benefit of the doubt — for now), or exonerate him completely, all income can be accounted for and is disconnected from the shortfalls which really were coincidentally correlated with the president’s total net worth.

      Until this is done, I have to side with Joe the Cab Driver. Up until the latest SST correction I was managing to convince myself of the general good faith of the keepers of the major anomalies. This correction, right before the November meeting, right when The Pause was becoming a major political embarrassment, was the straw that broke the p-value’s back. I no longer consider it remotely possible to accept the null hypothesis that the climate record has not been tampered with to increase the warming of the present and cooling of the past and thereby exaggerate warming into a deliberate better fit with the theory instead of letting the data speak for itself and hence be of some use to check the theory.

      This is a great tragedy. I, like most physicists including the most skeptical of them, believe that a) humans have contributed to increasing atmospheric CO2, quite possibly all of the observed increase, possibly only some of it; b) increasing CO2 should cause all-things-being-equal some warming shift in global average temperature with a huge uncertainty as to just how much. I’d love to be able to fit the log curve to reliable anomaly data to be able to make a best estimate of the climate sensitivity, and have done so myself, one that shows an expected temperature change on doubling of around 1.8 C. Goddard’s graph throws that sort of very simple, preliminary step of any investigation into chaos. How can I possibly trust that some, perhaps as much as all of the temperature change in the reported anomaly is representative of the actual temperature when the range of the applied corrections is as great as the entire change in anomaly being fit and when the corrections are a perfect linear function of CO2 concentration? How can I trust HadCRUT4 when it discretely adds a correction to latter day temperature estimates that are well out there into its own prior error estimates for the changed data points? I can’t trust either the temperature or the claimed error.

      The bias doesn’t even have to be deliberate in the sense of people going “Mwahahahaha, I’m going to fool the world with this deliberate misrepresentation of the data”. Sadly, there is overwhelming evidence that confirmation bias doesn’t require anything like deliberate dishonesty. All it requires is a failure in applying double blind, placebo controlled reasoning in measurements. Ask any physician or medical researcher. It is almost impossible for the human mind not to select data in ways that confirm our biases if we don’t actively defeat it. It is as difficult as it is for humans to write down a random number sequence that is at all like an actual random number sequence (go on, try it, you’ll fail). There are a thousand small ways to make it so. Simply considering ten adjustments, trying out all of them on small subsets of the data, and consistently rejecting corrections that produce a change “with the wrong sign” compared to what you expect is enough. You can justify all six of the corrections you kept, but you couldn’t really justify not keeping the ones you reject. That will do it. In fact, if you truly believe that past temperatures are cooler than present ones, you will only look for hypotheses to test that lead to past cooling and won’t even try to think of those that might produce past warming (relative to the present).

      Why was NCDC even looking at ocean intake temperatures? Because the global temperature wasn’t doing what it was supposed to do!. Why did Cowtan and Way look at arctic anomalies? Because temperatures there weren’t doing what they were supposed to be doing! Is anyone looking into the possibility that phenomena like “The Blob” that are raising SSTs and hence global temperatures, and that apparently have occurred before in past times, might make estimates of the temperature back in the 19th century too cold compared to the present, as the existence of a hot spot covering much of the pacific would be almost impossible to infer from measurements made at the time? No, because that correction would have the wrong sign.

      So even like the excellent discussion on Curry’s blog where each individual change made by USHCN can be justified in some way or another which pointed out — correctly, I believe — that the adjustments were made in a kind of good faith, that is not sufficient evidence that they are not made without bias towards a specific conclusion that might end up with correction error greater than the total error that would be made with no correction at all. One of the whole points about error analysis is that one expects a priori error from all sources to be random, not biased. One source of error might not be random, but another source of error might not be random as well, in the opposite direction. All it takes to introduce bias is to correct for all of the errors that are systematic in one direction, and not even notice sources of error that might work the other way. It is why correcting data before applying statistics to it, especially data correction by people who expect the data to point to some conclusion, is a place that angels rightfully fear to tread. Humans are greedy pattern matching engines, and it only takes one discovery of a four leaf clover correlated with winning the lottery to overwhelm all of the billions of four leaf clovers that exist but somehow don’t affect lottery odds in the minds of many individuals. We see fluffy sheep in the clouds, and Jesus on a burned piece of toast.

      But they aren’t really there.

      rgb

      • “Humans are greedy pattern matching engines” – off topic, but I’ve been waiting forever for someone to reduce humanity to a regular expression. Can I make your quote into a bumper sticker?

      • Karl et al 2015 decision to adjust more accurate buoy ss temperatures with less accurate intake temps (rather than vice versa, which would’ve had a cooling effect) “sealed the deal” for me that it is not simply confirmation bias, but willful corruption for The Cause.

      • “that is, I haven’t recomputed or checked his numbers and am assuming that it is a correct representation of the facts”

        You should. Or even try to figure what it means. 1.8&def;F in USHCN ajdustment? That needs checking.

        I presume that it means USHCN adjustment of some data (relative to what?) at some point in time (when) graphed vs the progression of CO2 rather than progression in time. Who calculated the unadjusted average? Goddard? How? Is unadjusted area weighted in the same way as adjusted? Is the difference a reflection of just comparing two different sets of stations?

        “Note well that all of “corrections” used by USHCN boil down to thermometric errors, specifically, a failure to correctly correct for thermal coupling between the actual measurement apparatus in intake values and the incoming seawater for the latest round,”

        This is bizarre. There is no SST component in USHCN.

        “Goddard’s graph throws that sort of very simple, preliminary step of any investigation into chaos. How can I possibly trust that some, perhaps as much as all of the temperature change in the reported anomaly is representative of the actual temperature”

        Start by asking why you trust Goddard’s graph.

      • Excellently argued. However, my take is a bit more dire. It has long been clear that most of the warming reported over the last 100 years was spurious and due to biased adjustments. Nevertheless, before seeing Goddard’s graph, I would have agreed that the adjustments might have been made in good faith.

        But I can no longer believe this now. It is simply inconceivable that an uncoordinated sequence of more or less honest mistakes would produce the almost perfect correlation in this graph. The adjustments must have been carefully calibrated to enhance the correlation between CO2 and temperatures. This graph is a smoking gun.

      • Maybe we should instead start by asking why we trust adjustments made by people getting paid to produce a certain result?

      • “All I can say is this….”

        Followed by 28 or so paragraphs of increasing length.
        Do not get me wrong, I loved reading it all…but this is funny!

      • Robert, one reason we conclude that there is conscious mendacity going on is because with each successive update to the “data”, they apparently warm the present and cool the past. So that implies that a given day’s temperature data get bumped up first, then up again a few more times, and then … after a while they start to get bumped down. And then, it’s pretty much down-down-down from there on out.

        So my current null hypothesis is that the only conceivable rationale for such changes is to conform the data to a predetermined, pre-desired result of “warming”. In order to falsify my hypothesis, I submit that you have to come up with some other conceivable rationale for such an insane pattern of changes. UHI clearly doesn’t fit the bill, because the actual UHI effect in a particular location doesn’t go in one direction in one period of time, and then swerve around and careen in the opposite direction later on. Neither does time of observation bias. And if there’s anything else, I don’t believe they’re disclosing it, which means that under the rules of Modern Science, we are required to consider the results completely spurious until whatever it is, is adequately documented and explained. And unless that ever happens (which is about as likely as all those thermometers sprouting wings and flying away), we must assume for all practical purposes that the reason for the ludicrous adjustments is to defraud the public.

        Lastly I’d point out that you’ve shifted the goalposts a bit on what is necessary for confirmation bias. You write, “All it requires is a failure in applying double blind, placebo controlled reasoning in measurements.” You neglected to mention that it’s possible for such a “failure” to occur on purpose, but you seemingly want us to conclude that since it could have all just been incompetence and the most extreme stupidity, that we should assume it was unless we know otherwise. I assume no such thing, because this matter is no longer a nice, folksy earth-science project. It is far into the realm of forensic accounting and criminal investigation, and so I try to approach it in that way, considering the amount of money and other resources that are on the line.

        Sincerely,

        Richard T. Fowler

      • You should. Or even try to figure what it means. 1.8&def;F in USHCN ajdustment? That needs checking.
        _______________________________
        Better yet show why Nick Stokes other than it’s in your personal interest to challenge skeptics, eg, you are paid to do so, no?

      • Nick Stokes says “Start by asking why you trust Goddard’s graph.”
        ++++++++++++++++++++++++++++++
        Why not show why you do not trust Goddard’s graph?

      • “Why not show why you do not trust Goddard’s graph?”

        Skeptics! You have no link to the original. You have no idea what version of USHCN he is talking about. You have no idea how the graph was made, or the basis for it. But you trust it, because it looks as you would like.

        My version is here. The adjustment is nowhere more than half what Goddard claims. I explain how I calculated it. I give the code. I show a complete breakdown by states.

        And here I show why the major adjustment, TOBS, is readily quantified and absolutely required.

      • Nick Stokes,

        I don’t see a whole lot of difference between Goddard’s chart and yours:

        The shape of the rise is just about the same, no? Both graphs are low in mid-century, and rise from there. That is the issue, it’s not about not a fraction of a degree. No one knows the planet’s temperature as accurately as they claim.

      • Nick Stokes
        August 14, 2015 at 4:18 pm

        “Why not show why you do not trust Goddard’s graph?”

        Skeptics! You have no link to the original. You have no idea what version of USHCN he is talking about. You have no idea how the graph was made, or the basis for it. But you trust it, because it looks as you would like.
        +++++++++++++++++++++++
        No, I take neither for granted but I’m experienced enough to believe it’s in your personal financial and ideological interest to assert such.

      • I feel better about being skeptical than I would about being unconcernedly and unanalytically credulous.

      • Note well, Nick Stokes ignored my assertion that he is paid to refute skeptics on skeptic climate blogs. I will not be surprised when his back channel emails are discovered and published in a climate gate like scenario.

      • Nick Stokes description of adjustments are as of 2014, does not account for the 2015 adjustments. I assume Tony Heller’s does but the good point is made by Nick that we do need have more clarity how the Goddard plot was determined.

      • Prof. Brown says: “I’d love to be able to fit the log curve to reliable anomaly data to be able to make a best estimate of the climate sensitivity, and have done so myself, one that shows an expected temperature change on doubling of around 1.8 C. Goddard’s graph throws that sort of very simple, preliminary step of any investigation into chaos.”
        I’m with you on that one! Surface data is so intermittent and scattered and needs so much processing to be morphed into a global average that the result says more about the processing that it does about the observations. It’s sort of like making a good cheddar from milk; with more processing you get Velveeta ™. So-called “global means” from surface data are meaningless.
        I got around that issue by looking at MSU satellite temperatures, which do sample the entire globe (except for a dot at each pole). If I take 36 years of that, subtract out the volcanic effects of el Chichon and Pinatubo, I get a Climate Sensitivity of 0.7C (more at http://www.esrl.noaa.gov/gmd/publications/annual_meetings/2015/posters/P-48.pdf
        given at the “2015 NOAA ESRL GLOBAL MONITORING ANNUAL CONFERENCE”
        http://www.esrl.noaa.gov/gmd/publications/annual_meetings/2015/ )
        Taking that result at face value means the “Adjustments” more than triple the actual climate effect of increasing CO2.

      • “Note well, Nick Stokes ignored my assertion that he is paid to refute skeptics on skeptic climate blogs.”

        Yes, it is yet another assertion here put with no evidence or basis whatever, and should be ignored. It is of course totally untrue. And no-one would pay to refute such a muddle as this.

      • Seems Climate Audit disagrees with your factless dismissal. Whether it is true or not may be in doubt. However, the no evidence part is patently false.

      • Robert,
        Thank you very much for this excellent analysis.

        There’s one obvious point that is true, irrespective of any details of the actual adjustments.
        As you pointed out, the adjustments are similar to the actual overall trend. In other words, a large part of the trend comes from the adjustments and not from the raw data.

        Surely, if such enormous adjustments are really required, then the original data is worthless and therefore the entire surface record is worthless. Is there any other science that would allow this to happen? Thank goodness for the satellite and weather balloon records.

        I think this may well be the biggest scientific fraud in history. But quite possibly it is not conscious or organised fraud. As you point out, it can arise out of huge numbers of decisions over many years. Those decisions will be strongly influenced by any unconscious bias.

        However, if the evidence of wrongful adjustment is strong enough, and the scientists continue to ignore it, then it does become conscious fraud.
        Chris

      • Heller’s graph is veeery disturbing. I’d like to see a peer reviewed paper on this, anyone volunteers?

        Frankly, rgb explained in great detail how you can accidentally end up with high correlation between the two. What one needs is just a complicated system with lots of potential, detectable or estimateable biases and scientists who calculate the expected result using a CO2 graph. It’s the bias which kicks in by peeking at the result before locking your answer.

      • Hugh:

        You ask

        Heller’s graph is veeery disturbing. I’d like to see a peer reviewed paper on this, anyone volunteers?

        A group of us produced such a paper many years ago. Please see here and especially its Appendix B.

        However, as as that link and my post to sergeiMK report, it is not possible to publish such a paper (n.b. my post to sergeiMK is still in moderation and I have linked to where I anticipate my post will appear if it comes out of moderation).

        Richard

      • “Humans are greedy pattern matching engines” – off topic, but I’ve been waiting forever for someone to reduce humanity to a regular expression. Can I make your quote into a bumper sticker?

        Sure. I’m trying to think about how to make it recursive, since a regular expression can be fed into a pattern matching engine to make it greedy…;-)

      • richardscourtney
         
        August 15, 2015 at 4:54 am

        But the MGT data sets often change. The MGT data always changed between submission of the paper and completion of the peer review process. Thus, the frequent changes to MGT data sets prevented publication of the paper.

        Thank you! The above caught my eye. With the major adjustments over the last 3 months, the next group may have the same problem. History is repeating itself.

      • We apparently see “cooling bias” where there is none as well, such as with the MMTS stations. Assuming that the MMTS units were properly selected and calibrated, then compared with the Stevenson Screens, any bias would logically be attributed to the Stevenson Screens, rather than to the newly calibrated MMTS units.

      • rgb says:

        You can justify all six of the corrections you kept, but you couldn’t really justify not keeping the ones you reject.

        For such a few, common words, that explains a whole lot.

      • Werner Brozek:

        You quote from here where it says

        But the MGT data sets often change. The MGT data always changed between submission of the paper and completion of the peer review process. Thus, the frequent changes to MGT data sets prevented publication of the paper.

        and you comment on that by saying

        Thank you! The above caught my eye. With the major adjustments over the last 3 months, the next group may have the same problem. History is repeating itself.

        True, but in the context of “Heller’s graph” I think this quotation from the link is more important.

        We determined that if MGT is considered as a physical parameter that is measured, then the data sets of MGT are functions of their construction. Attributing AGW – or anything else – to a change that is a function of the construction of MGT is inadmissable.

        Richard

      • Nick Stokes
        August 14, 2015 at 4:18 pm
        Skeptics! You have no link to the original. You have no idea what version of USHCN he is talking about.
        ====
        ROTFLMAO…you do not have any idea what you just said!!!

      • philjourdan August 15, 2015 at 5:40 am
        Seems Climate Audit disagrees with your factless dismissal. Whether it is true or not may be in doubt. However, the no evidence part is patently false.

        Who are you talking to?

    • You need to rethink the 1000s of scientists all over the world. There is absolutely no eveidence for your statement.Whereas, 31000 scientist did sign a letter refuting the premise of significant AGW.

      • “Whereas, 31000 scientist did sign a letter refuting the premise of significant AGW.”

        No, that is incorrect. Medical doctors are not scientists unless they are directly involved in medical research. The same is true for mechanical engineers, civil engineers, nuclear engineers, and software engineers. Oh, and what gives these disciplines the background to judge research papers in atmospheric sciences?

        If a petition saying vaccines were harmful were signed by mechanical engineers, civil engineers, and software programmers, would you believe it just because they are “scientists” to use your terminology?

      • How about you show us the petition of people who swear publically by the conclusions and methodology of the Warmista Brotherhood?

      • Chris, leave us nuclear engineers out of your list. We understand both radiation transport and Navier-Stokes. And, I might add, the Courant–Friedrichs–Lewy condition.

      • As a Physicist BSc MSc would it be OK if I signed it. Chris might I suggest that you look at the qualifications of IPCC “scientists” first. I think you might be shocked.

      • Chris,

        Give it up. The true ‘consensus’ is heavily on the side of skeptics of dangerous man-made global warming. The OISM Petition required only a few months to collect more than 31,000 co-signers; it was limited to U.S. scientists, co-signers must have earned a degree in one of the hard sciences, and each hard copy with their signature had to be mailed in — no emails accepted.

        As I’ve challenged your kind repeatedly in the past: post the names of even ten percent of alarmist scientists who contradict the OISM statement.

        Can’t do it? No one else could, either. So I’ll make it ten times easier: post the names of just one percent of people with degrees in the hard sciences who have ever contradicted the OISM statement.

        See how ‘consensus’ works? The term is pretty meaningless in science. But the numbers here completely destroy the alarmist claim that they have any sort of consensus at all. In reality, they are a small, loud clique of self-serving folks who have been crying “Wolf!” for decades. But there is no wolf, and there never was.

      • Menicholas, exactly how have I mischaracterized the petition? The petition site itself shows the disciplines of the signatories. Here are the numbers for some of the ones I mentioned: Medicine – 3,046; nuclear engineers – 223; computer science 242. Civil is not shown, I guess it falls under Engineering. I looked at the curriculum of a pre med student. There is virtually nothing in the course load that would give them an understanding of atmospheric physics. For engineering majors (of which I am one), there is typically no more than 1 year’s worth of Physics, which does not delve into atmospheric sciences. So exactly how have they been given the tools to judge the merits of papers on climate change?
        As far as a petition saying that AGW is real, since when does the validity of scientific research rely on petitions? Is that how we moved forward on vaccines, or space research, or advances in civil engineering? Of course not.
        dbstealey said: “The OISM Petition required only a few months to collect more than 31,000 co-signers; it was limited to U.S. scientists, co-signers must have earned a degree in one of the hard sciences, and each hard copy with their signature had to be mailed in — no emails accepted.”
        First off, as I noted above, a degree in the hard sciences does not qualify someone to be knowledgeable on atmospheric physics. I have a BSEE and MSEE from a Pac-12 university, there was no course content on atmospheric physics in the curriculum. Zero. Someone with an engineering degree MAY immerse themselves enough to be knowledgeable, but it is by no means a certainty.
        Secondly, even if you decide that ALL engineers/doctors/programmers are qualified to vote on this topic, how do you know their degrees are valid? Just because they wrote it on a card? Most universities in the US do not allow online access to the names and fields of their graduates for confidentiality reasons. So there is no way to even validate the accuracy of many of the submitted cards, other than blind trust.

      • Chris,
        I am not going to argue with you about it. It speaks for itself.
        Everyone can judge whether you fairly represented what the petition does and does not demonstrate.

        Again, where is the petition from the people who claim to have a consensus?
        If you cannot show one, what does that tell you?
        What does that tell everyone?

        As to the person who claims that some people attempting to discredit the petition by sending in fake submittals, that issue was dealt with and is explained on the site.

      • Menicholas said “I am not going to argue with you about it. It speaks for itself. Everyone can judge whether you fairly represented what the petition does and does not demonstrate.”

        Since I took data directly from the site, I would be very surprised if someone can demonstrate that I misrepresented it. Are there some medical doctors who are avid climatologists in their spare time? I am sure there are, but I highly, highly doubt it is more than 5% of the total numbers.

        “Again, where is the petition from the people who claim to have a consensus? If you cannot show one, what does that tell you? What does that tell everyone?”

        What it tells me is that science consensus is not done through an open petition. Can you name me one scientific area where the use of an open petition was a key factor in assessing which position was correct? Even 1?

      • For years, there was a claim by warmistas that the only people who doubted any aspect of the CAGW alarmist meme were a few fringe kooks, cranks, and uneducated nitwits, plus a few conservatives who just argued against any literal cause on general principle, and some scientists who were paid by the oil companies to make stuff up.
        The petition debunked this notion in short order.
        In case you were unaware, a large chunk of warmista jackassery consists of making one ridiculous claim after another, and the above was one of them.
        Every such new claim has ben disproven.
        In most cases, the exact opposite of what was claimed turns out to be the actual truth.

      • Of course, if you are now trying to imply that the petition was produced because it was skeptics who were saying that science is advanced by a process of voting, then you are either uninformed, new to this whole issue, or just tossing out a fake argument.

      • Please excuse my many typos.
        In my comment time stamped 11:51, it should read: “…any liberal cause…”

      • BTW, as DB rightly points out, go ahead and subtract out whichever groups you want.
        The remainder is still a large group.
        And this is by no means a complete list of people in this country with relevant degrees or knowledge who would sign had they known about it, or if they felt free to do so.
        Many people could or would not because of the often drastic consequences of taking a public anti-CAGW stance, or simply did not know about it. I would guess it represents a small fraction of those who feel this way.

        I wonder…do you happen to think that the smartest or most informed people are working in fields of inquiry for which they are the most intuitively gifted or knowledgeable in the country or the world?
        I for one happen to know for a fact that this is not the case.
        Many working in the climate science field are barely, or not at all, of a scientifically literate educational or mental level, IMO.
        And many who publish are not even trained in anything related to climatology or even an Earth science.
        So there is that, which alone makes what you are saying inconsequential.

        If you would like a list of such people who are nonetheless hugely prominent and oft quoted, and somehow considered “experts”, I am sure many here would be happy to provide you with such.
        Then again, if you need such a list, you need to do a LOT more reading on the subject.

      • Chris says:

        What it tells me is that science consensus is not done through an open petition. Can you name me one scientific area where the use of an open petition was a key factor in assessing which position was correct? Even 1?

        Thank you. There is not much difference between what you label an “open petition” and what the alarmist crowd labels a “consensus”. The only real difference is that the consensus is heavily on the side of the OISM statement, not on those opposing it. And the Petition was a “key factor” in scuttling the Kyoto treaty, therefore it was accepted that the OISM’s conclusions were correct.

        Next, you ask:

        Are there some medical doctors who are avid climatologists in their spare time?

        Misdirection. Your original comment was that MD’s are on the list without having an education in one of the hard sciences. That is wrong.

        A medical doctor can only be on the OISM petition if he/she earned a degree in one of the hard sciences. If they got their MD via a bachelor’s degree in English Lit or Sociology, they are ineligible. And there are almost no “climatologists” anywhere, who earned a degree in “Climatology”. Very few universities offer such a degree, and the ones that do haven’t offered it for very long.

        Your argument that climatologists are the only ones who can really understand the subject is complete nonsense. Climatology is not a priesthood. Anyone with basic knowledge of physics, math, chemistry, geology, or related fields is as capable of understanding the discussion as a ‘climatologist’. In fact, if you use Michael Mann as an example, there are plenty of people who know far more about the subject. Mann’s treemometers are widely ridiculed, and for good reason.

        Next, you asssert that…

        …a degree in the hard sciences does not qualify someone to be knowledgeable on atmospheric physics.

        More nonsense. Anyone with a degree in the hard sciences is fully capable of understanding ‘atmospheric physics’. To destroy that silly argument, I note that Prof. Richard Lindzen, author of twenty dozen published, peer reviewed papers on global warming, climate change, and other climate-related subjects, was the head of M.I.T.’s Atmospheric Sciences department for many years. FYI, Dr. Lindzen does not agree at all with the ‘dangerous man-made global warming’ scare. He says it is politics, not science. He also agrees with the OISM statement, saying that CO2 is harmless, and beneficial to the biosphere. Who is the authority we should listen to? You? Or Dr. Lindzen?

        Next, I asked you to post the names of just one percent of the OISM’s numbers, showing people with degrees in the hard sciences who have ever contradicted the OISM statement. You avoided answering. That is only about 310 names, vs the OISM’s 31,000. It is pretty clear that the OISM statement is the general consensus, and that those contradicting it are a very small clique of self serving rent-seeking scientists. If I’m wrong, post the names of 300 scientists who contradict the OISM’s statement. I don’t think you can come up with even a hundred names.

