Guest Post by Willis Eschenbach
This replaced the previous sticky, and I have this comment about the Economist. Bad form and unprofessional to use the word “denialists”. For WUWT readers who wish to complain: letters@economist.com or use their online form here. – Anthony
AN OPEN LETTER TO THE ECONOMIST
On Dec 11th, the Economist published an unsigned article attacking both me and my work. This open letter is my reply.
TO: The Person Unwilling to Sign Their Economist Article
Dear Sir or Madam;
Recently, you wrote a scathing article about me in the Economist discussing my post called The Smoking Gun At Darwin Zero. Some of it was deserved, but most was undeserved and false. The URL for your unprinicpled attack is http://www.economist.com/blogs/democracyinamerica/2009/12/trust_scientists … trust_scientists? Trust_scientists?? Have you read the CRU emails?
But I digress … you begin by quoting from the Australian Bureau of Meteorology, viz:
A change in the type of thermometer shelter used at many Australian observation sites in the early 20th century resulted in a sudden drop in recorded temperatures which is entirely spurious. It is for this reason that these early data are currently not used for monitoring climate change. Other common changes at Australian sites over time include location moves, construction of buildings or growth of vegetation around the observation site and, more recently, the introduction of Automatic Weather Stations.
The impacts of these changes on the data are often comparable in size to real climate variations, so they need to be removed before long-term trends are investigated.
While this is true, it doesn’t apply. None of the GHCN adjustments are from any of those sources. This is because the GHCN does not adjust for location moves. Nor does it adjust for construction of buildings, nor for any of the other items listed. The GHCN uses none of those to make its adjustments. So all of that is totally meaningless.
Next, you say the “explanation for the dramatic change in 1941 is simple”:
As previously advised, the main temperature station moved to the radar station at the newly built Darwin airport in January 1941. The temperature station had previously been at the Darwin Post Office in the middle of the CBD, on the cliff above the port. Thus, there is a likely factor of removal of a slight urban heat island effect from 1941 onwards. However, the main factor appears to be a change in screening