        The alarmist contingent’s consternation over the OISM Petition is evident. Ever since the Kyoto Protocol failed, largely due to those scientists, the climate alarmist crowd has been trying to attack the Petition. Your talking points appear to be copied straight from various alarmist blogs.

        Those arguments have completely failed. First it was the claim that the ‘Spice Girls’ were co-signers. Then it was ‘Mickey Mouse’, and similar fictional characters. But since every co-signer is listed online, those claims were easy to debunk. And your claim that a graduate’s degree is somehow top secret is nonsense. Those folks are proud of their education, and the schools are proud of their alumni. They don’t try to hide it.

        Next, I note that your attacks on the OISM Petition never question its conclusions: that the rise in CO2 is harmless, and beneficial to the biosphere, and that human emissions have never been shown to cause global harm. You are continuing to deflect from the statement’s conclusions by using ad-hom attacks, because the real world has supported the OISM statement — and it is busy falsifying the climate alarmist predictions, not one of which has ever come true.

        So, Chris, if you would like to discuss the science aspect of human CO2 emissions, I’ll be happy to oblige. It would be in your best interest, because you have decisively lost the argument that there is anything wrong, underhanded, or improper about the original OISM Petition.

      • Hi mark,

        You’re asking the wrong person because I don’t know who is and who isn’t qualified. But the point is moot because following the failure of the Kyoto Protocol in 1997, the OISM organization stopped accepting new co-signers.

        A few years ago I wrote them and asked for a card. They replied that they were no longer adding names to the list. That’s why the total number of co-signers has remained at 31,487.

      • Exactly DB.
        That list would be enormous if it was not a one time effort.
        Any idea how long it did collect?

      • Menicholas,

        As I recall, it took about a year or maybe a little less. It was circulated leading up to the meeting in Kyoto, and a few names were added afterward. Then the list was closed to new signers. But that’s just my recollection.

        In any case, I agree the list would be enormous if it had been left open to new co-signers. That statement has stood the test of time. It is as true now as it was in 1997.

        I think that if that same statement was opened to anyone with a degree in the hard sciences, and offered worlwide for a few years, there would probably be many millions of co-signers.

      • Menicholas said: “Of course, if you are now trying to imply that the petition was produced because it was skeptics who were saying that science is advanced by a process of voting, then you are either uninformed, new to this whole issue, or just tossing out a fake argument.”

        No, what I am saying is that this doesn’t prove anything, other than the fact that 31,000 people signed the petition. There are roughly 10M people with engineering degrees in the US, 1M doctors and 1-2M software engineers. So 31,000 out of 12M, or .26% of the total, have signed the petition.

      • dbstealey said: “Thank you. There is not much difference between what you label an “open petition” and what the alarmist crowd labels a “consensus”. The only real difference is that the consensus is heavily on the side of the OISM statement, not on those opposing it. And the Petition was a “key factor” in scuttling the Kyoto treaty, therefore it was accepted that the OISM’s conclusions were correct.”

        No, the AGW believer consensus was arrived at by the peer reviewed research of 1000s of climate scientists around the world. That is a completely different methodology than a survey sent to people who have technical backgrounds. Regarding the Kyoto treaty – number 1, where is your evidence that this played a KEY role in the vote? Second, the voting down of something due to a petition does not make a petition correct. That’s a laughable assertion.

      • dbstealey said” “A medical doctor can only be on the OISM petition if he/she earned a degree in one of the hard sciences. ”

        Wrong. I randomly chose one name from the list of MDs on the petition. Alan V. Abrams, MD. I googled him – he received is BA from Harvard. Not a BS degree, and BA. So that is not a hard sciences undergrad degree.

        “Your argument that climatologists are the only ones who can really understand the subject is complete nonsense. Climatology is not a priesthood. Anyone with basic knowledge of physics, math, chemistry, geology, or related fields is as capable of understanding the discussion as a ‘climatologist’.”

        I didn’t say it was a priesthood. And yes, people who don’t have climatology degrees can become knowledgeable. But the can word is “can”. The petition authors have provided zero proof that the signatories have any acquired expertise in climatology.

        So, once again, I fully agree that someone lacking a degree in atmospheric sciences CAN become proficient, such as Dr. Lintzen, but possession of a hard sciences degree does not in any way indicate that someone HAS become proficient in climatology. If you cannot understand or acknowledge that distinction, it is a waste of time to continue this discussion.

        “Your talking points appear to be copied straight from various alarmist blogs.”

        Lol, nice try. I think and write for myself.

        “You are continuing to deflect from the statement’s conclusions by using ad-hom attacks, because the real world has supported the OISM statement — and it is busy falsifying the climate alarmist predictions, not one of which has ever come true.”

        I am not deflecting from the petition statement, not in any way. The real world is not supporting the OSIM statement – perhaps in your WUWT bubble it is, but not elsewhere.

        Here’s an example. Shell just withdrew from ALEC, the most important lobbying organization in the US for legislative action, due to ALEC’s denial that AGW is an issue. Here is Shell’s position on climate change: “At the same time CO2 emissions must be reduced to avoid serious climate change. To manage CO2, governments and industry must work together. Government action is needed and we support an international framework that puts a price on CO2, encouraging the use of all CO2-reducing technologies. Shell is taking action across four areas to help secure a sustainable energy future : natural gas, biofuels, carbon capture and storage, and energy efficiency.”

        Even the largest oil companies in the world say AGW is real and is occurring.

      • mark,

        Somewhere on the OISM website I read that an M.D. must have a degree in the hard sciences in order to co-sign. I also told you that no more co-signers have been accepted since around the end of the ’90’s, so the question is moot. Furthermore, nothing is stopping you from doing your own homework, instead of constantly pestering others to do it for you. My comments speak for me, not for anyone else. And I sure don’t do homework for anyone badgering me.

        You’re just deflecting from the fact that I have proven beyond doubt that the so-called ‘consensus’ is totally on the side of skeptics of ‘dangerous man-made global warming’. The false belief that there is any ‘consensus’ of alarmists that outnumbers scientific skeptics has been shown to be nothing but hot air. You’ve lost the ‘consensus’ argument. It was never true.

        Your side lost the science debate, too: either produce testable measurements quantifying the fraction of man-made global warming (MMGW) out of total global warming, or you’ve got nothin’. In that case, suck it up. Because you don’t have data, all you have are conjectures; opinions.

        **************************************

        Chris says:

        …what I am saying is that this doesn’t prove anything… There are roughly 10M people with engineering degrees in the US…&blah, blah, etc.

        Chris, are you really unable to comprehend a few simple facts? You want someone to “prove” something for you. But proof is for mathematics. You don’t get to say you’ve ‘proved’ a hypothesis or a conjecture. In science, nothing is proven no matter how much supporting evidence is presented. But it’s easy to falsify a conjecture or a hypothesis.

        All it takes to falsify a conjecture like ‘dangerous MMGW’ is one contrary fact. Such as this fact: CO2 has risen steadily for decades, but global T has remained flat. That falsifies your debunked CO2=dangerous MMGW’ conjecture. It’s a dead duck. Sorry about that.

        Next, you drag out that old canard (another dead duck), pretending that the OISM Petition must be compared with everyone in the country; maybe everyone in the world… do I hear ‘everyone ion the Solar System’?

        Wrong. Doesn’t work like that, as statistician William Briggs has regularly pointed out. The only subset you may compare the 31,487 OISM co-signers with is another subset of equally qualified individuals, who have taken a position contradicting the OISM statement. Briggs can be contacted on his blog on the sidebar here. Ask him if your so-called “methodology” is anything but rank nonsense. Go ahead, I’ll wait here. Report back.

        Finally, I have repeatedly challenged you to produce, not 10% (3,148) of the number of OISM scientists who say the OISM statement is wrong, but only 1% (314) names of scientists who state that the OISM statement is wrong. Or even a hundred!

        You can’t even get a hundred named scientists who have ever stated that the OISM statement is wrong, compared with 31,487 who have publicly signed their names to that statement. Instead, you constantly hide out from answering my challenge. You change the subject, and move the goal posts, and fabricate baseless, unrelated assertions, and you garble statistics, and in general, you reply as if you’ve got nothin’. Instead of answering, you misdirect, avoid and deflect. Because you’ve got nothin’.

        Face it, Chris, we’ve seen all your same debunked, tired, falsified, desperate, illogical arguments before. You’ve said nothing original in this thread, you just parrot the misinformation you’ve been spoon-fed by people like John Cook. Try to think for yourself for a change.

        Now, if you want to discuss the science behind the OISM statement instead of deflecting again, then as usual I am always ready for that. You can start with the same challenge I gave ‘mark’ above:

        Either produce measurements quantifying the fraction of man-made global warming (MMGW) out of total global warming, or you’ve got nothin’.

        Answer that, if you if you really believe that the real world supports you. Quantify MMGW with a verifiable, testable measurement. If you can, you will be the first, and on the short list for a Nobel Prize.

        The fact is that global warming from all causes has stopped, and not one scary prediction from the climate alarmist contingent has ever come true. Your side is a combination of Chicken Little and the Boy Who Cried “WOLF!!”. You have ended up with zero credibility, because you try to argue without empirical facts, observations, and evidence showing either the predicted runaway global warming, or that any other alarmist prediction has ever happened.

        The rest of your comment is anti-science propaganda, straight out of SkS. Quoting Big Oil as your “authority” is amusing, but it is no more credible than any of your other repeatedly falsified beliefs. What, you think they don’t have a self-serving interest in this debate??

      • mark,

        The problem is that you lost the original argument, so now you’re tap-dancing. I made a statement. If you think you can prove it’s wrong, have at it.

        And I note that the alarmist contingent continues to avoid science, and instead keeps concentrating on deflection, ad-homs, etc.

        That’s because Planet Earth is decisively proving your ‘dangerous MMGW’ conjecture is nothing more than amusing nonsense. It did not happen as predicted. Therefore, it was WRONG. Falsified. Next…

        …And still waiting for those testable, verifiable measurements quantifying the fraction of MMGW, out of global warming from all sources including the natural recovery from the LIA.

        No wonder you’re hanging your hat on ad-homs and deflection. You haven’t got any MMGW measurements. Really, you’ve got nothin’.

        And about those fictional alarmist scientists on record as contradicting the OISM statement. Got fifty? Got twenty? Got a dozen?

        Nope. You’ve got nothin’.

      • dbstealey,

        I’ll ignore your initial paragraph about proof since Mark thoroughly covered that. To summarize, I guess it’s not ok for me to use the word prove, but it is perfectly ok for you to.

        You then say “All it takes to falsify a conjecture like ‘dangerous MMGW’ is one contrary fact. Such as this fact: CO2 has risen steadily for decades, but global T has remained flat. That falsifies your debunked CO2=dangerous MMGW’ conjecture. It’s a dead duck. Sorry about that.”

        False, your statement is not true. First off, as is acknowledged on this site, your statement about T vs CO2 is not true for the other temperature data sets besides RSS. Secondly, even for RSS data, T is clearly rising, and has continued to rise after pauses of several years up to 2 decades. So your refutation is a dead duck. Sorry about that.

        “Next, you drag out that old canard (another dead duck), pretending that the OISM Petition must be compared with everyone in the country; maybe everyone in the world… do I hear ‘everyone ion the Solar System’?”

        Interesting, when the 97% of climate scientists say AGW is real was posited, the refutation was based on the fact that only a very small % of all climate scientists were surveyed. Yet when I apply the same logic to the OSIM claim, you say that technique is not valid. Sorry, you can’t have it both ways.

        “The only subset you may compare the 31,487 OISM co-signers with is another subset of equally qualified individuals, who have taken a position contradicting the OISM statement.”

        False, that is an untrue statement. First, OSIM never has published how many cards were sent out, so we don’t even know how many possible respondents declined to sign the card. That of course is a critical factor, which is ignored by you and the OSIM people. Secondly, as I have made clear above, the respondents do not have demonstrated expertise in climatology. Say I put out a petition on cancer vaccines, and get 31,487 engineers, software programmers and chemists to sign it. Do you really believe for 1 second that my petition should carry more weight with the AMA and the conclusions of cancer vaccine researchers? That’s the analogy that you are proposing. It’s absolutely preposterous.

        “Finally, I have repeatedly challenged you to produce, not 10% (3,148) of the number of OISM scientists who say the OISM statement is wrong, but only 1% (314) names of scientists who state that the OISM statement is wrong. Or even a hundred!”

        838 actual experts in climatology as opposed to your expert medical doctors, etc. Here you go: https://www.ipcc.ch/pdf/ar5/ar5_authors_review_editors_updated.pdf

        ” Quoting Big Oil as your “authority” is amusing, but it is no more credible than any of your other repeatedly falsified beliefs. What, you think they don’t have a self-serving interest in this debate??”

        How specifically is Big Oil’s interest served by taking this position? How is their position served by advocating for a carbon tax?

        “Answer that, if you if you really believe that the real world supports you. Quantify MMGW with a verifiable, testable measurement. If you can, you will be the first, and on the short list for a Nobel Prize.”

        I’ve posted this 3 times to you in the past, and every time you’ve ignored it: http://newscenter.lbl.gov/2015/02/25/co2-greenhouse-effect-increase/

      • Chris says:

        even for RSS data, T is clearly rising, and has continued to rise

        Total baloney. Your baseless assertion is debunked by reality. Here is RSS data, overlaid with rising CO2:

        http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend/plot/esrl-co2/from:1997.9/normalise/offset:0.68/plot/esrl-co2/from:1997.9/normalise/offset:0.68/trend

        Your confirmation bias gives you a way to cherry-pick factiods that are provably false. The chart above demonstrates the extent of your religious eco-belief. Global warming stopped more than 18 years ago. The “pause” is accepted by the IPCC, but not by you?? Satellite data — the most accurate data there is — conclusively fasifies the “dangerous man-made global warming” conjecture, your eco-Belief notwithstanding.

        Next, if you actually believe Cook’s “97%” nonsense, why argue? I can’t change your religion. But rational folks have so thoroughly deconstructed that bogus propaganda meme that anyone who still believes in it is beyond help. You couldn’t find 97% of Italians who agree the Pope is Catholic. But “97%” of scientists say that MMGW is gonna getcha? That’s so silly it’s only value is in giving skeptics something to larf at.

        Next, the deluded belief in the “consensus” is typical of people who cannot refute the repeatedly falsified “dangerous MMGW” conjecture. The “consensus” (for whatever that’s worth in science; not much) has always been heavily on the side of scientific skeptics — the only honest kind of scientists. So go on believing in that fairy tale if it fills a psychological need, but I note that you always tap-dance around my challenge to produce more named scientists who contradict the OISM’s statement than the number of OISM co-signers. That is the only way you could credibly claim that there is a ‘consensus’ supporting climate alarmism.

        But you can’t even produce 10% of the OISM numbers. You can’t even produce one percent of their number! You can’t even name a lousy hundred scientists who contradicted the OISM’s TENS OF THOUSANDS of co-signers. That is beyond pathetic. But your eco-belief will never change because religion is emotion-based. The rest of us know that 30,000+ vs less than 100 ends the argument. Case closed. You lost. Deal with it.

        Next, your Berkeley link is one big FAIL. It is merely an opinion, obviously rigged for grant trolling. There is no testability, only their assertions. I have repeatedly challenged you to produce verifiable, testable measurements quantifying the percentage of MMGW. But all your link does is assert that they have found something — but there are no MMGW percentages shown, as usual. The reason is obvious:

        If we had a verifiable measurement quantifying MMGW, then we would also have the climate sensitivity number. With that, we would be able to show precisely how much global warming would result from the current emission of CO2.

        But as we know, every such prediction has failed miserably. Rather than the predicted accelerating (runaway) global warming, global warming has STOPPED. That is yet another fact that decisively falsifies the MMGW conjecture. Of course, your religion won’t allow you to see that. But just about everyone else understands it. When the Real World repeatedly debunks a conjecture, that conjecture is kaput. It was wrong from the get-go. You just can’t admit it.

        So enough with the silly press release claims. They are bogus because they cannot accurately predict global warming. As we know, that is the climate alarmist crowd’s most glaring failure. All their endless predictions of runaway global warming due to human CO2 emissions have been flat wrong. That’s why rational folks are laughing at your greenie religion. You believe in it, but it is no more science than Scientology.

        The central fact is this: accelerating global warming was predicted for many years. That has not happened. The predictions were wrong. All of them. In any other field of science, the side making predictions that have turned out to be 100.0% wrong would be laughed into the astrology camp. But only because of the immense taxpayer loot propping it up — and the small supporting clique of eco-religious True Believers — the repeatedly debunked MMGW hoax is still alive. Barely. But it’s on its last legs, and fading fast, as anyone who reads the public’s comments under mass media articles about “climate change” can see. Even a few years ago those comments expressed concern. But no more. Now when there is an article about global warming, the comments are about 90% ridicule. The MMGW scam is on life support now, for one central reason: Planet Earth is debunking your belief system. You were wrong, end of story.

      • mark said:

        RE: Dave’s Petition

        I finally got around to reading that link. It is 100% speculation, nothing more. There is no solid evidence showing that any of the ‘Spice Girls’ names, or any other fake names, were ever on the OISM list. That is asserted repeatedly as fact. But it is no more than the writer’s opinion. He does not back it up with evidence — only with links to others, who have the same opinion.

        Now, it’s possible, even likely that a few true believer eco-activists tried that. Dr. Robinson is like a red cape to a bull; your gang would no doubt try and cause him trouble by submitting fake names. But the list has been vetted, and there are no fake names as far as I can see. Prove me wrong. Show me a ‘Spice Girls’ name, or ‘Mickey Mouse’, or anything similar.

        Next, Chris alleges that one particular MD has no science degree. But after wasting ten minutes searching for his CV including his degrees, I couldn’t find it. If Chris has it, post it here. Show all of the good doctor’s degrees. His complete educational CV will do.

        You two are desperately grasping at straws. Out of more than thirty thousand scientists, if even 1% of the names were fake (and I know of no one who claims there were ever more than a handful of fake names in the OISM list), then that still leaves more than thirty thousand scientists — versus what? You can’t even come up with a few dozen names of alarmist scientists who have publicly contradicted the OISM statement.

        Do you really want to pick this hill to die on? If I were trying to make the alarmist case, I would steer well clear of the OISM Petition. It did its job on Kyoto, and the statement is every bit as accurate today as it was in 1997. I note that you two will ‘say anything’ as usual — but you refuse to debate the statement itself. All of your comments are ad hominem attacks, or minor nitpicking items unrelated to what the OISM statement said, or links to others who have no more evidence of their beliefs than you have. Your endless deflection, nitpicking and misdirection is tedious, and it shows you’ve lost the basic science debate.

        Therefore, I will be happy as always to discuss the statement itself. My long-held position is that CO2 is harmless, and it is beneficial to the biosphere. More is better. It has been up to twenty times higher in the past, without causing runaway global warming (or any measurable global warming for that matter). It is measurably greening the planet. Yes, CO2 causes global warming. But almost all of its warming effect took place within the first ≤100 ppm. But now, at ≈400 ppm, any warming from added CO2 is far too minuscule to measure; thus, your inability to produce measurements of AGW.

        If you still continue to argue periperal issues that have nothing to do with the OISM statement itself, it will be clear to everyone that you’ve lost the debate. Why not man up for a change, and try to defend your ‘dangerous MMGW’ belief system? I think it’s because you know that the facts and evidence will bury your beliefs. But hey, give it a try.

      • Too bad you moderators can’t identify ALL of the posts.

        Too bad you can’t plug the security hole either.

        [Reply: When we start registration w/password, you will have to spam elsewhere. In the mean time, it’s a pleasure to delete all the comments you’ve wasted part of your life writing. ~mod.]

      • dbstealey said: “Total baloney. Your baseless assertion is debunked by reality. Here is RSS data, overlaid with rising CO2:….. Your confirmation bias gives you a way to cherry-pick factiods that are provably false. The chart above demonstrates the extent of your religious eco-belief. Global warming stopped more than 18 years ago. The “pause” is accepted by the IPCC, but not by you?? Satellite data — the most accurate data there is — conclusively fasifies the “dangerous man-made global warming” conjecture, your eco-Belief notwithstanding.”

        Before the RSS pause, climate skeptics said that conclusions could not be drawn on AGW since the time periods for which we have good temperature data (roughly 30 years) was too short. Then, all of a sudden, once the recent RSS trend was noticed, a short period is just fine to draw conclusions. Hmmmmmm.

        Anyways, for trends involving large, complex systems like the earth, longer periods are better indicators.
        And the trend for RSS is clearly going up: http://www.woodfortrees.org/plot/rss/from:1980/plot/rss/from:1980/trend/plot/esrl-co2/from:1980/normalise/offset:0.68/plot/esrl-co2/from:1980/normalise/offset:0.68/trend

        Are there pauses? Sure, just like there was from 1986 to 1998. But the long term trend is definitely increasing. It is incredibly simplistic to assume that the temperature trend for a complex system like the earth, where 92% of solar insolation goes into the oceans, and which also has lots of natural factors like El Ninos, PDO, etc, would rise at a nice steady rate with no pauses.

        “Next, your Berkeley link is one big FAIL. It is merely an opinion, obviously rigged for grant trolling. There is no testability, only their assertions. I have repeatedly challenged you to produce verifiable, testable measurements quantifying the percentage of MMGW. But all your link does is assert that they have found something — but there are no MMGW percentages shown, as usual.”

        It’s not an opinion, it’s actual data, that was verified at 2 sites, one in Alaska, the other in Oklahoma. Who appointed you chief scientific authority for the planet? The last time I looked, nobody did. So saying that AGW is falsified if exact MMGW percentages cannot be calculated is untrue.

        Regarding the 97% claim by Cook, I made no mention of that, so I have no clue where you pulled that from. Regarding a list of scientists that comprises at least 1% of OSIM, I gave you a list of 838. I guess you didn’t bother to read it. Regarding Dr, Abrams, I don’t see how you could’ve spent 10 minutes looking for it without success, I found it easily in 30 seconds: http://vivo.med.cornell.edu/vivo/display/cwid-ava2002

        “Now when there is an article about global warming, the comments are about 90% ridicule. The MMGW scam is on life support now, for one central reason: Planet Earth is debunking your belief system.”

        Huge parts of the Western US are burning, plus a 2 month delay in the Indian monsoons, plus unusually severe heatwaves in many other places – yeah, Planet Earth is sure debunking my claims.

    • For one thing, they’re all using the same “peer-reviewed” methods. (I’m more or less quoting the response of a BOM official after people in Australia began making the same points about the Australian temperature record.)

      Do you believe that the divergence between surface and troposphere temperatures is real, perhaps telling us something significant about the world climate (albeit, I believe, contradicting all the basic models of climate processes)? And do you think this is more likely than the possibility that people are using dubious techniques to ‘fix’ the temperature record? If not, then the only alternative is something along the lines you suggest. (This is really a version of Hume’s argument against miracles.)

      Incidentally, some results from psychology would suggest that the idea of “purposefully” changing the data is problematic, since there is no question that people can evade facts or impose biases on them (e.g. vis-a-vis the so-called ego defence mechanisms). And in the little Global Village that constitutes climate science this could occur in a concordant fashion across the globe.

      • Do you believe that the divergence between surface and troposphere temperatures is real, perhaps telling us something significant about the world climate (albeit, I believe, contradicting all the basic models of climate processes)? And do you think this is more likely than the possibility that people are using dubious techniques to ‘fix’ the temperature record?

        Yeah, I haven’t really gone there in this thread, but as Werner pointed out above, it really is a serious question, isn’t it? Especially since the latest round of adjustments to the global temperature record increase the divergence still more, as they are (if I recall correctly) confined to the comparatively recent past in order to “bust” the “pause”. Or to correct an actual error in the way global temperatures have been computed.

        The point you make (and that follows from this last observation as well) is that there is no comfortable solution here. If surface temperatures diverge from lower troposphere temperatures, either the adiabatic lapse rate is changing, which seem very, very unlikely to me, or else one or the other is simple wrong. Note well, the LTT’s are constantly and consistently checked by soundings, so it seems unlikely that a change in the ALR would go unnoticed or unremarked on. I haven’t been able to make much sense of the way error estimates are constructed for UAH/RSS — it appears to be some sort of monte carlo jackknife but I’d probably have to attend a talk or something explaining it to understand it without way more effort than I have time for (bear in mind I have a full time day job and then some, this is a HOBBY of sorts for me, not a profession) but I can make no sense at all for the error estimates for the surface anomalies.

        Here is a remarkable fact. If we plot GISS and HadCRUT4 from 2000 to the present:

        http://www.woodfortrees.org/plot/hadcrut4gl/from:2000/to:2015/plot/gistemp/from:2000/to:2015

        one can clearly see that they differ by around 0.2 C. The problem with this is that the 95% confidence interval published for the HadCRUT4 data is around 0.1 C. At this point, one needs to do some sort of bitch-slap of somebody, somewhere, because if we were to (say) formulate a null hypothesis like: “Both GISS and HadCRUT are accurate representations of the surface temperature anomaly within their mutual error estimates” we would instantly reject it — in fact, after a glance at this graph we would never even formulate it. We would simply conclude that the publishers of the graphs have no clue as to what an error estimate or confidence interval really is, because I can tell you right now that it is larger than 0.2 C in 2015, probably much larger given the substantial overlap (non-independence) of the two computations of the same thing. One can easily observe this a second way by noting how much parts of the anomalies change as new adjustments are added to the series. The adjustments themselves are order of the supposed error.

        Now, I’m sure they can make an argument that their errors are computed using some algorithm, although it is very doubtful under the circumstances that the algorithm is correct, because statisticians are usually pretty conservative and common-sensical about this sort of thing and do things like check their answer compared to the similarly computed answers obtained by another group and going back to the error drawing board when the two differ by more than the computed 95% confidence interval or more than twice the standard error (which is basically not meaningfully computable as an error estimator for this problem in the first place as there is no way the data is iid and with non-independent data with both spatial and temporal autocorrelation standard error estimates will always be artificially too small as they will presume more independent samples than are actually present).

        The point is that it is obvious — and I do mean obvious — that there are issues with the major temperature anomalies quite aside from the adjustments that are made — and not made — to the actual thermometry. The issue of a fair assessment of error is perhaps the most serious one, because in my opinion (which could be wrong, but is not without foundation) the keepers of these indices are not fairly presenting the actual uncertainty in the global anomaly over time. This allows a near infinity of errors great and small to be made regarding just how reliable our knowledge is of, e.g., the total climate sensitivity. It also permits one to cherrypick indices — pick the anomaly that is the most exaggerated (but claims itself to be precise enough that the difference is meaningful!) and ignore the fact that another produces a less exaggerated result and also claims itself to be precise enough that the difference is meaningful. Precision is basically irrelevant here. What matters is accuracy, and it is perfectly obvious that none of the anomalies are particularly accurate, simply because they don’t agree anywhere close to within their nominal precision.

        This problem is serious enough in 2015. It is an absolute joke in 1850. It goes beyond serious. Claims for “confidence” of temperature estimates in 1850 aren’t worth the pixels used to represent them, and a pixel ain’t worth much.

      • If we plot GISS and HadCRUT4 from 2000 to the present:

        They really like to confuse things by having different base periods. Unlike Hadcrut4, the base for GISS is a very cool time so their anomalies are higher for that reason alone. But even so, when plotting the slope line for Hadcrut4 and GISS and by off setting them so they start at the same place, they still differ by 0.07 from 2000 to the present.
        However there is another complication. Namely Hadcrut4 underwent adjustments recently and the latest is now Hadcrut4.4, but WFT only shows Hadcrut4.3 that ended in May.
        See: http://www.woodfortrees.org/plot/gistemp/from:2000/plot/gistemp/from:2000/trend/plot/hadcrut4gl/from:2000/offset:0.1084/plot/hadcrut4gl/from:2000/trend/offset:0.1084

      • If surface temperatures diverge from lower troposphere temperatures, either the adiabatic lapse rate is changing, which seem very, very unlikely to me, or else one or the other is simple wrong.

        BINGO. Full House.

      • One or the other…or BOTH!
        Most likely both, IMO.
        They are so bad, what is the probability that one happens to be correct?
        I for one cannot count that low.

      • “Especially since the latest round of adjustments to the global temperature record increase the divergence still more, as they are (if I recall correctly) confined to the comparatively recent past in order to “bust” the “pause”.”

        The adjustment that really affected the divergence was the change from UAH5.6 to UAH6. Surfaces measure changes are trivial by comparison. UAH went in one adjustment from a trend as high or higher then surface to one much lower.

        So RSS, beloved of Lord M, has been consistent. But if the difference between troposphere and surface does not just reflect the difference between two different places, then which is likely to be wrong? The UAH jump is one pointer. Dr Mears of RSS is another:
        “A similar, but stronger case can be made using surface temperature datasets, which I consider to be more reliable than satellite datasets”

      • The adjustment that really affected the divergence was the change from UAH5.6 to UAH6. Surfaces measure changes are trivial by comparison.

        Well yes and no. Yes because the change was huge for UAH, but GISS and Hadcrut4 have many small changes each year or sooner and they add up to a larger change. Compare the latest Hadcrut4 with Hadcrut3 below.
        http://www.woodfortrees.org/plot/hadcrut3gl/from:1997/plot/hadcrut3gl/from:1997/trend/plot/hadcrut4gl/from:1997/plot/hadcrut4gl/from:1997/trend

        Also keep in mind that WFT only has Hadcrut4.3 and not Hadcrut4.4.

      • OK. The slope goes from 0.20 to 0.76 C/cen. And now plot in the same way the difference between UAH 5.6 and RSS over the same period. This is basically the difference removed in just one adjustment:

        Here it is RSS has slope -0.025 C/Cen, UAH 1.0 C/Cen

      • Werner Brozek says, August 15, 2015 at 8:49 am:

        “On the other hand, one does get a difference of about 0.2 by plotting Hadcrut3 versus GISS from 1997 and getting the slope. (However Hadcrut3 stopped in May 2014.)

        http://www.woodfortrees.org/plot/gistemp/from:1997/plot/gistemp/from:1997/trend/plot/hadcrut3gl/from:1997/offset:0.09552/plot/hadcrut3gl/from:1997/trend/offset:0.09552

        This is how the two compare from 1970 till ‘today’ (aligned at the beginning):

        Once again, note how I’ve down-adjusted HadCRUt3 from Jan’98 on. I explain the reason why here:
        https://wattsupwiththat.com/2015/08/14/problematic-adjustments-and-divergences-now-includes-june-data/#comment-2007217

    • If you have a specific objection, please state it, Sergei.
      Dr. Brown did not make general statements of a personal nature, or use a mishmash of logical fallacies in his analysis.
      However, you did.
      So state your objection to the posted information.

    • Sergei…
      I think you have left out the option that very view control the data, maybe a handful, and the pressure of keeping a job or getting funding the rest are afraid to and have no need to speak up. We all know how vindictive the Administration is as thy pour their wrath on anyone who disagrees or questions anything. Just look at Senator Mendez if you hare not aware of the tactics.

    • A whistleblower released definitive evidence, emails between climate “researchers” and keepers of temperature records in the US and Europe. The whislteblower’s release of emails was colloquially known as “Climategate.”

      The evidence also included the computer code used to create hockey-sticks and other fraudulent travesties.

      You must have missed it.

      Here’s a good overview: https://cei.org/op-eds-and-articles/chris-horner-climate-gate-e-mails-released-whistleblower-not-hacker

      As to the question of why insiders to the climate scam do not speak up and blow the whistle–think of the Mafia, Catholic clergy sex abuses, Penn State football’s winking at the decade-long boy-raping going on its locker rooms, or other secrets of illegal activities conducted by groups which generate cash and prestige for their members.

      The insiders usually only begin to talk when they are sitting in an interview room with the FBI. The feds offer them a choice: tell the truth and get a slap on the wrist, or keep quiet and face decades in prison.

      There is another way–the False Claims Act. It provides incentives to whistleblowers with knowledge of fraudulent claims made to receive federal grants. The vast majority of “climate researchers” receive federal grants. The FCA allows whistleblowers to bring civil suits, on their own, against the fraudsters, and then to share in funds clawed back.

      Until the FBI starts making arrests, the False Claims Act is the only way we’ll bust this scam.

      http://onwardstate.com/2010/01/14/former-cia-agent-investigates-climategate/

      • Sadly, the people who sign the paychecks which fund the justice system are the same people who are paying to get the claims of catastrophic warming.

      • “Sadly, the people who sign the paychecks which fund the justice system are the same people who are paying to get the claims of catastrophic warming.”

        The beauty of the False Claims Act is that it puts much more power in the hands of citizens and skilled trail lawyers. The power comes from our ability to share in the funds clawed back from the scammers.

        So, we are not just at the mercy of the 100% political Attorney General. If we can find a whistleblower (grad student slave in Mann’s department?) who has access to internal communications between the scammers (a la ClimateGate), with smoking guns, then we can begin the process.

        If everyone here worked their connections to spread the word about the False Claims Act and the potential rewards for whistleblowers, we could make a much bigger impact than arguing the facts with each other.

        Details here: http://www.whistleblowersblog.org/

    • sergeiMK:

      1. Educated people are very often incompetent in impressively grotesque manners. Nearly every time they step outside the core competency, in fact. But even moreso as educated people in their fields understand the need of social graces. Either to not state that the Emperor is naked. Or to believe that it is impossible that the Emperor is naked, because all of their colleagues are highly educated. It’s necessary credulity for paying the bills.

      2. It is not an accusation of fraud at all. An R-squared of 0.99 is. Which most folks would call a ‘scientific result.’ Indeed, most science folks would call an R-squared of 0.99 a ‘law.’ You could call it the Second law of GHG, or the First Law of Politically Funded Science, or…

      But to ask why so many would be ‘party’ to it? See the answer to your first point for the second part of the answer to your second. Thing is, if we’d get the science community back to skepticism and away from pal review, we’d have less credulity, better science, and the Emperor would be properly attired in fact rather than social fancy.

    • sergeiMK:

      You unfairly ask rgb

      So you are basically stating that all major providers of temperature series of either
      1 being incompetent
      2 purposefully changing the data to match their belief.

      1. How can so many intelligent educated people be so incompetent. This seems very unlikely. Have you approached the scientists concerned and shown them where they are in error. If not, Why not?

      2. This is a serious accusation of scientific fraud. As such have you approached any of the scientists involved and asked for an explanation?

      Your question is unfair because a group of us repeatedly tried all that years ago with no success. Please read this.

      rgb is doing all he can to publicise the issues so people know about them and, therefore, are enabled to care about them. I for one am grateful to him for that.

      Richard

    • “Can you give reasons why you think 1000s of scientists over the whole globe would all be party to this fraud. I do not see climate scientists living in luxury mansions taking expensive family holidays – perhaps you know differently?. What manages to keep so many scientists in line?”

      First, only the “attribution” scientists would be party to this fraud–and they are only 20% or less of the total number of scientists writing on the topic. The others (Impacts and Remedies) take the formers’ calculations on faith.

      Second, there is a recruitment bias going on. People entering the climatology field tend to be environmentally minded folks, or at least with a sensitivity to nature, who went into the field (once it had become politicized) because it had become politicized. They wanted to provide findings supporting the urgency of the crisis.

      Third, there is an indoctrination bias. Warmism is gospel in grad school and textbooks. Many of the chairs in climatology were, I suspect, endowed by do-good donors (e.g., Heinz) and foundations who wanted to prevent man from ruining his environment–and fighting climate change seemed like a good way to do so.

    • are there families/careers/lives threated to maintain the silence. why is there no Julian Assange or Edward Snowden, willing to the fraud?
      ====================
      1. threated – yes they are threatened. Judith Curry for example went from being the darling of the IPCC to an outcast for daring to speak out as a result if Climate-gate. There are many other examples.

      2. expose – yes, the Climate-gate papers exposed the corruption of climate science. However, both Assange and Snowden have immense legal and personal safety problems as a direct result of their moral stance as whistle-blowers. This is an extremely chilling message to anyone else thinking of blowing the whistle. The message is clear. Blow the whistle and your life as you know it is over.

      • Yes, Dr. Curry has made some amends, for sure. But she had an awful lot of atoning to do after the disgraceful way she spoke to and about Dr. Gray. Even leaving aside her lead on the smug assurances to all who would listen that the world was now in a new normal, back in 2005, and large and ferocious and ever greater numbers of hurricanes were a fact, not a prediction, and were here to stay.
        It can barely be overstated how awful she was to him. Even if he did not turn out to be nearly 100% correct, and she EXACTLY 100% dead wrong.

        Besides for all that, a ore vivid example of real world irony would be difficult to dream up…but it actually happened, as about one minute after these dire predictions we entered was, has been, and still is the quietest period of hurricanes in the Atlantic basin EVAH!
        (And by evah, I mean in all of the recent past and recorded history…just what it always means.)

    • a very good question, one that I have been gnawing on for some time, it is obviously happening so WHY are these 1000’s of scientists remaining quiet or worse supporting it (although the majority are remaining quiet in the hope thqt they never get the spotlight shined on them and have to state their position). Of course the continuation of their funding might have a small effect, plus they might want their career to continue (ask Willie Soon) but how do they sleep at night knowing that they are at least complicit by their silence in this fraud, why hasnt even one scientist come forward? Also why hasnt some opportunist politician stepped up and stated a contrary (visionary) view? or could that be (in the tradition of Yes Minister) “Very Couragious”

      • Also why hasnt some opportunist politician stepped up and stated a contrary (visionary) view?

        Senator Inhofe from Oklahoma wrote the book “The Greatest Hoax: How the Global Warming Conspiracy Threatens Your Future”. I have read it and it is excellent.

        We have to hope the Republicans get in next time.

    • The first graph, if correct, is either a staggering coincidence or staggering evidence of fraud

      I don’t know if the correlation data is actually correct and I would not take “Steven Goddard” at face value without double checking his work.

    • Serge,

      If there is a correlation of adjustments to CO2 as indicated any legitimate scientist would have to question the adjustments. That simply makes no sense. There are 5 or 6 seperate adjustments made to the data. Some of the adjustments overlap with each other in purpose. The adjustment process has been secret until recently. There has been virtually no peer review. I woouldn’t be surprised if the writers of the adjustment algorithms play with the algorithms adjusting the parameters until they get the maximum adjustment to enhance global warming. Now all they need to do is shoot the satellites so they don’t have this “check” that shows their funny manipulations are as fraudulent as the hockey stick graph. It’s extremely unlikely that there would be this divergence between satellites and land measurements and even more obvious something is wrong if the adjustments are greater when CO2 is higher. On top of that the land data is obviously very sparse and cannot be that accurate. There are only 3 stations from 75 to 90 S lattitude. The whole continent of africa is barely covered in sections as are large swaths of russia and canada.

      Further to pile inaccuracy on inaccuracy the ARGO buoys are spaced out over the oceans in about the same denisty as in antarctica. There is no way the land/argo data can compare to satellites. How could the balloon data also be wrong? Any sensible scientist would conclude something is wrong with the adjustments. It’s your guess as much as mine but the fact there is no obvious error doesn’t mean there isn’t error. There is simply no logical reason why this divergence should exist. Something is wrong. Until we figure out why the land record should be discarded and all adjustments removed.

      One reason why UHI is positive adjustment is because they select the base period as 1979 for UHI. So, a huge amount of “UHI” is locked into what they consider “before UHI.” As a result when they look at past temperatures close to cities they see they were going up too fast since they assume there was no UHI then. They therefore need to adjust those temps down to make them “realistic” and similarly after 1979 temperatures in many cities don’t go up as much as outlying areas of the cities so the cities need to be adjusted up to compensate.

      They need to go back to an earlier period before significant UHI happened.

      You also ascribe to scientists in climate an objectivity which is clearly missing. Their is a pressure to follow the “known” facts. Articles are written with boilerplate text which says they believe in global warming like Nazi’s would demand Heil Hitler. I’m not joking. There is an obvious sense of fear if you challenge the status quo. It is apparent in every article you read on the subject. They always state in the article especially if the article diminishes the science behind the “consensus” they have to always add: We believe in catastrophic global warming and this article does not mean that man isn’t destroying the environment, that catastrophic global warming isn’t happening even if the article seems to indicate problems in the theory. We believe. We believe. Don’t fire us. Don’t call us deniers. For these biolerplate addtions they are allowed to print their article.

      I am sure in many cases they add these kinds of statements because they are politically motivated to start with.

    • Using data from WFT. Taking the 12 month average from 1958.2 of CRUTEM3 NH and 12 month average of CO2 levels from 1958.2, gives a linear fit with a slope of 0.0156 K/ppm with R2=0.82. In the graph above for the adjustments to USHCN the slope is 0.0137 K/ppm with a R2=0.99.

      If this was finance we would have a conviction.

  5. Could the unbiased country based readings be eliminated because they are “outliers”? What would that do then?

    • Nik,
      It would cause yet more warming.
      Tony Heller and Paul Homewood have documented instances of this exact thing occurring.

    • Could the unbiased country based readings be eliminated
      =================
      This is exactly what the homogenization algorithm is designed to do. it eliminates the rural temperatures because they don’t match the more numerous urban temperatures. As urbanization increases, more and more rural temperatures become “outliers” and are eliminated via homogenization, until all that is left is urban temperatures.

  6. Because the proposed actions to a perceived climate crisis will be have such huge opportunity costs, every presidential candidate should have a trusted science adviser capable of forming a rational policy in this area.

    I would further propose that a package of supporting documents should be assembled and supplied to each adviser, and on the top of that package I would recommend this post. This is a correlation which absolutely must be investigated before any decisions are codified which will require world-wide confiscation of wealth and the vast environmental impacts required for the meaningful implementation of “renewable” energy sources.

    The concept of CAGW hinges upon observed surface temperature changes that fall within the range of the adjustments as shown in the first chart above. Until this correlation can be explained rationally, the science can hardly be considered settled.

    Fantastic work!

    • “…every presidential candidate should have a trusted science adviser capable of forming a rational policy in this area.”

      That isn’t the way politics works. A ‘rational policy’ is not considered. The policy provided is determined by the ideology of the political party in charge.

      • Hence the wise policy of wanting government to be small.

        and

        Smaller is better. Smaller and smarter is best.

        Why? A government of the people, by the people, and for the people, should track with population size.

        This short-sighted and illogical insistence on smaller government, willy-nilly, has affected genuine science research, for one. Can’t do what Dr. Gray suggested as the proper way for government to conduct science research: fund put both sides of an undetermined but publicly contentious scientific issue and let the scientists iron it out before activists, advocates, and misinformed journalists make the decision for an ignorant public.

        The population size in Lincoln’s time was 1/10 what it is now. The federal government has shrunk so much we have the same size government as 1956. The size of government today should reflect what we, the people, are trying to accomplish. Of course, that sounds almost Pollyanna-ish to say, it’s so corrupted. It’s not size that matters, it’s need.

        Instead, to make up for the shortfall in proper government, we have private military contractors doing what active military could and should do (for better pay), and charging exponential fortunes for it. Look at the mess Snowden told us about, did you see his slide of the global private contractors handling our private US citizen data outside of US jurisdiction?

        Remember the 83 million customers hacked at JP Morgan Chase last year? We were told it was such a sophisticated operation that it could be the Russian government, and therefore required more sanctions? Well, three weeks ago they arrested two Israelis (ISR), one Israeli-American (FL), and another guy (FL) for the job. NSA outsourced major intel work to private Israel firms according to Snowden’s slide. How do we know one of those employees couldn’t compromise our banking system armed with NSA treats?

        I don’t want government small, I want it cleaned up and made effective. The Clinton admin’s failure to regulate mortgage banks (which are not regulated by the federal Bank Charter Act, only by the NY Federal Reserve, another Greenspan-era tweak) caused the subprime crisis. The FBI warned Congress in open testimony in September 2004: FBI warns of mortgage fraud ‘epidemic’.
        Seeks to head off ‘next S&L crisis’
        , and NY Fed Prez Timmy Geithner ignored warning testimony from the Director of the Criminal Division at FBI headquarters in DC, broadcasted and published by CNN. It was his YOB (job). Then Obama put him this ne’er-do-well in charge of the henhouse as Secretary of the Treasury instead of putting him in jail.

        Small is not the issue. Accountability is.

  7. Are there any statistics on the surface temperature reading stations that are urban versus rural? IOW, are the temperature reading stations primarily urban in ratio?

    • Even determine what is “rural” s not easy, as UHI can happen in a small town say growing from 500 people to 3,000, or growing from 3,000 to 10,000. Among many odd things about the homogenization process is the fact that what stations in the data base get used change monthly, with up to fifty percent of the official stations data not being used.

      • If that is the result of the homogenization process, then that is hardly the collection of data in a scientific way.
        In any event, the recording stations should be placed in areas that are not affected by the UHI effect. Surely such a task is not insurmountable.

      • Jim, that no such effort is underway, even though the technology obviously exists to put these recording stations at regularly spaced rural locations, tells us that an objective and unbiased surface record is not desired.
        It is not like climate science is on a tight budget!
        Every jackass study any nitwit can dream up is funded generously.

  8. The climate alarmists are getting really desperate. It is well known that IOP (Inst of Physics) leans to climate alarmism but upto know they have allowed some critical comments on Posts at physicsworld.com but they have removed comments of mine on two different posts and immediately closed comments. The most recent was at http://physicsworld.com/cws/article/news/2015/aug/07/new-sunspot-analysis-shows-rising-global-temperatures-not-linked-to-solar-activity were I made a short comment (originally number 13) agreeing with the first comment by Dr John Duffield. The second comment was in reply to Letitburn (no11) and became comment 14. This latter comment included some facts about the Stefan Boltzmann (S-B) equation straight out of Perry’s Chemical Engineering Handbook. It would appear that IOP can not allow anyone to present facts which do not support their theory.
    Dr Brown you are correct about UHI.. I note it just about everyday with the the outside air thermometer on my Japanese car. Certainly the majority of those calling themselves climate scientists in the alarmism camp are incompetent and have little or no understanding of heat&mass transfer, However, there are also some of those incompetents with political agenda (eg some at GISS) who are falsify data.

    • I have made the same observation with regard to central Edinburgh and the immediate hinterland to the east (south adds in a fairly quick 150 metre ascent to confuse matters). In mid-evening in winter the difference can be anything up 5²C.

      • On cold winter nights the difference is even larger.
        Ask any farmer or learned meteorologist.
        These are now referred to as “cold pockets” or “agricultural areas”. They are mostly places with few structures or paving, and farmers put their thermometers where they will be warned of how cold it is near the crop, not on the side of their barn or driveway to their house.
        When I had a plant nursery, and used to have to stay up all night every night in winter or risk losing everything, I was also in college studying several subjects relevant to climate and weather, including climatology and meteorology. I am an amateur astronomer and that keeps me outside at night as well.
        I was also very interested in what I saw regarding microclimates around the growing areas.
        I undertook for several years straight to place thermometers by the dozen all over the place at our farm.
        Including a few expensive ones, and a few high/low ones. (As an aside, I found even cheap thermometers costing a dollar or two were usually very close to the most expensive ones.
        But the main thing I noticed was the huge variation in temps around any structure at all, or any paved surface, or even under and near large trees (Florida live oaks retain their leaves year round). I mean large. I was not in the habit of writing down the readings, but looking at dozens of thermometers, sometimes every fifteen minutes, night after night for years on end…I can tell you I got a real sense of some things which are not commonly known, or widely discussed.

        Aside from the microclimate aspects of all of this nearly obsessive temp watching, was a sense of how wide was the variation in how fast temps could fall at sunset, depending on humidity levels (absolute humidity levels, measured by the dew point), and of how a veil of cirrus streaking overhead could stop and reverse a falling temp trend in minutes, by up to five degrees almost instantly.

        /end pointless ramble

      • Not pointless “at all. GISS and USHCN commonly do not use up to 50 percent of their stations, and they claim that adjusting stations within 1200 K of “chosen” stations is perfectly legitimate.

        A simple drive down the Calif central valley with constant change (often less then ten minutes later) in T of up to 2 degrees or more up and down as one drives, illustrates the absurdity of this practice. Your post takes these changes to an area far smaller.

      • Menicholas says:

        “As an aside, I found even cheap thermometers costing a dollar or two were usually very close to the most expensive ones.”

        (This comment is an aside, too. Thermometer calibration interests me. Part of my Metrology carreer involved calibrating thermometers of all types; mercury, electronic – RTD, platinum resistance, J/K/R thermocouple, etc., along with many other weather related instruments.)

        You need to spend a minimum of about $30 to get a good scientific stick thermometer with a calibrated accuracy of ±0.5ºF. (that is very good accuracy, btw). Drugstore thermometers might be that accurate, but you’re taking a chance.

        Several years ago I bought a couple dozen calibrated thermometers for an experiment. They came connected in a plastic strip, side by side. Before I separated them I moved them to different locations, both inside and outside the house. Every one of them read exactly the same, from about 50ºF – 80ºF, so I think the accuracy and linearity were correct.

        If you’re going to buy a drugstore stick, put all of them together on the shelf and leave them a while. Then pick the one(s) in the center of the group’s temperature range. You will always find some that read higher or lower than the average; reject those outliers. Of course that’s not calibrating, but what you really want is a benchmark to observe the temperature trend. Temperatures around the outside of a house can vary by several degrees, within even ten feet. So place the thermometer permanently, in a shaded area away from heat sources, etc.

        The important metric is the trend. That’s more important than the temperature at any one point in time. A cheap drugstore thermometer will show the trend if you record the temp at the same time every day.

        For anyone who thinks calibrating a stick thermometer is simple and easy, see here:

        http://pugshoes.blogspot.com/2010/10/metrology.html

        Anthony also wrote an article on this a few years ago:

        https://wattsupwiththat.com/2011/01/22/the-metrology-of-thermometers

      • While I do not recall specifically doing so, I am sure I would have riffled through the whole display of thermometers on the shelf at store I bought them at, and chosen ones that were in agreement with each other. The cheap ones I used were alcohol in glass. Bimetal were known (by me anyway) to be balky, especially outside, and did not last due to corrosion. Electronic ones were not widely available or inexpensive back then.
        That was back in the 1980’s when I first bought them, and I remember paying somewhere near $40 for a mercury high low thermometer. It was a type with two separate columns. I would place a cheap one next to a good one to compare values. Every once in a while I recall gathering them all up and putting them in a row, and at least once placing them in ice water to check them. I was mostly concerned with how they did at low temps, near freezing and below.
        I also found that if they got out of whack, it was usually due to the glass moving in the case with the graduations on it. Cheap ones do not have the numbers marked in the glass…usually just one or two marks that are then lined up on the case. It would be easy for an observant person to then adjust them.
        I seem to recall at least one lab exercise where each student had to calibrate a mercury in glass thermometer using ice water and boiling water ( I am supposing they do something similar with commercial or home use thermometers.) and then mark the graduations, then use that thermometer to perform some careful analysis. I think it may have been a analytical chemistry lab. Or maybe P.Chem.
        But I do not really remember. I took a lot of science classes. Just about all I studied.
        I got mostly all A’s in my chemistry classes. Grade in Analytical Chemistry (In some school known as Qualitative and Quantitative Analysis) was based almost solely in accuracy of results. They give you an ore sample (or whatever…each week was something new and difficult, as I recall), you tell them what it’s concentration of metal is, etc.
        You had to know exactly what you were doing, AND be very careful, AND have steady hands AND a good eye, or else you could not do well in chemistry labs, most especially A.C.

      • “Not pointless “at all. ”

        Thank you David.
        I suppose I was referring to my tendency to tell a longer version of a story than is strictly required to make a point.

  9. I’m sure the satellite record will be next. “Who controls the past controls the future. Who controls the present controls the past.” George Orwell, 1984

    • I think they will wait for the satelites to fail and then not relaunch new ones. With them gone they will be able to adjust to their monies content

    • Let us hope that somebody in position sees this risk, checks that there are no such plans and has the scientific integrity to stop any such attempts or misconducts. Karl Popper; the master mind behind the modern scientific method, Popper´s empirical method; has warned us about such risks:

      “it is still impossible, for various reasons, that any theoretical system should ever be conclusively falsified. For it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition. It is even possible without logical inconsistency to adopt the position of simply refusing to acknowledge any falsifying experience whatsoever. Admittedly, scientists do not usually proceed in this way, but logically such procedure is possible –

      “… the empirical method shall be characterized as a method that excludes precisely those ways of evading falsification .. ”

      “According to my proposal, what characterizes the empirical method is its manner of exposing to falsification, in every conceivable way, the system to be tested. Its aim is not to save the lives of untenable systems but … exposing them all to the fiercest struggle for survival.”

      (Karl Popper – The Logic of Scientific Discovery)

  10. Nothing but “adjustments” across the board!

    I have a real problem with these “adjustments” and continue to try to get a better view of what the actual temperature record would look like if you were able to remove them. It is more than apparent that the adjustments being applied are very linear in nature so it should be quite easy to remove them if you can get a starting date and the proper slopes.

    I just took the information that Tony Heller provided, the plots NOAA/GISS publish of these adjustments and it appears that they began just prior to 1940, probably to commemorate Guy Callendar’s “ground-breaking” paper (http://www.theguardian.com/environment/blog/2013/apr/22/guy-callendar-climate-fossil-fuels

    ) blaming OMG-it-is-CO2! in April 1938 right at the previous temperature peak in the dust bowl days, so, I will accept that as being very close to the correct inflection date. Adjustments prior to 1938 seem to be a magnitude smaller. The slope is a SWAG estimate from the best information I have been able to gather. If you have a better record of the adjustments, download HadCRUT4 or other dataset and reverse those out, would love to see.

    Here is my best stab at that view:

    • I will not rule out that the slopes I used in that plot above may even be too conservative, ask yourself, is today as warm as recorded in the late 30’s? I say no way, so that plot is only partially corrected. Forgot to include that in my comment above.

      • Tony has written posts with charts showing the number of days at all stations above 90 degrees, or 100 degrees, etc
        They all show that back then, hot days were far more common.
        It is impossible to believe that hot days have become less common, by a large amount, and yet it is overall hotter now.
        Ludicrous, in fact.

    • Sadly, that isn’t a completely crazy graph, although I’d argue that we can’t really correct the correction by selectively removing corrections. One source of bias is to ignore corrections that should be there but go “the wrong way”, like UHI, or to find a way of making UHI not produce a warming bias but rather a cooling one (present relative to past). UHI correction alone is likely order of 0.1 to 0.2 C from 1850 to the present — in my opinion — and is very difficult to estimate or compute precisely. That is, it is readily apparent — I can see it literally driving my car around town and watching the built in thermometer go up and down as I drive into a shopping center parking lot or drive down a suburban road or drive further down a rural road — easily 1 to 2.5 C over a distance of 4 or 5 miles. You can see it beyond any question represented in the network of personal weather stations displayed on e.g. Weather Underground’s weather maps — one could probably take this data per city and transform it into a contour “correction map” surrounding urban stations, although since the temperature can shift 1+ C over a few hundred meters, this is going to be really difficult to transform into something accurate and meaningful.

      The problem is only half with the data and how an anomaly is built in the first place. A large problem is in the way error is absurdly underestimated. HadCRUT4, in particular, has unbelievably absurdly small total error estimates for the 19th century, unbelievably small error estimates for the first half of the 20th century, and merely somewhat too small ones for the last 50 or 60 years. That they are too small is evident from how much they just shifted due to a previously unrealized “correction” to sea surface temperatures. Whether or not the correction is justified, the fact that it was capable of making as large a change as it did simply means that the error estimates were and remain far too small for even the contemporary data give the enormous uncertainties in the methodology and apparatus.

      However, if I were to fit the graph you generate to obtain a good-faith estimate of total climate sensitivity, it would end up being only around half of what I get now fitting HadCRUT4 without the newest correction. But I still wouldn’t have any faith in the result, because the acknowledged error bars on the 1800s points is around 0.2 to 0.3 C, and it should really be 2 to 3 times this large. We really don’t have a good, defensible idea of what the global average temperature was in 1850 compared to today. Seriously. Antarctica was completely unmeasured. The Arctic was impossible to visit. Siberia was the wild west. The Wild west was the wild west. South America was unvisited jungle. Stanley had not yet found Livingstone in Africa. China was all but closed. Japan was closed. Australia was barely explored. Huge tracts of ocean were unvisited by humans except for pirates and whalers. Global trade, mostly, wasn’t, and what there was proceeded along narrow “trade routes” across the ocean and along coasts.

      Yet we know the global temperature anomaly in 1850 to within 0.3 C!

      Or, maybe not. Maybe we are just kinda making that up.

      rgb

      • Yes Robert, you must take that with a grain of salt. i wish there was available better datasets of the very adjustments that have been made, some HadCRUTs, some NCDCs, and all categorized by UHI adjustments, homogenization adjustments, site adjustments, TOb adjustments, etc, and part of what I assumed above may not really apply or there may even be more, but who really knows? To me that is the real sad point, no one person can decipher it all the way back to the original.

        But it is so curious isn’t it just how tiny a per-month accumulative adjustment completely changes your entire mental view from impeding-catastrophe to nothing-to-worry-about-at-all.

      • Also, you besides being a physicist are very versed in computing as I picked up visiting your site quite a while ago and if this upward bias on the adjustments would be in error this just brings back a very, very dumb mistake I made some forty years ago and have never forgotten it to never repeat again. In code, something as innocent as round(T*1e4+0.5)/1e4 or such would be so fatal, in that case it forgot what such code does to negatives, like accumulative monthly ±anomalies. If so, there would appear a very tiny bias. Sorry but I look at such instances and that is always foremost in my mind, why so consistently upward nearly linear?. Surely not.? There is one piece of code, proprietary and unavailable and private, that all temperature records passing through NCDC must go through, and such missing steps, blank holes, has always made me suspicious ever since I became aware of that while reading about adjustment steps. Ancient code back when you had to do such things as rounding yourself in code.

      • But it is so curious isn’t it just how tiny a per-month accumulative adjustment completely changes your entire mental view from impeding-catastrophe to nothing-to-worry-about-at-all.

        Well, bear in mind that (depending on which “adjusted” dataset you use) e.g. HadCRUT4 shows only 0.8 C (or maybe by now it is 0.9 C after the latest adjustments) temperature increase over 165 years. I haven’t posted this graph yet on this thread, but it is worth doing at least once:

        So yeah, subtracting a linear trend of 0.8/165 = 0.005 C/year is enough to flatten the entire warming to nothing. Alternatively, the total warming observed in HadCRUT4 corresponds to a linear trend of 0.005 C/year, or half a degree per century. It would be a great time to digress on just how large secular temperature change rates are or have been in pre-thermometric past (not that we know or can resolve changes like this even with thermometry — the acknowledged error bars in HadCRUT4 make this something like 0.005 \pm 0.003 C/year, and the acknowledged errors are not IMO believable in 1850 and are not consistent across the different anomaly indices in 2015 and hence aren’t believable there as well). Prior to 1850 and on into the proxy-inferred past, our accurate knowledge evaporates into “nearly useless for answering this question” quite rapidly.

        We have a more or less fixed body of thermometric data to work with to infer the global temperature over the past 165 to 200+ years. We cannot carry this back any farther than 1724 as there were no thermometers at all before this date, and practically speaking we are going to have a hard time building a global anomaly or temperature with any useful accuracy (not precision, ACCURACY) before 1900 if not later. To put it bluntly, the confidence intervals indicated on the HadCRUT4 graph are not credible as any sort of measure of accuracy and are highly dubious as measures of some sort of internal precision on data that in 1850 had to be kriged over something like half (or more) of the terra or oceana incognita globe with enormously sparse samples.

        Anyway, as the graph above clearly shows, I am not in any way “denying” the high probability that human produced CO2 is likely causing some warming. I can give you a best fit number — 1.8 C per doubling of CO2 according to the graph above, with substantial error bars. There are numerous reasons to have large error bars. Obviously one can draw a number of curves like the blue line that aren’t too expensive in \chi^2 compared to the already evident apparently natural 0.1 C oscillation plus the substantial 0.2 to 0.3 C interannual noise. The CMIP5 MME mean is supposed to be an “acceptable” fit (personally, I think it sucks, but that is just me):

        So presumably a smooth log CO2 curve with a much lower sensitivity with no worse a \chi^2 than that belonging to the MME mean would also be acceptable as an estimate, say one with less than 1 C per doubling of CO2. I simply present the best fit to HadCRUT4 as it is.

        But this fit is pointless if I cannot trust the data I’m fitting! And right now, I’m having a very hard time trusting it. Its error estimates are, as I showed above, some sort of meaningless internal precision, not accuracy, because HadCRUT4 differs from GISS LOTI by over twice their error bar over extended ranges outside of the reference interval used to define “anomaly”. Steve Goddard’s plot at the top — or the many other plots of this sort that he presents of the effect of successive adjustments to various climate records on his website — do not add to this confidence. Neither does Nick’s version of the same data — which does have a more believable range but which also still looks like it has very much the curvature of cCO2 over time. Goddard does show — I think — how he gets the data he plots against CO2 on his website as the difference between USHCN 2.5 and a much earlier HCN version. This might explain the discrepancy, as Nick is likely just tallying changes in the USHCN series. In any event, the curve plotting the difference is in good agreement as to the range and has almost exactly the same shape as the fit I showed above (or below, can’t remember) to cCO2 over time, so it is very likely that this is the result that is being plotted above. It would without any doubt be good for Goddard to provide details on how he computes it, though.

        As to whether or not it is reasonable to use the subtraction he uses — I don’t see why not. For one thing, even if it does exaggerate the range, the range isn’t the point. The point is the linear correlation on a scatter plot. I suspect Nick would obtain a very similar linear correlation if he were to build a scatter plot of his own data against measured and/or extrapolated CO2. It might not be as perfect as Goddard’s, but I’ll bet it produces an R^2 that is still far, far too high for comfort. There are secondary pieces of information that suggest corruption of the HCN averages. Goddard isn’t the only person to observe these — I’ve discovered a number of them myself mousing around. But also on his site is a lovely set of graphs showing things like the distribution of the years where state high and low temperature records were set. These are results that do not necessarily depend on time of day adjustments, and really should not be particularly sensitive to thermometry — they provide the envelope of the temperature outliers over the field of measurements. The 1930’s are the hands-down winners in the state high (and a near winner in low) temperature record setting process. The present is utterly unremarkable, although the 1990’s were hotter than “normal”.

        Note well that if anything, state high temperature records should be biased towards the present! We have more measuring sites (any of which could register a local record). We have more UHI warming with bigger cities and plenty of terribly sited weather stations to contribute a peak. And even so the 1930’s dominate. This makes it — in my opinion implausible that the current decade is, in fact, the warmest on record in the United States.

        If the United States — surely one of the best measured countries in the world — is in error for whatever reason by enough to promote the post-2000 interval up past the 1930s (but somehow in a way that has set almost no new state high temperature records in the last 15 years) then it seems pretty reasonable that the global temperature anomaly is corrupted by at least this amount as well, probably because of the use of the same incorrect adjustments and/or neglect of adjustments that would ameliorate the problem.

        So, Nick, is there a glib explanation for why the vast majority of state high temperature records were set before 1970, with at least 1/4 of them in the 1930s alone, with only a tiny handful in the “warmest ever” 2000-2015 interval? Or if you don’t like per state, look at the surface area of the states with high temperature records pre-1970. Again, there may be a good explanation, but this is very much a problem, a substantial inconsistency that adds to the reasons to doubt the accuracy of the adjustments. So it isn’t just the — is it fair to say “surprising”? — correlation between adjustments computed any way you like as long as the methodology is well defined and not unreasonable — and atmospheric CO2? Isn’t it odd that many state records — NC’s, for example — show no warming trend at all over the last century? Are we special? Or is it just the case that our records haven’t been adjusted enough yet?

        I will repeat it yet again. Adjusting data before using it to prove a point is always dangerous, sometimes necessary, and if the point is not proven before the adjustment and is proven after the adjustment (and you were trying to prove the point — you have a grant, tenure, a career at risk if you don’t) something that historically, empirically has been shown time and again to be a Really Bad Idea. At the very least, your error estimates need to be extremely generous post adjustment because you need to include the possibility that your adjustment was biased by your desire — your need — to prove your point.

        Double blind, placebo controlled. Having the data adjusted and analyzed by a third party who doesn’t even know what the data is supposed to represent. Showing what the raw (unadjusted) data shows, as a sanity check on what you are “proving” with the adjusted data. And yes, plotting the adjustments against the principle variable you are trying to correlate with a result to see if they are just plain too perfectly in agreement with that point to (probably) be real.

        At the very least there is a substantial burden of proof not just to show that each adjustment made could somehow be justified, but that no adjustments that would have confounded the point being demonstrated were omitted (and that’s a tough one to show, with UHI sitting there all naked and unaccounted for or unbelievably accounted for, and likely other adjustments to consider as well), and how it just so happens that when one adds up all of the corrections, they are in a perfect linear relationship with that primary variable. Correlation may not be causality, but with a correlation this good, you’d better be prepared to prove that it isn’t even inadvertently causal, because the point you want/need to make depends as much or more on the adjustment as it does anything in the unadjusted data!

        That’s the killer, right? If half the TCS estimate goes away with unadjusted data, I’d argue that the lower bound of TCS is even smaller than the unadjusted estimate. You just don’t get to adjust and increase precision at the same time, at least not according to information theory or empirical practice. And “scientists” make this mistake all the time, which is why we are just now learning that eating fat and dietary cholesterol doesn’t increase your blood cholesterol, so bacon and ice cream and eggs — in moderation, as there is still a connection to total calories and obesity — is no longer a sin. That’s what happens to an entire branch of science, for as long as decades, once somebody sets out to prove a point and gets to select the data to use to do so.

        rgb

      • UHI correction alone is likely order of 0.1 to 0.2 C from 1850 to the present — in my opinion — and is very difficult to estimate or compute precisely.

        Following the daily weather forecasts as I do I know that Mets regularly state a difference in temp between countryside and town of upto 10°C

      • “Goddard does show — I think — how he gets the data he plots against CO2 on his website as the difference between USHCN 2.5 and a much earlier HCN version.”

        No, he doesn’t. You really should find out what he does. USHCN has a set of 1218 stations. In their published measure, they average all of those, estimating missing data using historic and neighbor data.

        In any recent month, 800-900 report (some delayed), and 300-400 are missing. Goddard averages (with different weighting etc) the 8-900 that do report, and subtracts that average from the NOAA’s different average of 1218. The entire discrepancy is attributed to adjustment.

        But it isn’t. The main thing is the difference in stations. We’re talking of averaging absolute values. If the 8-900 were on average cooler or warmer places than the 1218, that difference goes into the “adjustment”. And they easily can be. Not only does the US have big climate differences N-S etc, but even big seasonal differences go into an annual average.

        In this post, I did a simple demonstration. You can set up the averaging to show the alleged adjustment difference. Part is the actual difference between adjusted and unadjusted for stations that actually report. And some, SG’s excess, is the difference between adjusted data for stations that do and don’t report. If you recalculate that replacing actual monthly data by the unadjusted longterm average for that station, you get a very similar result. It isn’t due to adjustment, or even weather. It’s due to the changing subset of stations and their differences in average climate.

      • Fact is, Hansen himself said in the late 1990s that there was nothing unusual going on with temp trends.
        But then it became more important to make everything point to CO2 for all of history. Remember, it was a little while after the ice core graphs made it appear that CO2 caused temps to rise, and this was shown to be the reverse of what occurred. So around that time the alterations to the record really got cranking. What is breathtaking is how far they have had the gall to carry it.
        All the way to what is reported here, so blindingly obvious it should be enough to lead to congressional investigations.

  11. Well, gee…

    From 2000 to 2008 there was massive data corruption that wasn’t well tracked.

    However since 2008 Climate4you has been tracking adjustments:

    We know the CO2 effect (from the 22 PPM = 0.2 W/m2 study) was about 1.05 W from 1900 to today or about 0.28°C..

    We know that CGAGW was about 0.23°C or about 0.85 W/m2.

    All non-GHG anthropomorphic effects are about 1 W/m2 (if you make the assumption that the 3% urban land surface is asphalt not grass you get 1.65 W/m2).

    There is easily about 1 W/m2 of solar intensity increase on average in the 20th century.

    So the 20th century warmed about 1°C as reported. about 0.75°C as measured, and about 0.5°C in reality if measured in the pristine areas.

    Another 1/4°C of CO2 warming in the 21st century isn’t going to make a lot of difference. More people will make the planet a little warmer regardless of how much CO2 they produce. There doesn’t seem to be any way to achieve dangerous temperatures from GHG alone. The 9 year or less methane lifetime makes the methane release scares a SYFY channel fantasy.

    And further while it is easy to demonstrate over $1 Trillion per year in CO2 benefits from more food, fish, and forest (55% increase since 1900), the documented evidence of damage from more CO2 or warming is insignificant – cold is still killing more people than warming.

    • PA August 14, 2015 at 7:42 am says;

      We know the CO2 effect (from the 22 PPM = 0.2 W/m2 study) was about 1.05 W from 1900 to today or about 0.28°C..

      We know that CGAGW was about 0.23°C or about 0.85 W/m2.

      And how do we know this?

      • Umm, I going to assume you don’t visit climate sites much because everyone who is current on the climate picture would be aware of the study.

        http://www.nature.com/nature/journal/v519/n7543/full/nature14240.html

        “Here we present observationally based evidence of clear-sky CO2 surface radiative forcing that is directly attributable to the increase, between 2000 and 2010, of 22 parts per million atmospheric CO2. The time series of this forcing at the two locations—the Southern Great Plains and the North Slope of Alaska—are derived from Atmospheric Emitted Radiance Interferometer spectra3 together with ancillary measurements and thoroughly corroborated radiative transfer calculations4. The time series both show statistically significant trends of 0.2 W m−2 per decade (with respective uncertainties of ±0.06 W m−2 per decade and ±0.07 W m−2 per decade)”


        The forcing is 0.2 W/m2 +/- 0.06 W/m2 for 22 PPM. It is what it is. For global warmers to claim more forcing they would have to actually measure it instead of model it. The past performance of climate models indicates that warmers really don’t know what they are doing. Any claims by global warmers that aren’t backed by empirical measurement should be rejected out of hand.

        If global warming climate scientists continue to insist that models trump empirical measurement we should have a wave of RIFfing and debarring in the climate science field and have more sensible scientists take their place.

        IPCC CO2 only forcing equation is Fco2 = 5.35 * ln (C/C0) = 0.31°C
        TSR is basically Ftsr = 2 * 5.35 * ln (C/C0) = 0.62°C

        Since this was an 11 year study the TSR should be applicable. So the IPCC TSR (and by implication the IPCC ECS) is three times too high.

    • Seeing such automatic adjustments, and observing that they are continuing month after month, year after year with multiple stations being cooled in the past .01 degrees at a time with no announcements as to why, one wonders if the computer code is forever active, further homogenizing the already homogenized past, each change necessitating in the code a requirement for additional changes, always in the same general direction.?????.

      • Well, yeah.

        If you take the 0.23°C and math it out GISS is adjusting temperatures around 4°C per century per century.
        There are 85 years between 1915 and 2000, they have been adjusting temperatures for 7 years (that climate4you has been tracking).

        Rate of change = 0.23 * (100/7) * (100/85)

        So by 2100 there will be about a 7.50°C difference between 1900 and 2100 based on adjustments alone.

        Warmers can dance around this all this want and justify it until the cows come home. It is dishonest and deceptive and if we continue to tolerate it things will get worse. Warmers should be given until the end of 2015 to get their adjustments in. Any adjustments to increase the trend after 2015 to the pre 2010 temperature record should result in RIFfing or debarring the individuals involved.

        If we end this practice now, we can stop over 1500% of the 2100 “global warming”.

    • Well…

      This is getting so old it has lost the humor it used to have. When NOAA and other groups declare ice covered water is warmer than open water in previous years there is a serious problem.

      The solution is to require that government presentation of data meet engineering standards. NOAA or the universities would have to conform to an ASME standard or submit a request for one. Publishing non-conforming data should be prohibited by law (IE result in termination or debarring).

      Publishing this absurd data and charts that misrepresent reality has gone on long enough.

  12. The correlation plot is indeed impressive, but “Atmospheric CO2” is really just a proxy for time. We know that over time Atmospheric CO2 has increased to the (shudder) 400 ppm range. What the plot really shows is increasing positive temperature corrections over time, thus increasing desperation to show global warming … whatever that is.

    Remember, there is no need of IPCC if there is no CC. How many panelists have spent the majority of their careers looking for supporting evidence of catastrophic, global, anthropogenic climate change?

    • The correlation plot is indeed impressive, but “Atmospheric CO2” is really just a proxy for time.

      No, it’s not. That’s what is so damning. Atmospheric CO2 follows a very nonlinear function of time. Here is a very simple/smooth fit to atmospheric CO2 over time, showing where it interpolates Mauna Loa data in the recent past and showing how it compares to ice core data (which I mistrust for a variety of reasons, but which are used to provide a decent estimate of a starting concentration:

      This curve is nothing at all like a linear function of time. What Goddard showed — presuming that he fit the corrections to time, inverted it, and plotted the corrections against CO2 at the time using a curve like this one, or the actual data (I do not know for sure what his methodology was and am taking it on good faith that he did the right thing to match the temperature correction to the CO2 concentration at the time being corrected) — is that the corrections themselves make a curve almost identical to this, identical within a bit of noise, when plotted against time.

      So what are the odds that required corrections to good-faith records of past temperatures, kriged and infilled as necessary to cover the globe with an increasingly sparse record as one moves back in time, will end up falling within a single scale factor on precisely the same nonlinear function of time as the carbon dioxide concentration in the atmosphere? It not only isn’t likely, it isn’t even right. If it were deliberate, they would have fit the corrections to \Delta T = \chi*log(cCO2) - \Delta T_0 — that is, they would have made them fit a log function of the concentration. Humans can’t do log functions in their heads, though, but we’re gangbusters in “selecting” things that might produce a linear monotonic fit. We can do this without even trying. We probably did.

      It would be very interesting to apply Goddard’s methodology to the other two major indices — to the total corrections, per year, applied by HadCRUT4 and GISSTEMP to the underlying data. I’m guessing all three have applied very similar corrections, and that they all three will “magically” turn out to closely match the correction to the CO2 concentration at the time, augmenting the (probably real) log linear warming that was occuring with a linear function of CO2 concentration.

      Even if one does consider the changes as monotonic functions of time, one has precisely the same problem, only it is less obvious. What are the prior odds that any given set of measurements made over a span of time using fairly consistent instrumentation would need to be corrected in a way that is a) a nearly perfectly monotonic function of time; b) monotonic in precisely the opposite direction that one would expect due to the most obvious source of correction, the correction due to the increase of the world’s population by a factor of 15 or so and its GDP and average per capita energy consumption by a factor of 1500 or so? I’d say fairly low, actually.

      But I’d be happy to be proven wrong, not by “justifying” the corrections made but by justifying the omission of the corrections not made (such as the UHI correction) and explaining how it worked out that they all lined up on CO2 concentration by accident!

      It’s possible, of course. Just unlikely!

      rgb

      • “I’m guessing all three have applied very similar corrections, and that they all three will “magically” turn out to closely match the correction to the CO2 concentration at the time”
        This makes no sense even in terms of the conspiracy theory being promoted. Suppose people really were conspiring to bring temperatures into line with CO2. There is no arithmetic reason to suppose that the adjustments would be proportional to CO2. In fact, if they were, that would imply that the unadjusted were also proportional to CO2, which would render the “faking” unnecessary.

        I run a program, TempLS, which works from posted monthly data, and can use either adjusted or unadjusted GHCN. It makes very little difference.

      • “In fact, if they were, that would imply that the unadjusted were also proportional to CO2”

        That makes no sense and is not at all true.

      • Suppose people really were conspiring to bring temperatures into line with CO2. There is no arithmetic reason to suppose that the adjustments would be proportional to CO2. In fact, if they were, that would imply that the unadjusted were also proportional to CO2, which would render the “faking” unnecessary.

        Sigh. This is the problem with using anomalies. You forget that you are really considering temperatures in the ballpark of 288 K. And then, we are considering the deltas in the anomalies. On a scale of 288 K, the temperatures themselves are almost not changing at all — their relative growth is around 1/3% over 165 years, including all adjustments. Now why, exactly, should the adjustments not only be proportional to this 1/3% change but of the same order as (a significant fraction of) the 1/3% change and not be proportional to the 288 K actual temperature being adjusted and noisy, uncorrelated with CO2 at all?

        That’s the thing — thermometers don’t read “anomalies”. Anomalies are inferred, by means of a complex procedure wish loads of room for error, because we can’t compute the global average temperature itself to within an accuracy of one whole degree K! and we know it. It is asserted (de facto) in HadCRUT4 that the error is reduced to 0.1 C by the 2000’s, even though GISS LOTI differs from HadCRUT4 by around 0.2C over most of that interval. So the accuracy of the anomaly is no better than 0.2 C in the 21st century, and more likely is order of 0.3 C or (given the substantial overlap in data used and methodology) larger still. The inference of an anomaly — especially in the more remote past — requires the assumption of a certain kind of stationarity in the climate. But of course, the object of the exercise is to show that the climate is not stationary due to CO2. Which means that past anomaly computations cannot even be consistent because we have literally no way of going back and measuring ENSO events and ocean temperatures in the 19th century.

        But anyway, yeah, I thought of the possibility that you might expect the corrections to co-vary with the temperature. Then I remembered that the corrections should co-vary with the temperature at scale, not at the entirely artificial scale of the anomaly. In fact, it is precisely the fact that they should not covary at the scale of the anomaly, as a substantial fraction of the total anomaly, that is being pointed out.

        Let’s put this in perspective, shall we?

        You are measuring the height of a tree growing outside of my house using an ordinary tape measure. Every day you get one of my sons to hold the tape at the bottom of the rootbase and you try to guestimate the height of the tree based on the highest position of the highest leaf. My sons are indifferent help in this sort of thing, so sometimes they put the end of the tape in one place, sometimes another. After a few weeks of measuring, you change tape measures and suddenly the tree seems a bit higher, so you compare the two and find that one tape measure reads a centimeter more than the other.

        Now, what are the odds that, when you try to adjust for the change in tape measure, when you try to compute a correction “per son” based on observed variations in the day to day measurements and tiny patterns — millimeter scale patterns — you think you detect in the measurement based on how much wind there was at the time flipping the leaf around and so on — that of the total two centimeter growth observed in the tree at the end of the day, one centimeter of that growth is due to the variations described and proceeds at exactly the same rate as the actual growth of the tree from 20.00 meters to 20.02 meters? The errors in holding the tape are distributed relative to 20 meters, not relative to the 1-2 centimeters of eventual growth. Even if a different son held the tape, differently, for each of three weeks of measurement (with the tape measure used changed as well at the end of week 2) it would be a hellacious coincidence to end up with a smooth correction that perfectly matched the growth anomaly of the tree.

        That’s why the safest thing to do in most of these cases is not to measure, or infer, anomalies, and to minimally correct for even things like changing sons or changing tape measures. The former conceals the fact that the base of your errors is the height of the tree, where the day to day “anomaly” is mostly noise at this scale. The problem with the latter is that the strength of statistics done right is that in most cases, measurement errors balance out, and that it is very difficult to be able to conclusively show that they don’t and correct for one error without risking failing to correct for a compensating error. Better just to accept fact that you can barely resolve the growth of the tree relative to your ability to accurately measure its height, let alone infer it growth rate from such a short series of measurements of bouncy leaves at the top relative to a starting point you cannot see (you can’t see where my sons held the tape from on top of the ladder, so you have really no idea if they were consistently resting it on a root the first week, but not the last, etc.

        rgb

      • rgbatduke, this paper seems related to your three detailed comments. Within you mentioned specifically the US temperature record accuracy and I thought you just might gain a little from this paper if you have not already come across it:

        http://www.int-res.com/articles/cr/17/c017p045.pdf

        Particularly Figure 1, pretty close to my plot upthread, eh? Oh, the way it was (and thanks for your detailed pov). Also btw, upon thinking back I do believe it is Karl that hold the patent on that code-that-all-t’s-must-pass-through at NCDC creating GHCN that all datasets call their base due to one of his prior papers back in the 90’s. Could be mistaken but think that is at least close.

      • the strength of statistics done right is that in most cases, measurement errors balance out
        ===============
        we find that to be true in data warehousing. the errors balance out in the aggregate because they are randomly distributed. it is only when you try and drill down to a specific item that the errors are revealed.

        however, as soon as you try and correct a specific class of error the error distribution is not longer random – because you haven’t randomly corrected the errors – and the errors no longer balance out.

        thus while corrected data is likely more accurate when you are looking at specific temperature, it will tend to be less accurate when you are looking at it in aggregate. which is a surprising, counter-intuitive result.

      • rgbatduke:

        Your ‘three sons and two tape measures analogy’ is brilliant!
        Thankyou! I intend to use it with, of course, proper attribution.

        Richard

      • “That’s the thing — thermometers don’t read “anomalies”.”

        Actually they do. Fahrenheit read anomalies relative to a mixture of ice/alcohol; Celsius to the freezing point of water. Neither knew anything about absolute zero. That didn’t matter to them.

        Anomalies are in fact local. It is the discrepancy relative to an observed average for that site – often confused. It is the statistical practice of subtracting the mean.

        The son/tree analogy fails, because you are not considering the tree as a sample from a population of trees, measured by many other sons. Yes, you may have difficulty with that one measure. But it is still well established that trees do grow. In fact, tree measuring will be improved by the use of anomalies. Don’t measure from the ground. Plant a calibrated stake, and mark the historic observations, and difference. Put up a Stevenson screen to keep out the wind while you measure. It won’t be perfect, but after looking at a few trees for a while, you’ll figure that on average they grow.

      • Menicholas
        “That makes no sense and is not at all true.”
        Here’s the math. Suppose you measured T, it wasn’t proportional to CO2, so you tried to correct it so that it is:
        T + Adj = A*CO2 for some constant A
        And you then find that for some B
        Adj = B*CO2
        Subtracting
        T = (A-B)*CO2
        ie the original T was proportional to CO2.

        The conspiracy theory doesn’t even make arithmetic sense.

      • All you have shown is that the adjustments MUST follow CO2 in order for the math to work, which is the exact issue with the adjustments. The adjustments should have nothing to do with CO2 as that is not what they are for. It is merely reinforcing a circle jerk that has the conclusion chasing the data.

  13. Wow. Draw your curve, then plot your points.
    Theory before data. Then make sure the theory wins.

    On the face of it, any theoretically justifiable adjustments should be independent of the CO2 level.
    What is the P-value that the Figure 1 relationship is random? 0.000…001? How many zeros are after the decimal point?

  14. @sergeiMK: Do not take the word of posters here!!!!!

    Trace the data back to as close to its original source as possible, analyse it yourself (download, pop into excel etc).

    Then see which view seems reasonable.

    I am quietly confident that views such as those of RGB et al will agree with your research.

    However, you raise interesting points with, currently no clear answers.

    But it is illuminating to view the near past in scientific ‘findings’.

    Fat: bad/now good,
    eggs: bad/now good,
    Red wine: bad/now good,

    Only this morning on my BBC news channel, a report from a Prof. Tim Benton is enjoying wall to wall coverage of his new report saying that

    “Researchers say extreme weather events that impact food production could be happening in seven years out of ten by the end of this century.”

    even though if ***YOU*** download and plot the satellite temperature records, there has been no temperature increase for at least 18 years, so no possibility of a change in the extremity level of weather events.

    Now, the good Prof B. sprinkles words in such as could, might and may, which makes his paper worthless, why would he conclude that weather events are getting worse, if as we can all see that the temperature is effectively constant?

    I think that when this bad science episode has finished, there will be much research done into why scientists behaved the way they are, much research!

  15. I have argued before that HadCRUt’s version 3 actually matches global surface temps pretty well against those of the lower troposphere (1979-2014):
    http://woodfortrees.org/graph/hadcrut3gl/from:1970.5/to:1998/compress:3/plot/hadcrut3gl/from:1998/offset:-0.064/compress:3/plot/rss/to:2005.67/offset:0.13/compress:3/plot/rss/from:2005.67/offset:0.16/compress:3

    That is, after you’ve corrected for the obvious (but never amended, or even mentioned by the UKMO or UEA) calibration error across the 1997-98 seam between two different sources of HadSST2 data, which led to a spurious jump in the mean global sea surface temperature level of about +0.09K:

    GISS has managed to lift their global temperature series about 0.2K above “Reality” (HadCRUt3gl) since 1970. Most of it happened post 1998:
    http://woodfortrees.org/graph/gistemp/from:1970/compress:3/plot/hadcrut3gl/from:1970/to:1998/offset:0.1/compress:3/plot/hadcrut3gl/from:1998/offset:0.036/compress:3

  16. Is there a dataset of temperatures collected only by radiosond (weather balloons)? if the RSS is, as asserted, validated against a metric in which “Lower Troposphere temperatures … sample[s] smooth over both height and surrounding area (that is, they don’t measure temperatures at points, they directly measure a volume averaged temperature above an area on the surface. )They by their nature give the correct weight to the local warming above urban areas in the actual global anomaly, and really should also be corrected to estimate the CO_2 linked warming, or rather the latter should be estimated only from unbiased rural areas or better yet, completely unpopulated areas like the Sahara desert (where it isn’t likely to be mixed with much confounding water vapor feedback).”

    If so, how far back do the records go? What percent of the global area is sampled?

    • And where is Senator Inhofe’s promised review of GISS/NOAA homogenization of surface temperature records? I would have thought he would have started to have a conclusion prior to Paris December. Perhaps they are still digesting the Karl paper before launching the enquiry.

    • Wait..logic alert. An “official thermometer” is placed in position A, in Billy Bob’s backyard in a town of 20 people. It takes accurate measurements. 20 years later, position A:

      1-is in the middle of a sprawling metropolis, a concrete jungle.
      2.-is now position B, because “as the city grew, the thermometer was moved out of town”.

      In either future scenario, what logical reasoning creates a need to “add a cooling adjustment to the past” if the temperature recorded in Billy Bob’s backyard 20 years ago was ACCURATE?

    • Bogus claim Donald L. Klipstein.

      Isn’t odd that you did not back up your claim with citing any official thermometers getting moved out of town.

      There is more reliance on thermometers installed at the local airport, but only afew airports are actually ‘out of town’; even then those ‘out of town’ airports usually establish their own extensive areas of mortar, masonry, asphalt and large sources of heat.

    • They are what? Where is hell’s name did you get that from? Look at Anthony’s surface station work before blurting out such nonsense. You will save yourself a little embarassment

    • Donald

      One of the reasons to add a cooling adjustment to the past is correct: As cities grow, their official thermometers are moved out of town.

      That would seem to be a simple way to correct for UHI, and the best response just to leave the data as is.

  17. Why isnt anyone talking about the fact that super duper atmospheric experts at NASA launched a “state of the art” satellite last year designed to measure exactly how much CO2 was spewing into the air and where that CO2 came from, and yet OCO2 only produced ONE report in December of 2014 that hinted strongly that NASA et al were WRONG. Why no more press releases talking about the latest, up to datest OCO 2 data?
    Anyone?

    • Seems everyone will just have to wait… further adjustments ongoing. Such fine artwork takes time to sort and render with the desired public impact.

    • NASA OCO-2 team is placing the Level 2 CO2 measurements on the data portals. the data is mostly broken into 15 day chunks. The files are anywhere from 150 Mbytes to over 900 Mbs. But to use that data requires some pretty serious workstation power and the right data tools and the right technical skillset. Probably only a very select few groups has those. My guess is some manuscripts science papers have been written but are being held up for “unknown reasons.”

      But you are Correct in the observation that the one OCO-2 picture released last December pretty much destroyed the pre-OCO2 modelled pictures of the Northern Hem vs. Souther Hemisphere CO2 assumed sources.

      • But to use that data requires some pretty serious workstation power and the right data tools and the right technical skillset.
        =====================
        which obviously already exist because they quickly produced the first report.

        the absence of any further reports suggest that the someone in authority did not like the results.

  18. There so many different aspects related to the disagreement between a group that thinks we are warming at an alarming rate and those that think the warming has been modest(or flat the past 16 years).

    The battle taking place is over how extreme(or not) the temperature increase will be and the catastrophic effects(or not) caused by the increase in CO2.

    The biased opinions, come from humans viewing CO2 as either, pollution or a beneficial gas.

    The same humans apply the effects on other creatures so they line up with the effects on everything.
    In one camp, CO2 only has negative effects. Every report/study shows the negative consequences on climate, weather, the oceans and all life.

    As an operational meteorologist that predicts global crop production and US energy use, I can say with absolute certainty, that in my field of expertise, the increase in CO2 has been beneficial to world food production and less energy use(overall).
    Also, there have been less violent tornadoes, severe storms and hurricanes(but probably more flooding events). With the reduced meridional temperature gradient and increase in precipital water from slightly warmer air, this makes sense too.

    Without question, life on this planet always does worse when the planet gets colder and does better when it gets warmer. One side is tragically missing some key elements and focusing with tunnel vision on everything negative that can be construed, sometimes theoretically and speculatively in order to pile up the negatives with no positives.

    The proven law and maybe the most important one for much of life on this planet is this:

    Sunshine +H2O +CO2 +Minerals = O2 +Sugars(food)

    If CO2 were at 1,500 parts per million, going above the upper limit of benefits to photosynthesis, it would make sense to reduce it. However, we are at JUST 400 ppm and have quite likely rescued life on this planet from dangerously low levels of CO2, if we were in fact at just 280 ppm before the Industrial Revolution.

    Going well below 280 ppm CO2 would have been catastrophic to life. Going well above 400 ppm(doubling for instance) will mostly bestow additional benefits.

    But don’t believe me, ask life on this planet. Look around at the planet greening up and tell me it isn’t already providing the answer.

    This is not to say that we are doing a good job as stewards of the planet. We waste natural resources(especially water) and pollute. Our government subsidies and pushes environmentally ruinous policies(corn grown for ethanol) and instead vilifies the hugely beneficial gas, CO2.

    We waste the most money and resources trying to stop the positive contribution and don’t address the real negative ones with gusto.

    Think about the meeting coming up in December. It’s all about CO2 emissions. Why isn’t it about a billion+ people on this planet not having fresh water with that number projected to increase as we suck ground water/aquifers dry? Why isn’t it about corn ethanol causing massive pollution and wasting of natural resources/land? There are many important environmental issues that should be getting top billing but we don’t hear about…………..because our governments have their agenda and the cult/ideology/religion is based on a religious faith that ignores realities stated above.

    This is true brainwashing and bears no resemblance to the scientific method.

  19. The surface and lower troposphere are not perfectly linked. There are places that sometimes or often have surface temperature too cool for convection to the main part of the lower troposphere. This happens mostly at nighttime or in polar regions. As snow and ice coverage decreases, the local surface temperature can increase more than that of the atmosphere a couple km above. As increase of greenhouse gases reduces surface cooling at nighttime resulting in higher nighttime temperatures, this has little effect on temperatures a few km aloft. According to radiosonde datasets, since 1979 the lowest 100 or so meters of the troposphere has warmed .02-.03 degree/decade more than the lower troposphere as a whole. Have a look in figure 7 of http://www.drroyspencer.com/2015/04/version-6-0-of-the-uah-temperature-dataset-released-new-lt-trend-0-11-cdecade/#comments

    HadCRUT3 indicates 1979-onward warming being .03 degree/decade more than UAH V.6.0 does and is probably reasonably honest.

    • Unfortunately, Hadcrut3 ended in May 2014. However like the satellites, it had 1998 as the warmest year to the end. However GISS has 1998 in a 3 way tie for eighth place now.

  20. What a stunning correlation between USHCN Temperature Adjustments and Atmospheric CO2! It inspires this simple calculation:
    The slope of 0.0136522857 degrees F per PPM of CO2 converts to 0.007585 degrees C per PPM CO2.
    As CO2 increases 26 percent, from 317 PPM to 400 PPM, the Adjustments goes up 0.626 degrees C.
    An increase of 26 percent, or a factor of 1.26, is the cube root of a doubling of CO2.
    A doubling of CO2, then, leads to an Adjustment increase of 3 times 0.626, or 1.88 degrees C.
    This gives us another value of that holy grail of climatologists, the Climate Sensitivity to a doubling of CO2. In this case, the Climate Adjustment Sensitivity to a CO2 doubline is 1.88 degrees C, nicely within the IPCC estimates.

    • Nicely? I’d say it’s BARELY within the the IPCC estimates according to AR5. The sensitivity range according to AR5 is 1.5C-4.5C

      You’re talking it’s within the range by 0.38C. Maybe that’s why they dropped the lower end estimate contained in AR4 from 2 to 1.5…..:)

    • If its 1.88dC, we can all take a giant sigh of relief, particularly the doomers. The nasty scenarios rely on much higher sensitivities. Anything under 2dC gives us a nice pleasant glide path to mitigate any negative effects over many decades and centuries, while enjoying the many benefits of a slightly warmer climate.

  21. “RSS sample predominantly the layer of atmosphere centered roughly 1.5 km above the ground, and by their nature smooth over both height and surrounding area (that is, they don’t measure temperatures at points, they directly measure a volume averaged temperature above an area on the surface.”

    1. They dont measure temperature directly.
    2. The sensor sits in space. It is hit by photons that have left the atmosphere.
    3. That creates a BRIGHTNESS at the sensor.
    4. based on this brightness at the sensor you can then INFER a temperature at various altitudes
    a) This INFERENCE is based on multiple simplifying assumptions
    b) This INFERENCE is based on microwave radiative transfer models.
    c) start your reading with this paper
    http://journals.ametsoc.org/doi/pdf/10.1175/1520-0450%281983%29022%3C0609%3ASSOUTM%3E2.0.CO%3B2
    5. The satellite data May be compared to in situ radiosonds. The global coverage is miniscule
    some sample problems
    http://nsstc.uah.edu/users/john.christy/christy/2009_ChristyN_Australia.pdf

    If folks want to read an intelligent review they can start here. Its 144 pages long
    focus on pages surrounding 40 if you dont have the patience to learn

    http://www.scottchurchdirect.com/docs/MSU-Troposphere-Review01.pdf

    • What is the point of writing such drivel? No scientific instrument measures temperature “directly”. *All* temperature measurements are INFERRED. So what? When I measure temperature using a mercury thermometer I INFER the temperature by the amount of expansion of the mercury in the glass tube.

      What is the point of such a discussion other than a transparent effort to attempt to rubbish a data set that indicates the work you defend has problems? Pathetic.

      • “When I measure temperature using a mercury thermometer I INFER the temperature by the amount of expansion of the mercury in the glass tube.”
        A mercury thermometer has far fewer variables that can affect the accuracy of the measurements than a satellite measurement. That’s the difference.

      • And so does a GPF receiver. But it’s completely irrelevant so long as the process has been validated. That’s the difference.

      • That should have read, “GPS” not “GPF”. A microprocessor also has far more variables to consider than an abacus in terms of the technology that went into it, but the microprocessor is still more accurate.

      • Final example. Which has more “variables” to consider, a mechanical clock or an atomic clock? (By “variables” one assumes one means which is the more complex to build.) Also, which is the more accurate?

        The measurement of time must be INFERRED from the design of the device. No measurement instrument directly measures anything whether that is temperature, time, air pressure, etc. All measurements are INFERRED. More complex devices are typically MORE accurate, not less accurate. That’s why they are made more complex to begin with. What a surprise…

        The game Mosher is playing is to try obfuscate by implying that complex = less accurate. That is not true. It’s not even true is simplistic cases. It’s a dumb thing to try to imply.

      • you think?
        dontcha think that there are a myriad of sources for error in thermometer readings?
        accuracy of the temperature scale itself…
        variance in registration of the scale on the thermometer?
        variance in amount of mercury or whatever inside the thermometer?
        angle of viewing the thermometer?
        rounding error from the continuous nature of the thermometers’ data to the discrete nature of a recording of a specific temperature?
        the fact that thermometers measure the temperature of a point in space for all intents and purposes, not an area?

      • >>More complex devices are typically
        >>MORE accurate, not less accurate.

        Like the Harrison H4 chronometer.
        The most complex and the most accurate chronometer of its day.

  22. for folks to lazy to read.. here is a unformated version

    “If the surface and troposphere are indeed strongly coupled to each other thermally, then discrepancies between
    their temperature trends are indeed puzzling. At the very least, we would have to say either that uncertainties in MSU
    and radiosonde records are more uncertain than we imagined, or that there are regional and/or global interactions
    between the two that AOGCM’s are not getting. Most of the climate simulation models used over the last decade or so
    Located at:
    http://www.scottchurchdirect.com    >>   Climate Change    >>   Troposphere Temperatures
    41 of 144
    assume thermal coupling across atmospheric vertical layers and have been less well characterized regarding things
    might interfere with this coupling (e.g. water vapor, sea level pressure, or deep convection cells). So it is not surprising
    that they predict similar surface and upper air temperature trends. But if the troposphere is even partially decoupled
    from the surface, either regionally or globally, then surface and upper air trends may well diverge (NRC, 2000).
    Recently, several lines of research have emerged suggesting that this may well be the case. One of the most
    promising has been the work of Kevin Trenberth and David Stepaniak of the National Center for Atmospheric Research
    (Boulder, CO) on the earth’s global radiation budget. Trenberth and Stepaniak studied the earth’s energy budget and
    the way solar energy input to the atmosphere and surface are redistributed globally. Among other things, they found
    that important zonal and poleward energy transports occur in the tropics and extra-tropics that redistribute latent heat
    mush more strongly in these directions than vertically, decoupling the surface from the troposphere in these regions.
    The finding are particularly significant because it is primarily in these regions that lapse rates are much higher than
    expected from models, and the surface and troposphere trends are most noticeably different, and uncertain, in the
    various datasets. There are two mechanisms at work here which strongly couple vertical and poleward heat transport
    providing an almost seamless energy balance that connects outgoing long-wave radiative cooling with annual variation
    of solar atmospheric heating. Radiative cooling of the earth at the top of the atmosphere is globally uniform. But
    because the earth’s rotational orbital plane is tilted with respect to its solar orbital path (the ecliptic plane), the
    weighting of solar heating will shift in a meridional (north – south) direction annually – which is, of course, why there
    are seasons at higher latitudes. This requires a poleward energy transfer that must balance. Trenberth and Stepaniak
    showed that this balance has two components which favor a poleward transfer of latent heat that largely decouples the
    surface from the troposphere, particularly in the tropics and extra-tropics (Trenberth & Stepaniak, 2003a,b). They
    found that in lower latitudes the dominant mechanism of latent heat transport if the overturning of Hadley and Walker
    cells. In the upward cycle of these cells the dominant diabatic heat transfer occurs from the convergence of moisture
    driven by the cell motion itself. This results in a poleward transport of dry static energy that is partially, but not
    completely balanced by an equatorial transport of latent heat, leaving a net poleward transport of moist static energy.
    In the subtropics, the subsidence warming in the downward branch of these cells is balanced by cooling that arises
    from the poleward transport of energy by transient baroclinic eddies. These eddies are broadly organized into storm
    tracks that covary with global stationary atmospheric waves in a symbiotic relationship where one feeds the other. The
    relatively clear skies in the subtropics feed this cycle by allowing for strong solar absorption at the surface which feeds
    the latent heat transport cycle through evaporation, and in return, this is compensated by subsurface ocean heat
    transport that is itself driven by the Hadley circulation winds. The relationship between these cycles and how they
    exchange energy is shown in Figure 35.
    For their analysis of the magnitudes of these effects, Trenberth and Stepaniak used overall energy transports
    derived from reanalysis products for the period 1979-2001 from the National Centers for Environmental Prediction–
    National Center for Atmospheric Research (NCEP–NCAR) as derived by Kalnay et al. (1996) and used in Trenberth et
    al. (2001). These were deemed to be most consistent with the overall heat budget as determined from Top of
    Atmosphere (TOA) and ocean measurements (Trenberth and Caron 2001; Trenberth & Stepaniak, 2003a). Other
    complimentary heat budget data from the Southampton Oceanographic Centre (SOC) heat budget atlas was also used
    to characterize ocean surface heat transfer (Josey et al. 1998, 1999). Trenberth and Stepaniak noted that this data
    had considerably uncertainties due to sampling error and systematic biases from bulk flux parameterizations, but they
    were careful to use them only with relevant physical constraints that limited the impact of these uncertainties on their
    results (Trenberth et al., 2001; Trenberth and Stepaniak, 2003b). TOA data was taken mainly from Earth Radiation
    Budget Experiment (ERBE) satellite measurements of TOA radiation (Trenberth 1997). Precipitation estimates were
    taken from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) precipitation estimates (Xie
    and Arkin, 1997).
    Figures 36 and 37 show typical zonally average annual magnitudes of the energy transfers involved in these
    various processes in the tropics and extra-tropics for the North Pacific (Fig. 34), and the South Pacific (Fig. 35) for the
    ERBE period February 1985–April 1989. It can be seen that the net effect is to give the earth’s energy budget has a
    strong poleward component in the tropics and extra-tropics that redistributes a significant portion of surface reradiated,
    convective, and latent heat poleward rather than vertically. This should at least partially decouple surface temperature
    trends from upper troposphere trends in these regions in ways not accounted for in previous AOGCM’s. Given that this
    effect is most evident in the tropics and extra-tropics, we should expect that heat transfer processes that would
    ordinarily bring the troposphere up to the same temperature as the surface will be at least partially diverted, leaving the
    troposphere cooler (or perhaps under some circumstances, warmer) in these regions than would otherwise be
    Located at:
    http://www.scottchurchdirect.com    >>   Climate Change    >>   Troposphere Temperatures
    42 of 144
    expected. The fact that it is the tropics and extra-tropics that display the largest discrepancies between UAH and RSS
    analyses lends further support to this theory. There are still considerable uncertainties in the magnitudes of some of
    the heat transfer budgets in this process, and more work needs to be done to fully characterize it (Trenberth &
    Stepaniak, 2003a,b), so the degree to which this process contributes to discrepancies between various MSU analyses
    and the surface record needs further examination.
    The important point here is that the existence of such a mechanism means that we should expect at least some
    disconnect between surface and troposphere warming rates in these regions. Even if this disconnect proves to be of
    considerable magnitude, it would not present any issues for the long-term surface record, which we must remember, is
    robust and well characterized independent of the troposphere record (NRC, 2000; IPCC, 2001). As it is today, MSU
    products, and to a lesser extent radiosonde products, vary between those that predict little if any disconnect and can
    be comfortably reproduced by state-of-the-art AOGCM’s (Mears et al., 2003; Prabhakara et al., 2000; Vinnikov and
    Grody, 2003) and those that show relatively large, statistically significant disconnects (Christy et al., 2003). The truth is
    likely to be somewhere in-between. For our purposes, it is enough to emphasize that demonstrable differences
    between surface and tropospheric temperature trends do not invalidate either record. “

    • ” This should at least partially decouple surface temperature
      trends from upper troposphere trends in these regions in ways not accounted for in previous AOGCM’s. ”

      upper Troposphere yes, but lower troposphere there’s very limited decoupling. The discrepancy of a few years ago was enough to hand-wave (as described above). But today, the continued a increasing divergence with each new revision (as RGB put it):” the divergence is already large enough to be raising eyebrows, …”

      Finally, the MSU Troposphere decoupling explanation fails to even touch on the obvious positive warming effect, systematic corrections (as discussed by RGB) continuing to be applied in ever more magnitude in past measurements by those government agencies.

      • +1 It also does not provide either a mathematical derivation or a physical derivation for the gross adjustments made to all surface records or why UHI is a negative and not positive adjustment.

    • For our purposes, it is enough to emphasize that demonstrable differences between surface and tropospheric temperature trends do not invalidate either record.

      This would be easier to accept if there were not all of the adjustments that only the surface records underwent according to the top graphic for this article.

    • Considering that the troposphere is dimensionally a very thin layer on the earth’s surface, the idea of the tropospheric temperature being even partially decoupled from the surface temperature seems far fetched as an explanation of the divergence between the surface temperature records and the satellite temperature record. But considering that we are talking about some fabulous history of global average temperature and a minuscule alleged anomaly of less than 1C miraculously extracted from crappy data totally unsuited to the purpose, I find it difficult to credit any of the global temperature reconstructions. Essentially, these people are modern day alchemists trying to turn lead into gold.

    • I’m going to be blunt here. If I were your employer, you would not be allowed nowhere near any kind of Internet forum, and you would be terminated if you disobeyed that prohibition. You are arrogant and condescending, making the people for whom and with whom you work look really, really bad. Do them and yourself a favor, and us too, and absent yourself from public Internet discussions for a good long while.

      P.S. I see now that you are a member of Phi Beta Kappa with a degree in English: these facts are undetectable from your writing on this forum. (I am but a lowly member of Sigma Tau Delta with a B.S. in Math and Computer Science.)

      • I don’t have a problem with someone having an English degree that is self taught in maths and science, so long as they are good at what they do. But Mosher makes some amazingly stupid comments here on a regular basis, and while that’s not evidence that he doesn’t know what he’s doing, it’s not confidence inspiring either.

    • Typical Mosher, once again missing the obvious while copy and pasting mostly non cogent details, and at the same time insulting folk in general.

      First the divergence papers you are quoting refer mostly to regional, NOT GLOBAL divergences, and second, those reports are more then ten years old, So NOT RELATED TO THE CURRENT RECORD DIVERGENCE, which is unphysical, far more global then in the past when those papers were written, and does not in the least conform to ANY CAGW theory. Both surface and troposphere data sets cannot be right.

      Also Mr Mosher once again utterly fails to mention how thoroughly the satellites are measured and calibrated against weather balloons, which are unaffected by UHI, homogenization issues, station moves, and ever increasing ignoring of official stations in the data base.

      The satellite data sets show 1998 as the warmest year by a LARGE margin, about .3 degrees C. This easily exceeds their error margins, and by NASAs owns methodology 100 percent demonstrates that 1998 was warmer then 2014 and 2015. Further Mr. Mosher negates to mention that CAGW theory postulates that the troposphere should warm MORE THEN THE SURFACE.

      • In a previous comment on a different topic Mosher hand waved away the sat divergence by educating us with the information that nobody lives in the middle troposphere. Hence these data sets could safely be dismissed as irrelevant. (Well, that is the obvious implication of the comment, anyway.) You really can’t make up stupid like that.

      • Nop one lives in the ocean either. Or in the Arctic Ocean or on Antarctica. And yet these places are used to make the total warming what it is.
        Mr. Mosher also likes to point out that the satellites do not use an actual thermometer!
        Sophistry of the first order.
        All methods of measuring temperature rely on some or another physical characteristic of some material.
        I really am getting sick of the straw men and logical fallacy arguments.
        Just looking at Mr. Mosher’s comment, it is too lazy of an effort to even pay much attention to.
        Forbearance in the face of condescension is one thing, but from someone who has never, in my experience, shown any real trace of being in a position, intellectually or educationally, to condescend…it even more galling.
        No one is obligated to suffer such people cheerfully or reservedly.

    • Steven (and others): One can write a Word macro to convert a paragraph full of line breaks to one without. It simply does a search and replace to convert carriage returns to spaces. It’s easy–after one’s learned how to write macros.

      • You don’t even need a macro. You just do:

        Find …….. §p **
        Replace … sp
        And do a replace all.

        Mosh is simply the height of egotisical rudeness. He thinks he is so wonderful and superior, when he is actually the worst poster on this site – with the least to say and no ability whatsoever to explain what he means. I have said before that 50% of science is communication, which means that Mosh would probably be quite a dab-hand with a cart and broom….

        ** The characters for a line-return differ, from package to package.

    • Since you should have have least minimal technical computer skills, could you please edit your posts after you copy and paste them for formatting before hitting the “post comment ” button????
      Most of your stuff is annoying to read anyway, but the horrible formatting doubles it.

    • Mosh.

      Jezz, mate, have you still not learned how to do a global change to a Word or Pages file, to get rid of all the line-returns. You are either stupid or lazy. Yeah – lazy, the very term you accuse everyone else of being.

      Besides, which is the more complex, with the most uncertainty,

      a. 10,000 surface thermometers, each with their own siting, instrumental, interfere, scalar, measurement, urbanisation, and data compilation issues.

      b. A single thermometer viewing the entire world.

      R

  23. When are they going to stop adjusting past temperatures? As long as they continually adjust the temperature data, it is an admission that the data are wrong; otherwise, there would be no need to “correct” it.

    Those who uses current data sets such as GISS, Hadcrut, or Hadsst for scientific purposes are only fooling themselves. They have to know that the data they are using will be corrected, perhaps many times, in the future. So what they are using now is wrong and cannot produce valid results. There is no scientific purpose for a temperature data set that is constantly changing. It is useful only for propaganda purposes. I suppose they know that. They just don’t want to admit it because that would destroy the propaganda value, too, and make it useless for any purpose.

    • Entire bodies of ecology, ag science, microbiology-epidemiology, and social sciences are riding IPCC’s RCP8.5 (CO2 business as usual emissions) model ensemble-fueled gravy train of “if that, then this could happen.

  24. Imagine the impact of insisting the raw data,as measured, be listed in each one of those papers detailing doom by heat.
    Of course this would then force detailed explanations of the adjustments and their validity.
    Climatology can not go there.
    As the reader would mostly dismiss such speculation as nonsense.
    Climate Science really is not, only in the social sciences does such baseless speculation claim to be adhering to the scientific method.
    Must be a whole Post Normal method.
    As a taxpayer can I pay my share in Post Normal dollars?

    Steve McIntyre suggested that Climatology should try using the same standard that mining engineers are held to, we wish.
    Imagine a mine assessment using climatologies methods.

    • Or – imagine that medical companies operated by climatologies methods.
      Many countries has laws against quackery to avoid medical harm to people caused by unreliable scientific methods.
      Unfortunately, the existing laws cannot prevent quackery within climate science.

  25. Reblogged this on CraigM350 and commented:
    Professor Brown comments later in this article
    Why was NCDC even looking at ocean intake temperatures? Because the global temperature wasn’t doing what it was supposed to do!. Why did Cowtan and Way look at arctic anomalies? Because temperatures there weren’t doing what they were supposed to be doing! 
    From talking with meteorologists and communications with the UK Met Office this does sadly seem to be the case. Their investigations are not geared towards what is but rather why rather why it is not matching forecasts. Josh had it spot on…

    • Karl Popper did a great work demonstrating why inductivism and justificationism are utterly flawed.
      I see so many good reasons why the modern scientific method; Karl Popper´s empirical method, should always be applied. Good scientists know that their theory are merited by the severity of the tests they have exposed it to, and not at all by the unlimited amount of possible good reasons why a theory could, or should be correct. Here are some quotes from Poppers work I personally find very essential. I think these quotes also helps to become aware of some shortcomings in climate science:

      “A scientist, whether theorist or experimenter, puts forward statements, or systems of statements, and tests them step by step. In the field of the empirical sciences, more particularly, he constructs hypotheses, or systems of theories, and tests them against experience by observation and experiment.”

      “The .. empirical method .. stands directly opposed to all attempts to operate with the ideas of inductive logic. It might be described as the theory of the deductive method of testing, or as the view that a hypothesis can only be empirically tested—and only after it has been advanced.”

      “But I shall certainly admit a system as empirical or scientific only if it is capable of being tested by experience. These considerations suggest that not the verifiability but the falsifiability of a system is to be taken as a criterion of demarcation. In other words: …. it must be possible for an empirical scientific system to be refuted by experience.”

      “it is still impossible, for various reasons, that any theoretical system should ever be conclusively falsified. For it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition. It is even possible without logical inconsistency to adopt the position of simply refusing to acknowledge any falsifying experience whatsoever. Admittedly, scientists do not usually proceed in this way, but logically such procedure is possible”

      “the empirical method shall be characterized as a method that excludes precisely those ways of evading falsification which … are logically possible. According to my proposal, what characterizes the empirical method is its manner of exposing to falsification, in every conceivable way, the system to be tested. Its aim is not to save the lives of untenable systems but … exposing them all to the fiercest struggle for survival.”

      “All this glaringly contradicts the programme of expressing, in terms of a ‘probability of hypotheses’, the degree of reliability which we have to ascribe to a hypothesis in view of supporting or undermining evidence.”
      (Which is exactly what IPCC largely does in their work by their invention of degrees of agreement and by expressing their subjective confidence. The IPCC report is a grand monument over inductivism and justificationism.)

      “The Logic of Scientific Discovery” It is well worth a read. The first part of the book is easy reading and enlightening on Popper´s empirical method. I think that scientific minds will find it soothing. http://strangebeautiful.com/other-texts/popper-logic-scientific-discovery.pdf

    • never has there been a better example of a cartoon doing a far better job than a thousand words could ever hope to .

  26. Werner Brozek, (edited by Just The Facts) wrote:

    “In the post with April data, the following questions were asked in the conclusion: “Why are the new satellite and ground data sets going in opposite directions? Is there any reason that you can think of where both could simultaneously be correct?”

    Werner Brozek /Rgbatduke/ Just The Facts,

    Werner Brozek (& Just The Facts) , that is a great question; and rgbatduke, that is a wonderfully stark answer.

    Perhaps we should start to develop a matrix like this to keep track of assessments of the various temperature work products? This is just a quick concept of a matrix.

    John

  27. Glad to see others catching on to the established fact that global SAT indices are manufactured by reverse-engineering the desired connection to CO2 via unconscionable systematic “adjustments” of actual measurements. Without such devices, the CAGW meme would fall apart even in the minds of novices.

      • BTW, since the use what is essentially the same adjusted data, it is not a surprise they look similar.

        The troposphere not warming is completely contrary to CAGW physics. This is the true strength of this post. Do you wish to debate that point?

      • Please Mr Nick S, show us where in the entire body of the iPCC and all papers written on CAGW, there is a prediction the troposphere will not warm at all for twenty years, but the surface will set new records every year.

      • Since Professor Richard Muller thoroughly trashed Michael Mann, he has not had much to say in the Climate field, other than an op-ed in WSJ. His daughter, Mosher’s boss, on the other hand, a true fanatic, continues to push to destroy modern civilization. Mosher does as he is told, clearly needs this job, leave him alone poor fellow…

      • “In fact, SAT adjustment makes very little difference.” Then why do it?

        You are, as far as I can tell, talking about what happens in a single multi-stage adjustment process. As David A notes August 14, 2015 at 9:46 pm, there have been large changes to the record over time.

        For instance, look at Hansen’s Figure 4 from his 1999 paper “GISS analysis of surface temperature change”, on page 36. Compare that with the current corresponding graph at the GISTEMP webpage.

        In the current version, the anomaly for 1900 is almost -0.2°C; that for 1999 is almost +0.6°. That’s a change of nearly +0.8°C. But in the 1999 version, the anomaly for 1900 is just slightly below 0.0°, and the anomaly for 1999 is just slightly below 0.4°C. That’s a change of only about 0.4°C.

        Over a span of about 15 years, GISS altered the temperature record to effectively double the change in temperature from 1900 to 1999.

      • Nick Stokes:

        Through indiscriminate kriging of UHI-corrupted station data into the countryside and over-zealous “scalpeling” of intact records, BEST produces a bogus trend in SAT that is no less egregious than that introduced by conscious mimicking of CO2 data. Because neither you nor any of the index manufacturers have any professional concept of vetting field data to exclude UHI effects nor any realistic spectral specification of natural variability, your claims of innocent adjustments are based on exercises in circular reasoning.

      • Through indiscriminate “kriging” of UHI-corrupted station data into the countryside and over-zealous use of “scalpeling” of intact records to achieve “homogeneity,” BEST introduces a bogus trend into its global SAT index that is no less egregious than that produced by conscious mimicking of the CO2 record. Because neither you nor any of the index manufacturers have any professional concept of vetting station records to exclude UHI effects nor any spectral specification of natural variability, your claims of minor, innocent adjustments are based upon circular reasoning.

      • So Berkeley Earth is in on the conspiracy too?

        No, Berkeley Earth is also wrong in assuming non-correlated gaussian distributions when conducting statistical tests (e.g. when adjusting station readings, or testing their algorithm).

        In the BE paper on how they do the adjustments, they fail to cite a significant finding that autocorrelation breaks most standard changepoint detection methods. Temperature time series are auto-correlated. So BE is likely adjusting far too much.

        BE’s paper:

        ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/papers/williams-etal2012.pdf

        Paper that shows how bad changepoint detection techniques fail on autocorrelated data (section 4, in particular Table 1)

        http://journals.ametsoc.org/doi/pdf/10.1175/JCLI4291.1

        Peter

    • Moderator:

      If comments, such as mine of Aug. 15 at 1:36pm, did not disappear without a trace upon submission WUWT, you would not get duplicate re-writes.

  28. “…
    IMO, there is absolutely no question that GISS and HadCRUT, at least, are at this point hopelessly corrupted.
    …”

    Just about says it all.

    Thanks Dr. RGB for the straightforward no nonsense assessment.

  29. For everyone ‘too lazy’ to read this…just keep your eye out for the word ‘marketing’.
    Steven M. Mosher, B.A. English, Northwestern University (1981); Teaching Assistant, English Department, UCLA (1981-1985);
    Director of Operations Research/Foreign Military Sales & Marketing,
    Northrop Corporation [Grumman] (1985-1990); Vice President of Engineering [Simulation], Eidetics International (1990-1993);
    Director of Marketing, Kubota Graphics Corporation (1993-1994);
    Vice President of Sales & Marketing, Criterion Software (1994-1995); Vice President of Personal Digital Entertainment, Creative Labs (1995-2006);
    Vice President of Marketing, Openmoko (2007-2009); Founder and CEO, Qi Hardware Inc. (2009);
    Marketing Consultant (2010-2012); Vice President of Sales and Marketing, VizzEco Inc. (2010-2011); [Marketing] Advisor, RedZu Online Dating Service (2012-2013); Advisory Board, urSpin (n.d.);

    Team Member, Berkeley Earth 501C(3) Non-Profit Organization unaffiliated with UC Berkeley (2013-Present)

    • And your point is? Christopher Monckton has a degree in journalism, and has been a journalist, run a shirt shop and been a political adviser for much of his career. Yet I don’t see his lack of scientific credentials criticized here.

      • “His comments are logical, and is mathematical acumen is very high” and, more importantly, he follows the party line for Whats Up.

      • Chris,

        When you cannot refute Lord Monckton’s science, you do the usual ad hominem attack.

        There is no better evidence that Lord M is correct — and that you’ve got nothin’ to counter him.

        @trafamadore: That may be. But you omitted the fact that the WUWT ‘party line’ follows science — unlike you. Who do you follow? Algore?

      • dbstealey says: ” you omitted the fact that the WUWT ‘party line’ follows science”

        you forgot the sarc tag. People might think you were serious.

      • trafamadore,

        So Algore is your Messiah!

        Based on your abysmal batting average (‘there was no consensus that contradicted Galileo’; and your having no understanding of the Constitution; and ‘The mining company caused the yellow river, not the EPA’; and “Tisdale is more worried about the demise of his little hiatus” — “little”, after almost twenty years of ‘hiatus’; and “climate scientist Peter Gleick” [heh, as if]; and “Eco warriors use carbon to move around so they can get people to stop using carbon.”)… why should anyone assign any credibility to any of your posts?

        Practically every comment you make is scientific nonsense, ad-hom attacks, appeals to corrupt authorities, or just simpleminded cheerleading for a failed conjecture (CO2 causes dangerous man-made global warming).

        If you’re ever out of work, you can get a job as a parrot.

      • db and “get a job as a parrot.”

        Well, I get to parrot real scientists; you get to parrot their polar opposites, Tisdale and lordy Monkton. Sounds good to me.

        PS. Did Monkton really run a shirt shop?

      • trafamadore,

        You think running a business is a criticism. I doubt you could run a lemonade stand successfully.

        As for your guy Mann, he claims to be a Nobel Prize winner.

        One is ethical, and one is a fakir.

      • If you’re going to quote his credentials, do them fully. Monckton has a M.A. in Classics from Cambridge, his first degree.

    • charles nelson,

      I’ve met Steven Mosher several times. He’s really a nice guy. Smart, too, I guess. But I can never get over the fact that someone who earned a degree in English cannot write a correct, coherent sentence. What’s up with that? Are degrees at NU handed out to anyone with a pulse?

  30. Follow the money. Research grants, political contributions, university positions, consultancies, government jobs, etc. These are your real causal variables when it comes to climate science.

    • Research grant money is given out in many fields – medical research, oceanography, geology, etc. Why don’t “follow the money” problems occur in these fields?

      • An interesting question.

        The problem with the bit of climate science that has to do with the future and is most “political” is that unlike most other sciences it isn’t falsifiable within the the time frames that most funders operate on.

        Of course fads and fashions make blind alleys fundable for a while, but the great day of reckon tends to come within a couple of funding cycles and everyone moves on. Climate science has a longer time frame before judgement day, but I think they had better be unequivocally delivering the goods before the end of the decade or the funding tide will start to go out.

      • Sure…end of the decade. What is another $150 billion in our tax dollars?
        We should begin to get some truth by then, huh?
        Most people need to “deliver the goods” long before hundreds of billions are tossed to them.

      • Menicholas think it as tax breaks for a religion. Equally unfalsifiable but the established churches get taxpayer resources as long as they manage to keep enough voters on board.

        The point is that the funding issue is a political issue not a scientific one.

        I’ll probably now be banned at William M. Briggs.

      • “Research grant money is given out in many fields – medical research, oceanography, geology, etc. Why don’t “follow the money” problems occur in these fields?”
        =============================================================
        Those fields do not allow statist the necessary excuse to tax the very air you breath and expand political power over others life’s that CAGW offers. Political statist, like vampires drawn to blood, flock to the CAGW me-me.

      • Why don’t “follow the money” problems occur in these fields
        ==============
        they most certainly do occur in medical research. or do you think the current epidemic of obesity and diabetes in the US is due to “no willpower”? apparently no one thought to ask what would happen if you fed people the same diet used to fatten cattle.

        fields like oceanography, geology, etc. have no money so there is nothing to follow.

      • Science used to be a vocation (still is in many fields) but it is in the process of being commoditised, corrupted and “bought and sold by (insert appropriate qualifier) gold”

        Here is a really nice example of the corruption of science by money http://whistleblower.org/actonel Who dares to doubt that this is being repeated throughout academia? How many potential whistle blowers prefer to keep quiet and retain their jobs? Tip of the iceberg?

        Perhaps the differences between this and the climate science world are that (a) it was really, really blatant; (b) an actual bribe was offered in plain sight; (c) it was a singular event at one time and one place and (d) it was done by big bad pharma, whom we all know are ruled by money, money and money (but not necessarily in that order). The whole public-sector research-grant-giving tenure-granting environment is much more fuzzy and seems to work by unspoken and unwritten rules that have more in common with religious orthodoxy and political correctness than heavy-handed threats and orders. Also, money is a tool rather than a raison-d’être.

        I wish someone would show me how to insert a hyperlink. Techno-klutz here is a twentieth-century guy adrift in the 21st. Perhaps I should stick to looking at rocks, but I’m captivated by the transparent absurdity of the whole global-warming industry and can’t keep away from reading about it.

      • re: “Why don’t “follow the money” problems occur in these fields?[ medical research, oceanography, geology, etc. ]Chris

        By Jove Chris you got it! Corruption is ubiquitous.

        Dan Kurt

  31. First of all, I once knew a goose and it would resent being compared to a climate agitator.

    Second, the problem pointed out here is EASILY corrected, We just need to tweak the satellite data since it is obviously the problem. Probably orbital decay or time drift – we can find something that works in the favor of AGW. I mean, these guys are so CREATIVE.

    (I am sorry, but I have lost my faith that science is self-correcting anymore… They have gotten away with this nonsense for over 20 years now.)

  32. Anthony knows which are the good stations in the US. How about a continually updated chart for those and compare that to the USCRN chart.

  33. Mr Goddard really needs to post the source data and code. It’s bad for the skeptic side to follow the same bad practices as the CAGW side. Nick Stokes has tried to reproduce the adjustment and can’t, and he posted source and data. He has a valid looking falsification. Do you want this falsification of Goddard to continue to be valid or not?

      • Bull.

        I’ll grant you posted that at 1:17am, but you might want to explain why you said that?

        Posting source code and data is SOP for the Open Atmospheric Society. It’s not SOP for the warmists. Let’s do better than them.

      • Goddard/Heller posts source code and data. He might not for a repeating chart, which he uses often, but certainly does with the first instance.

      • Goddard/Heller posts source code and data. He might not for a repeating chart, which he uses often, but certainly does with the first instance.

        So how many hours do you want me to spend on search engines and manually searching SG’s website? I’ve already blown 20 minutes so far. Now multiply that by the number of readers.

        If he’s posted it, why not just link to it every time? It’s easy, and saves a lot of hassle by the readers.

  34. The Monty Hall problem, aka two boys and sibling problem, (re Marylinn vos Savan) might shed some light on why thousands of highly intelligent professors of Mathematics, no less, can make probability/logical errors.

  35. Since 70% of The GISS and HadCRUT measurements are based on water temperatures 1,5 m or so below the surface why should they be comparable with the LT temperatures .? The ALR is not applicable, I guess, between water and air.

  36. Interesting post.

    I am glad to see that there are those willing to point out the obvious fact that modern “climate science” is built on top of pure hoax. (I would use the F-Word but it is a “trigger word” here)

    When I learned about the earth’s weather machine and climate it was the beginning of the 70s and we held to the US Standard Atmosphere Model that was developed by real scientists during the space race with the USSR. Sometime during the late 80s we decided, without any proof at all, that the then current model needed to be junked and we should use an ancient model resurrected by two of the worse scientists of modern times. (I’ll not name them at this time — guess)

    So, OK, perhaps the modern theory is correct, after all a lot of rent-seeking minions of the state, and people who recieve very generous gifts from the state, claim that the debate on the underling theory is over. If the theory were, indeed, correct then one would think that the data would not need to be “adjusted” (what a weasel (2) word for what really is going on) every day. We can never just up and say what the temps were in 1931 for example. Why the hell not?

    Why not? Well, I think it is because we went down the rabbit hole when we claimed that CO2 did any warming at all. Certainly that theory must be held to in all aspects of public life or you are a crank or worse. Someday, this too shall pass. And when it does, it would be nice if Karma gave me a little justice upon the criminals large and small in this affair. (alas, at my age I’ll most likely not live to see it)

    (1) http://hockeyschtick.blogspot.com/2014/12/why-us-standard-atmosphere-model.html

    (2) some of my favorite pets were weasels, I don’t mean to belittle weasels by comparing them to “climate scientists)

    • As I recall, Mark, there was no debate. The opening line in the conversation was a politician, who has taken exactly one science class in his life, declaring that the debate was over!
      (BTW, I seem to recall his professor in that class said he was not a bright student and barely passed.)

    • US Standard Atmosphere Model
      ====================
      I’ve had a quick read through the article on the US Standard Atmosphere Model and the Greenhouse Equation. Fascinating. Truly.

      In effect the 33C greenhouse effect is due to the atmosphere lapse rate. the midpoint of the mass of the atmosphere is slightly more than 5km elevation, and at this point the atmospheric temperature is 255K, which is the temperature calculated for solar radiation reaching the earth.

      The 33c of warming is thus the 5km x 6.5c/km wet lapse rate. Which implies that the only way to change the average temperature of the earth is to change the solar radiation reaching the earth or to change the amount of water condensing in the atmosphere.

      • ferdberple above – “or to change the amount of water condensing in the atmosphere” sounds a bit like Willis Eschenbach and his tropics evaporation theory to maintain global temperatures within a narrow range.

      • interesting observation. as temperatures rise, as more water evaporates from the ocean and condenses in the atmosphere, the wet lapse rate will decrease, to say 6, the greenhouse effect is reduced to say 30C, decreasing surface temperatures by 3C, reducing the temperature.

        quite the opposite of what the IPCC predicts. They believe that radiation will increase the surface temperature due to the greater amount of water in the atmosphere increasing the greenhouse effect.

      • “…Willis Eschenbach and his tropics evaporation theory…”

        Evaporation and condensation into sunlight-reflecting clouds.

  37. Since there is trillions of dollars of expenditures planned to combat CO2 emission, one would think that spending 0.00001 trillion on a couple more temperature satellites would be a useful spend.

    I guess that’s only for those who want the real answer.

  38. It must be genetic! Maybe I can get a grant to study the possibility that there is a human gene that both predisposes a person to work for government AND exhibit a unique susceptibility to CO2 whereby an increasing level decreases their propensity to tell the truth? Hmm… I guess I should add up the projected costs to conduct my research before submitting my proposal –

    Paper: $1.00
    Pencil: $0.25
    Polygraph: $744.99 (Stoelting-UltraScribe-The-Arthur-VI-Polygraph-Lie-Detector on Ebay)

    • No need for a polygraph, which warps statistics, not unlike “settled science”, eg, green house theory, global warming, global wierding, climate change, extreme weather, climate chaos et al.

      In the real world, there is a direct correlation between more science/engineering education and skepticism of extreme green house theory effects, to a point, that is until your job is directly dependent on pal review/grant seeking/rent seeking and politics; hence. the mendacious warmists’ arguments above

  39. GISS and HadCRUT, at least, are at this point hopelessly corrupted.

    Unfortunately due to poor change control and tracking practices, the data stewards of these temperature records will never be able to adequately respond to this claim.

    • Nick has posted source code and data. You haven’t. The closed data/closed source habits are something the warmists do, It’s not something skeptics should be doing.

      In the age of hyperlinks, Dropbox, Amazon S3, github, etc, it’s pretty easy to cite your code and data.

      Peter

      • Actually, he has done so repeatedly over an extended period of time. Just because your cursory glance at his site didn’t instantly reveal it, doesn’t mean what you say is right. You are wrong.

      • you missed the part about “in the age of hyperlinks”. If he’s posted it , link to it! it is trivial. I do it every time I publish a graph. It’s very easy and removes a lot of doubt and removes a counter argument. For extremely little work.

        It’s like writing bad English. sure your audience might figure it out, but why make them go the struggle and misunderstanding?

      • You said, “You haven’t” in relation to Tony’s source code and data. Nick Stokes doesn’t do that every time he comments on a blog. Nor does Tony. If you made more than a modicum of effort, you’d find what you were looking for. As it turns out, you didn’t. You’re statement is provably false. Be man enough to admit it.

      • Peter, Don’t be the clown of the day. Tony H has always pointed to the source of his data. If you don’t find it because the source has changed the link then look for it or ask Tony.

      • Tony H has always pointed to the source of his data. If you don’t find it because the source has changed the link then look for it or ask Tony.

        Search engine is failing. Browsing SG’s website is failing. I don’t have Tony’s email address. In fact mostly I know about SG’s productions, not Tony’s.

        How many hours do I need to spend to satisfy you that it’s hard to find it? I’m already on 30 minutes. So far I’ve found UHSCN’s ftp server, which is good for data but I can’t tell if it’s the same data SG/Tony/Whoever is using and it doesn’t include source code…

        Making it hard for your audience is bad communication. I believe you are caught in your own bubble and can’t clearly communicate outside of it, you’re assuming your audience knows everything you know. It’s a common problem, but you should correct it if you want your views to prevail.

        Calling names when someone can’t find and item on the WWW is childish and counterproductive. When I was a Unix admin back in my unwise youth we always use to say “RTFM” when someone wanted help, but it was always rude and stupid to do so because the poor schlub didn’t know which manual to look at. So instead, Windows took over much of the world instead of Unix… (Nowadays I send them a hyperlink and say “Here’s TFM”). So again if you want your views to prevail you need to make it easy for the consumer of your analysis to believe you.

        As it is, I think Nick Stokes is correct that over half of the alleged adjustments are bad analysis on SG/Tony/Whoever’s part. Because he explained why and provided data and source code. So how’s it working winning over people to your side? Not so well is it? And I’m a prettty strong skeptic of CAGW. But I’m also a strong skeptic of bad rhetoric.

        https://en.wikipedia.org/wiki/Rhetoric

        Peter

  40. I was beginning to feel sorry for Nick Stokes. He obviously does a lot of work in this area and much of his stuff is very convincing to a layman like myself. I also think that he is a true believer and not a paid follower.
    But then I read Steven Goddard’s response, to which he has pointed us above.

    How does Mr. Stokes explain that USHCN records show that the percentage marked with an “E” has more than doubled in less than fifteen years? And why has he not attempted to defend or even explain the strange mistreatment of UHI, which has been denounced not only by the authors but by a number of knowledgeable bloggers on this site?

    • “How does Mr. Stokes explain that USHCN records show that the percentage marked with an “E” has more than doubled in less than fifteen years?”

      The USHCN was set up in 1987. At the time, it consisted of selected stations that were currently reporting and seemed likely to continue. With USHCN, for historic reasons, the NOAA unwisely calculates an average absolute temperature for the US. That requires that you keep the same stations in the set, else the result depends on whether the changing composition of the stations was drifting warm or cool. So when stations do drop out, they use an estimated value to complete the calculation.

      So in 1987 there were 100% stations reporting, and a good percentage continued for some time. But over 30 years, volunteer observers grow old, move, or whatever. The percentage drops.

      • Sounds like Goddard/Heller’s FUD description to me. How can USHCN assign estimated temperatures to reportedly 50% of stations and claim the accuracy they do. Seems to me we are getting nearer the truth. Kudos to Nick Stokes for at least admitting this point Goddard/Heller has been making repeatedly.

      • “reportedly 50% of stations “
        Reported by whom? It isn’t 50%.

        The fact is that they have, in recent years, 800-900 stations reporting each month. That is still a lot, and gives good accuracy. Infilling is just a device to get the best estimate of the average, based on that number and with a method consistent with what was done before. It doesn’t add information. NOAA has, incidentally, recently adopted a new approach.

        Pollsters do something similar. If they have too few men in their sample, despite trying for the right number, they don’t give up. They adjust by upweighting. One way of doing this is to “fabricate” extra men in the count, who respond like the average of the other men. It’s a convenient method if you are correcting across several categories. It doesn’t create extra information – it just corrects a bias.

      • So when stations do drop out, they use an estimated value to complete the calculation.
        =====================
        you’ve got to be kidding.

        only a numskull that has no idea of statistics would come up with that sort of solution. You cannot hope to preserve the stations. They are not static. They will change over time as will their surroundings. It is a nonsense to try and adjust the readings to try and compensate, to the point of inventing readings for stations that no longer exist.

        What will we learn next? That ARGO invents readings for floats that stop working?

      • “so the percentage now is around 50%. you feel this is acceptable?”
        Why don’t you actually try to find out what it is? It’s just a matter of counting. And no, it isn’t around 50%.

        In any case, about a year ago NOAA switched to a different method based on fine gridding.

      • “That requires that you keep the same stations in the set, else the result depends on whether the changing composition of the stations was drifting warm or cool. ”

        Umm, what? You imply that recorded temperatures are inaccurate due to other recorded temperatures, and that you, or anyone, know(s) what said recorded temperatures Should Have Been? No you do not, and in terms of handling data, this is an obscenity! You are condemned to doing Professor Brown’s taxes for life, as well as his offspring…

      • That explanation is the most idiotic I’ve ever heard of. This really is the worst kind of junk science.

      • My thanks to Nick Stokes for replying to my first point. His explanation also provides an explanation as to why Mr. Goddard is correct in stating that getting on for 50% are estimates. I am always impressed with Mr. Stokes knowledge and diligence. Where I differ with him is that I do not believe that any series where even 10% of the raw data is “homogenised” is valid. It may be useful but to base any serious credence on it cannot be justified. There is too much scope for bias, even if that bias is unwitting.

        Mr. Stokes points out below that pollsters use the same techniques. That is probably why none of the polls in this year’s Israeli election (including the exit polls) got anywhere close to forecasting Netanyahu’s majority And why, more significantly, all the polls in Britain were so inaccurate that even allowing for their “margin of error” none got anywhere near to correctly forecasting a small but significant Conservative majority.

      • That requires that you keep the same stations in the set, else the result depends on whether the changing composition of the stations was drifting warm or cool. So when stations do drop out, they use an estimated value to complete the calculation.

        So, to put this in terms of another trial I’m quite familiar with — a physician enrolls 100 patients in a study of whether or not eating plums prevents hangnails. Initially, on average, there is no average hangnail-preventative response to plum-eating, but the physician perseveres, thinking that perhaps the benefit only appears over time. However, many of his original enrollees get tired of eating plums, or die from plumorrhea, or start to eat apricots instead. After a few years he has only 50 patients left.

        Does he:

        a) Do the best he can with those 50 patients as a sample of 50 patients; or

        b) Fill in estimated values for the response of patient hangnails to plums, perhaps by finding the patient who lives closest to a drop-out and just using their data twice?

        I have to agree with Fred on this one. This is where I seriously question the competence of the people involved. Solution b) isn’t just wrong, it is (in the case of medicine) illegal. You can’t claim N = 100 for the results of a ten year study of plums and hangnails when only 50 patients complete the study, and nothing you can do to “estimate” the data for the missing patients can reduce the error estimate on the base of 50 that remains. The information on those patients is just plain missing. It is gone. We don’t know what happened, or would have happened, to them, had they continued in the study. The whole point of the study is to determine the very probability you would use to perform the estimate.

        Then, there are the nearly infinite opportunities for confirmation bias to creep in when making the estimate. In any patient population, some patients will have a positive hangnail response, and some of them will be living in an extrapolable cluster. All the physician has to do is find a population that is “drifting negative” as patients drop out and extrapolate the positive hangnail cluster to this missing members in this population and Surprise! The whole population is suddenly showing a positive response to the hypothesis that plums prevent hangnails, and at N=100 at that! The physician beats the dread p = 0.05 margin, headlines blare “Eat your plums, as they have been proven to prevent hangnails” and it takes forty damn years before somebody does a proper large scale study that proves, conclusively, that there isn’t the slightest positive response, that hangnails occur completely independent of the levels of plum consumption across not only the population but across all sub-populations. In the meantime the physician is given a permanent research position at a teaching hospital, runs a special plum clinic for hangnail sufferers, and retires, wealthy and lauded for his contributions to medicine — chances are decent he’s dead long before somebody figures out what was going on.

        I’d even throw in c) compute the yearly averages with the enrollees you have left, but adjust the error estimates as you go so that the certainty of your result properly diminishes as you reduce the number of supposedly independent and identically distributed samples drawn from the population of plum-eaters.

        I also looked at Goddard’s description of his methodology and his approach. Interestingly, it is an approach that if anything should show a strong warming bias from the UHI, as AFAICT he is taking a flat average of all reporting stations, and over time reporting stations should almost invariably become more urban as the population of the US has steadily increased in both number and density and (especially) energy consumption and land use changes. I agree that one should be very suspicious if adjusting and selecting and infilling data produces a result that significantly departs from a flat average, given only a reasonable density distribution of reporting sites and independent of the changing details of those sites. The whole point of averages is that those details should be no more likely to warm than to cool, that holding the base of the tape measure a little bit high should balance the times it is held a little bit low, the times it is read by somebody that always rounds up will probably be balanced by times it is read by somebody that always rounds down.

        Finally, I still can see no reason whatsoever that the adjustments relative to a flat average should follow a linear trend relative to CO2. Again, one would expect the opposite, that a careful treatment of UHI would produce a shift in all more recent flat-average temperatures down at a rate proportional to CO2, simply because CO2 production is proportional to energy use and population and hence the UHI.

        rgb

      • Bob, you take my breath away.

        I am trying my best, and hoping against hope, to get this insight out into the wider world. It is important and it is real. There is no way that the adjustments to the anomalies should so perfectly track the changing CO2.

        Tony Heller, Steve Goddard, has done an important thing and you and Werner have helped enormously in bringing this into the light. Let’s see how far it runs.

      • “Solution b) isn’t just wrong, it is (in the case of medicine) illegal. You can’t claim N = 100 for the results of a ten year study of plums and hangnails when only 50 patients complete the study, and nothing you can do to “estimate” the data for the missing patients can reduce the error estimate on the base of 50 that remains”

        That’s nonsense. Where did they claim N=100? They simply apply a technique for computing an average – in this case a spatial integral. There is no claim that it reduces the error estimate – it reduces bias. Goddard’s technique doesn’t. If you want to see this in full glory, see here. Goddard later patched that one up, but it is the method that is wrong. And it is the problem that NOAA’s infilling approach avoids.

        There is no issue with infilling in principle. The whole concept of a US average is based on infilling. You have 8 million sq km of ConUS, and you need a space average, and have about 1000 stations. In that average everything outside those stations is assigned a value imputed from the data you have. That is how integration is done. Then you add it up. In filling simply makes it a two-stage process, basically for arithmetic convenience.

      • rgb’s plum eaters are not a good example here. People dropping out of medical trials is an obvious issue and medical statistics has a bunch of techniques for dealing with the problem – censored data as it is known. They would not apply to temperature data of course, where the questions are rather different!

        Nick Stokes is, of course, right that there is nothing wrong with interpolation/in-filling of temperature data in principle. But climate researchers seem to process very complicated data – incomplete, spherical time series – with what might be called reckless abandon. Questions which call for careful analysis seem to get ignored if results meet a certain agenda – Karl being a good case in point. Interpolation of data is a notoriously thorny issue. For example, the comparatively easy problem of interpolating market option prices has caused all sorts of difficulties. Taking a somewhat extreme case in temperature interpolation, it seems doubtful that the krigers have much idea about the functions they are using to interpolate temperatures over large parts of the planet. This is just a guess of course, but since the relevant mathematics is deep into a straight mathematics degree, one of which I am pretty confident.

      • I agree that one should be very suspicious if adjusting and selecting and infilling data produces a result that significantly departs from a flat average

        Flat averaging IS the same thing as infilling, except not taking any spatial location into account. It’s more wrong than kriging*

        Imagine I have 4 stations, A, B, C, D. I get reports on year 1 from A and B, and reports for year 2 on C and D.

        In Goddard’s method (AFAICT, lacking source code) year1 = A/2 + B2. year2 = C/2 + D/2. The trend for the two years is thus C/2 + D/2 – A/2 – B/2. This means that A and B filled in for C and D in the first year and C and D filled in for A and B the second year.

        What spatial averaging (kriging) does is make it so that we don’t average let’s say Buffalo and San Diego stations. If San Diego is missing, maybe they use Los Angeles, which will have less error than using Buffalo as San Diego and LA have more similar weather.

        What SG is doing effectively is using Buffalo and 900 other stations to substitute for years when San Diego is missing. That’s more wrong than kriging.

        I think what’s happening with the adjustments that correlate with C02 is UHI. The adjustments for missing rural stations are probably using urban stations. Since urbanization and C02 are correlated, so the adjustments are correlated. I have to download a pile of data and get a resource of urbanization index to prove this hypothesis.

        In the end other posters are right though. Kriging or averaging, the data is just GONE. The error bars on this are huge. Heck, just the fact that a fractal surface is undersampled I’ve found increases the standard error of xbar by about 2x, because the distribution is not normal (it’s got kurtosis). Like almost all disciplines, I’m sure climatologists are assuming normalitly when in fact the data isn’t normally distributed…

        https://www.dropbox.com/sh/jzoxwyqbf3qs2j5/AAAysSOjhsYDuSvOu5_mbCiHa?dl=0

        If you are interested in an octave/matlab monte carlo simulation of undersampled autocorrelated surfaces.
        Peter

        * you might be amused that my spell checker is trying to autocorrect “kriging” to “rigging”…

      • This age of cheap calculators boggles my mind. Apparently you have to have “source code” to add up 2 sets of figures, take an average of each and then report the difference. Guess I am old. We used to do that with pen and paper.

      • Nick, you’re just digging the hole deeper. I downloaded the data and wrote my own scripts to check long ago, 40-50% of the latest month’s values were marked with an E. This is trivial for anyone with programming experience to verify.

        I work with complex data adjustments in the real (business) world every day, where bad results cost people jobs and put companies out of business. Steve is absolutely correct — you must first compare the simple averages and ask why the adjustments, whatever their justification, have the effect they do. It’s a basic sanity check, and if you can’t explain why the adjustments form a hockey stick, no one should take your data seriously.

        And every adjustment adds uncertainty. This is true whenever you touch the data. Yes, even if not doing the adjustment means you remove Buffalo one year and San Diego the next (missing data generally doesn’t have a bias). The more complex the adjustment, the harder it is for a human to evaluate whether the adjustment even makes sense, let alone adds bias. One very quickly arrives at a point where the data modellers can make the modelled data fit their biases.

        There are serious problems with the modelled, officially reported US data — NCDC said these past few Great Lakes winters were average, yet we have had record ice. The measured temperatures (and the simple averages) say these were cold years.

        I have to get back to work that people will voluntarily pay for, but the upshot is that there is no reason to think Steve’s simple average of measured temperature data is any less accurate than what is officially reported.

  41. Question – Why? Based on Steven Goddard’s graph of ’USHCN Temperature Adjustments Vs Atmospheric CO2′, why is there a systematic warming bias in the USHCN organization and also why is there a systematic warming bias in the GISS and HADCRUT organizations (those two orgs develop surface temperature time series products based on USHCN temperature products)?

    My question is why does there exist a systematic warming bias within those 3 government sponsored scientific focused organizations?

    I think one reasonable answer is that, as organizations, they hold the opposite of the view that climate science is an attempt to achieve objective understanding/knowledge of reality; rather, organizationally they view climate science as a means for producing work products that show there is global warming.

    Why do they have that view of climate science? I think the organizations have it because the leadership and general membership of the organizations learned a certain fundamental view of all science in college that requires science to be like that; learned it in courses that justified a subjective philosophy of science.

    The issue is a philosophical one. So that is where the intellectual battle must be fought for climate science.

    John

  42. Steve Goddard should give the technical specs for his graph(s), exactly which source datasets were used and the details of the processing used to produce those graphs. This is because (1) that kind of pedantry is expected in publications, and (2) SG has an early history of getting things wrong, which is why he was put off WUWT originally. He may have risen above that, but I’d need to verify anything I used from him.

      • “He’s done that time and time again on his blog. “
        Yes. And it is always the same C++ code (well, one for GHCN, one for USHCN). And all it seems to do (no description supplied) is read the USHCN data and put it into .csv files. That is the output of the linux script. The actual processing seems to happen in Excel spreadsheets, not supplied.

      • I’ve looked at SG’s USHCN code but I’m not good with C++. There’s a lot a repetitive code in the “main” module — but that’s not necessarily bad. But the code doesn’t seem to generate the final adjustments-CO2 graph. But it may be that when the csv files are produced, that the subsequent graphing is trivial. So I can’t audit this. If much is being made of this, it’s certainly worth for someone to replicate SG’s processing to audit & confirm the results. Sorry I can’t do better here.

      • The C++ code seems to output some generic statistics about the datasets – record high, low, and plain averages. But there is no geographic information handled (lat/lon). And no other datasets, like CO2. The comment says it is “Code for parsing and processing daily USHCN data”, and that is about it. It does that for each of the raw, TOBS and final files separately, so there is no way after averaging to match raw and final to get individual station adjustments.

      • I agree with Nick here. SG’s documentation is entirely inadequate. He should provide full step-by-step details of his processing. It’s not good enough to show a result, it must be replicable.

      • I’ve replicated his work in another language. Despite the 1970s data formats it’s a fairly trivial exercise.

  43. OK, let’s back up a little.

    If what the graph at the top of this post shows is correct, that proves data tampering, right?

    And if not, RGB (for whom I have a lot of respect, based on his previous posts and comments) is playing a joke on us, no?

    I’m as skeptical about warmism as anyone, but my horse sense tells me there’s something wrong with that graph.

    A really basic question, and I feel like a simpleton asking it… where does USHCN get its “raw” data from? GISS? Hadcrut? Somewhere else? And why does the body of the article not even mention USHCN after the first paragraph?

    Has anyone tried a similar exercise with GHCN?

  44. Nick Stokes writes: “Anomalies are in fact local. It is the discrepancy relative to an observed average for that site – often confused. It is the statistical practice of subtracting the mean.”

    That is correct but as a consequnce one should never then apply “Pairwise Homogenization Algorithm (PHA) Adjustments” which destroy that statistical spread. This automated algorithm which both NOAA and Berkeley use to “correct” the data has the effect of fixing a warming trend. It is the underlying reason why trends continue to rise. Yes their are some rational reasons why older data need adjusting due to station moves etc. but this homogenisation applied globally is simply wrong.

    To give one example – Santiago, Chile

    Red curves shows NOAA corrections for Santiago – resulting in 1.2C of apparent warming. Even CRU (green) did not meaure that. Blue are the raw measurements.

    The Urban Heat Island(UHI) effect in reality mostly ‘cools’ the past in all land temperature series. This may seem counter-intuitive but the inclusion of stations in large cities has introduced a long term bias in normalised anomalies. The reason for this bias is that each station gets normalised to the same eg. 1961-1990 period independent of its relative temperature. Even though we know that a large city like Milan is on average 3C warmer than the surrounding area, it makes no difference to the apparent anomaly change. That is because all net warming due to city growth effectively gets normalised out when the seasonal average is subtracted. As a direct result such ‘warm’ cities appear to be far ‘cooler’ than the surrounding areas before 1950. This is just another artifact of using anomalies rather than absolute temperatures.

    • Great example of why adjustments require enormous vetting and sanity checks, long before they should be considered valid inputs to multi-trillion-dollar global policymaking.

  45. The effort to make climate change seem less a past occurrence and more a current ONLY occurrence required the same kinds of adjustments to not only the data set, but to reconfigure what paleo-data to put IN the data set.

    To wit, when climate is cold in the North, and extends further into lower latitudes, equatorial heat will shift South of the equator, where few paleo-sources of proxies are available. Therefore the conclusion is often that past climate change was regional only, not global like it is being touted to occur today. Same is true for warm periods. It is possible that the extreme cold of Antarctica was marching towards the Northern Hemisphere during the Medieval Warm Period, but alas, there are few paleo-sources of proxies to draw from.

    Those that deal with past climate anomalies likely fail to appreciate that while one hemisphere experiences extremes in one direction, the other hemisphere may trend in the opposite direction. I wonder if a data set that simply records change (regardless if up or down) from a century scale climatological average would capture the global complex nature of major climate regime shifts of whatever cause during the span of time when human species walked the Earth, to a better degree than what we currently see from research. My hunch is that it would show that our current warming trend is a tiny blip in comparison.

  46. Interesting to see all the sincere discussion of the temperature data manipulation here.

    The real deal is at Tony Heller’s website. Tony did the analysis, code-crunching, data research a long time ago, uncovering the depth of the depravity of the manipulators.

    His website is quite well-organized, with categories provided in the heading of the home page.

    Note that, due to hosting issues, there are two versions of his site. The original has the best compilation of his historical postings. The header of the original site includes links to his data methodology, as well as other categories.

    Here is the original:

    https://stevengoddard.wordpress.com/

    Since March of 2015, Heller posts on his new site, Real Climate Science:

    http://realclimatescience.com/

    • The real deal is at Tony Heller’s website. Tony did the analysis, code-crunching, data research a long time ago, uncovering the depth of the depravity of the manipulators.

      I looked at both of your links. The first one has a “UHCN code” header that shows where some source code is. No excel spreadsheets though.

      The second one has no links to source code or data.

      Why don’t you just post the actual deep link? Or can’t you find it?

    • bit chilly… here too. Tomorrow’s high to be 73F, low 57F and that is in usually-hot-hot-hot-Oklahoma in August!, the hottest month of the year. Electric bill’s a crashing, only two days above 100F this entire summer, 101F and 102F, and that is quite weird here if you are young and can only remember the past couple of decades. When I was young, there I go, showing my age ;( , it was more like we are now experiencing.

      I am like you… where’s the frik’n global warming ?? After digging through all of the data for eight years, and the record manipulations, it becomes more than apparent… it never existed at all except for the very normal ±≈0.5°C oscillation spread across every six decades or so.

  47. Nobel laureate Ivar Giaever’s speech at the Nobel Laureates meeting 1st July 2015, who is not the typical rent seeking “scientist” or extreme left wing ideologue.

    ***I don’t approve of the youtube poster’s title, e.g. “climate hoax”

      • Truly. Win Nobel Prize. Retire. Become a skeptic and resign from the American Physical Society as soon as possible,

      • Always important to remember the non grant seekers/non pal reviewers/non political favor seekers and ideologues!
        ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::;

        Hal Lewis: My Resignation From The American Physical Society – an important moment in science history,,,

        Sent: Friday, 08 October 2010 17:19 Hal Lewis

        From: Hal Lewis, University of California, Santa Barbara
        To: Curtis G. Callan, Jr., Princeton University, President of the American Physical Society

        6 October 2010

        Dear Curt:

        When I first joined the American Physical Society sixty-seven years ago it was much smaller, much gentler, and as yet uncorrupted by the money flood (a threat against which Dwight Eisenhower warned a half-century ago).

        Indeed, the choice of physics as a profession was then a guarantor of a life of poverty and abstinence—it was World War II that changed all that. The prospect of worldly gain drove few physicists. As recently as thirty-five years ago, when I chaired the first APS study of a contentious social/scientific issue, The Reactor Safety Study, though there were zealots aplenty on the outside there was no hint of inordinate pressure on us as physicists. We were therefore able to produce what I believe was and is an honest appraisal of the situation at that time. We were further enabled by the presence of an oversight committee consisting of Pief Panofsky, Vicki Weisskopf, and Hans Bethe, all towering physicists beyond reproach. I was proud of what we did in a charged atmosphere. In the end the oversight committee, in its report to the APS President, noted the complete independence in which we did the job, and predicted that the report would be attacked from both sides. What greater tribute could there be?

        How different it is now. The giants no longer walk the earth, and the money flood has become the raison d’être of much physics research, the vital sustenance of much more, and it provides the support for untold numbers of professional jobs. For reasons that will soon become clear my former pride at being an APS Fellow all these years has been turned into shame, and I am forced, with no pleasure at all, to offer you my resignation from the Society.

        It is of course, the global warming scam, with the (literally) trillions of dollars driving it, that has corrupted so many scientists, and has carried APS before it like a rogue wave. It is the greatest and most successful pseudoscientific fraud I have seen in my long life as a physicist. Anyone who has the faintest doubt that this is so should force himself to read the ClimateGate documents, which lay it bare. (Montford’s book organizes the facts very well.) I don’t believe that any real physicist, nay scientist, can read that stuff without revulsion. I would almost make that revulsion a definition of the word scientist.

        So what has the APS, as an organization, done in the face of this challenge? It has accepted the corruption as the norm, and gone along with it. For example:

        1. About a year ago a few of us sent an e-mail on the subject to a fraction of the membership. APS ignored the issues, but the then President immediately launched a hostile investigation of where we got the e-mail addresses. In its better days, APS used to encourage discussion of important issues, and indeed the Constitution cites that as its principal purpose. No more. Everything that has been done in the last year has been designed to silence debate

        2. The appallingly tendentious APS statement on Climate Change was apparently written in a hurry by a few people over lunch, and is certainly not representative of the talents of APS members as I have long known them. So a few of us petitioned the Council to reconsider it. One of the outstanding marks of (in)distinction in the Statement was the poison word incontrovertible, which describes few items in physics, certainly not this one. In response APS appointed a secret committee that never met, never troubled to speak to any skeptics, yet endorsed the Statement in its entirety. (They did admit that the tone was a bit strong, but amazingly kept the poison word incontrovertible to describe the evidence, a position supported by no one.) In the end, the Council kept the original statement, word for word, but approved a far longer “explanatory” screed, admitting that there were uncertainties, but brushing them aside to give blanket approval to the original. The original Statement, which still stands as the APS position, also contains what I consider pompous and asinine advice to all world governments, as if the APS were master of the universe. It is not, and I am embarrassed that our leaders seem to think it is. This is not fun and games, these are serious matters involving vast fractions of our national substance, and the reputation of the Society as a scientific society is at stake.

        3. In the interim the ClimateGate scandal broke into the news, and the machinations of the principal alarmists were revealed to the world. It was a fraud on a scale I have never seen, and I lack the words to describe its enormity. Effect on the APS position: none. None at all. This is not science; other forces are at work.

        4. So a few of us tried to bring science into the act (that is, after all, the alleged and historic purpose of APS), and collected the necessary 200+ signatures to bring to the Council a proposal for a Topical Group on Climate Science, thinking that open discussion of the scientific issues, in the best tradition of physics, would be beneficial to all, and also a contribution to the nation. I might note that it was not easy to collect the signatures, since you denied us the use of the APS membership list. We conformed in every way with the requirements of the APS Constitution, and described in great detail what we had in mind—simply to bring the subject into the open.

        5. To our amazement, Constitution be damned, you declined to accept our petition, but instead used your own control of the mailing list to run a poll on the members’ interest in a TG on Climate and the Environment. You did ask the members if they would sign a petition to form a TG on your yet-to-be-defined subject, but provided no petition, and got lots of affirmative responses. (If you had asked about sex you would have gotten more expressions of interest.) There was of course no such petition or proposal, and you have now dropped the Environment part, so the whole matter is moot. (Any lawyer will tell you that you cannot collect signatures on a vague petition, and then fill in whatever you like.) The entire purpose of this exercise was to avoid your constitutional responsibility to take our petition to the Council.

        6. As of now you have formed still another secret and stacked committee to organize your own TG, simply ignoring our lawful petition.

        APS management has gamed the problem from the beginning, to suppress serious conversation about the merits of the climate change claims. Do you wonder that I have lost confidence in the organization?

        I do feel the need to add one note, and this is conjecture, since it is always risky to discuss other people’s motives. This scheming at APS HQ is so bizarre that there cannot be a simple explanation for it. Some have held that the physicists of today are not as smart as they used to be, but I don’t think that is an issue. I think it is the money, exactly what Eisenhower warned about a half-century ago. There are indeed trillions of dollars involved, to say nothing of the fame and glory (and frequent trips to exotic islands) that go with being a member of the club. Your own Physics Department (of which you are chairman) would lose millions a year if the global warming bubble burst. When Penn State absolved Mike Mann of wrongdoing, and the University of East Anglia did the same for Phil Jones, they cannot have been unaware of the financial penalty for doing otherwise. As the old saying goes, you don’t have to be a weatherman to know which way the wind is blowing. Since I am no philosopher, I’m not going to explore at just which point enlightened self-interest crosses the line into corruption, but a careful reading of the ClimateGate releases makes it clear that this is not an academic question.

        I want no part of it, so please accept my resignation. APS no longer represents me, but I hope we are still friends.

        Hal

  48. This seems relevant – a Berkeley Earth discussion about how close USHCN and BE are despite different methods:

    http://rankexploits.com/musings/2012/a-surprising-validation-of-ushcn-adjustments/

    The problem I see is they are both optimizing for spatial correctness and then doing time comparisons to see a trend. This is wrong. If you want to compare temperatures over a long period of time, you should be optimizing for time correctness and ignoring spatial correctness.

    If you wanted to look at temperatures over time (i.e. trends), you could:

    (1) Eliminate all stations that don’t have a contiguous healthy record
    (2) Time-interpolate stations with some short term (e.g. < 3 years) missing records. This is fine if you are comparing on multi-decadal scales.

    If you wanted to compare over the time dimension, you shouldn't be doing spatial interpolation…

    It's like the Heisenberg Uncertainty Principle – you can measure the location of a particle, or you can measure its momentum, but you can't measure both at the same time. Also same thing with a signal artifact – you can measure its frequency, or you can measure its location, but doing both at the same time is difficult and you can't get both exactly, only some compromise.

    I probably should go write a proof of this proposition… but it feels correct. Choose one – time correctness or spatial correctness. You can't have both.

    Peter

    • Peter Sable:

      You’re entirely correct in pointing out that accurate determination of temporal, rather than spatial, variations in temperature should be the main objective of studies to detect climate change. After all, the land surface is fractal and non-homogeneous in materials of composition, making the determination of spatially-averaged temperature highly problematic. The all-important low-frequency components of variability that determine the “trend” tend, however, to be highly coherent over distances of several hundred kilometers on the continents, thereby allowing fairly sparsely sampled locations to be used quite effectively as areal averages. It’s precisely the lack of such coherence between BEST and adjusted USHCN that calls into question both btime series.

      • hereby allowing fairly sparsely sampled locations to be used quite effectively as areal averages.

        The option (1) is the correct choice. Throw away station data that has long gaps or large known errors.

  49. Agreed with rgb – good work Sir.

    Below is my post from 2009 – a very cold year (btw, more cold years to follow).

    Note that in 2008 I calculated the “Warming Bias Rate” = [UAH – Hadcrut3]/time ~= 0.2C / 3 decades of ~0.07C/decade.

    Now from rgb above the Warming Bias Rate = [UAH – Hadcrut4]/time = [0.685 – 0.204] / ~3.5 decades = ~0.14/decade or TWICE THE WARMING BIAS RATE OF JUST 6 YEARS AGO.

    OMG it’s getting worse! We’re all gonna burn up from phony global Warming Bias Rate measurements! :-)

    Actually we will just squander trillions more on ridiculous green energy scams that are not green and produce little or no useful energy.

    The good news (actually not so good) is we’ll all be “saved” by imminent natural global cooling, which should start by about 2020, maybe sooner.

    People will look back at this brief warm period with great fondness, and wonder at all the false global warming hysteria.

    We should be keeping a log of names of all the warmist fanatics and their organizations, and preparing a major civil RICO lawsuit – contact me if you have the money to fund it.

    Regards to all, Allan

    https://wattsupwiththat.com/2009/05/19/comparing-the-four-global-temperature-data-sets/#comment-134269

    I think this is a good, rational analysis of recent temperatures.

    Comparing UAH and Hadcrut3 from 1979 to 2008 I get ~0.20 to 0.25C greater warming in Hadcrut3, or ~0.07 per decade, essentially identical to the above for the most recent ~decade (0.11 – 0.04 = 0.07C). See Fig. 1 at
    http://icecap.us/images/uploads/CO2vsTMacRae.pdf

    I have assumed that this difference is due to UHI, etc., as per McKitrick and Michaels recent paper and Anthony et al’s excellent work on “weather stations from hell” (or less critically, “weather stations from heck” – after all, we haven’t summarized third-world weather stations yet, have we?).

    What is perhaps equally interesting is that there has been no net warming since ~1940, in spite of an ~800% increase in humanmade CO2 emissions.

    See the first graph at
    http://www.iberica2000.org/Es/Articulo.asp?Id=3774

    I find all this anxiety about humanmade global warming to be rather undignified, to say the least. It is the result of the current state of innumeracy in the general populace, and says more about the hysterical tendencies of those who advocate for CO2 reduction than it does about the science itself, which provides no evidence for their irrational fears.

    Then there are those darker types who would seek to profit from these irrational fears, and have chosen to exacerbate rather than calm the disquiet of the general populace.

    In summary, the current movement to curtail CO2 emissions is unsupported by science, but is strongly supported by scoundrels and imbeciles.

    Regards to all, Allan :^)

  50. Engineers are trained to handle data. “Climate Scientists” apparently are not! This concept of a worldwide or nationwide “average temperature” is significantly flawed. Were I or any of my classmates tasked with producing such a number, we would select widely spaced, continuous records from around the country and/or the world, average them, and report. None of us would call it the Average Temperature of the United States, or the World, because it isn’t. None of us would adjust one single datum, much less produce an algorithm to “adjust” all of them.

    Nick Stokes and his ilk pretend they have knowledge they simply do not have, as Professor Brown points out. The Great Unwashed seem to believe it, as Main Stream Media gives it lots of ink, but this does not make it true.

    Gridding??!! “Kriging??!!” “Phantom stations??!!” Reporting an average to the .01 degree C when the data was taken to whole degrees? Ludicrous. The most offensive is the Arctic extrapolation over 1200 km and varying latitude, but the entire operation is a “mug’s game.”

    • “Were I or any of my classmates tasked with producing such a number, we would select widely spaced, continuous records from around the country and/or the world, average them, and report. None of us would call it the Average Temperature of the United States, or the World, because it isn’t. None of us would adjust one single datum, much less produce an algorithm to “adjust” all of them. ”

      Such a consistent database does not exist. Many of the adjustments are warranted. The data was not collected to study the problem of climate change but it is all we have.

      For example, Time of Day (TOB) adjustments are perfectly acceptable. The problem is, in the wrong hands, only adjustments like TOB that make the past colder are done. Ones like UHI are not or are distorted. Data homogenization techniques make painting the obs box every 10 years lead to global warming.

      There is, BTW, a pristine set of data sensors in the USA for this problem. It was set up in 2004. It shows no warming. But the time frame is short and it is only in the USA.

      Also, I have no problem calling it the “average temperature” That is what it is. The estimated average temperature (anomaly) of the planet at 2m above the surface. What is so wrong with that ?

      • Because it is not USA or World Average Temperature. It would be the average of five spots, or 500, or even 5000 if there were 5000 long continuous records, but even 5000 would not be a national or world average. Take a walk, notice that the temperature changes every few yards. I live in Chicago, on the Lakeshore, where a thermometer 2 miles offshore at the water intake can be 30 degrees F different from the airport twelve miles away…

  51. We need an independent verification and reproduce-ability of the Steven Goddard graph that begins this article. Has anyone tried to reproduce this data or have the raw data ?

    • Thank you for that! It is interesting to note that while the slope for UAH6.0 is positive for 5, 10, 15 and 20 years, it is actually negative for some times in between for example from April 1997 to February 1998 and for all of 2009.

  52. Dr. Brown says:

    …Note well that the total correction is huge. The range above is almost the entire warming reported in the form of an anomaly from 1850 to the present…..

    The date 1850 rings a bell. What was happening in the decade around 1850?
    Ice cores from the Freemont Glacier show it went from Little Ice Age cold to Modern Warming warm in the ten years between 1845 and 1855.

    ABSTRACT
    An ice core removed from the Upper Fremont Glacier in Wyoming provides evidence for abrupt climate change during the mid-1800s….

    At a depth of 152 m the refined age-depth profile shows good agreement (1736±10 A.D.) with the 14C age date (1729±95 A.D.). The δ18O profile of the Upper Fremont Glacier (UFG) ice core indicates a change in climate known as the Little Ice Age (LIA)….

    At this depth, the age-depth profile predicts an age of 1845 A.D. Results indicate the termination of the LIA was abrupt with a major climatic shift to warmer temperatures around 1845 A.D. and continuing to present day. Prediction limits (error bars) calculated for the profile ages are ±10 years (90% confidence level). Thus a conservative estimate for the time taken to complete the LIA climatic shift to present-day climate is about 10 years, suggesting the LIA termination in alpine regions of central North America may have occurred on a relatively short (decadal) timescale.
    http://onlinelibrary.wiley.com/doi/10.1029/1999JD901095/full

    So much for CAGW.

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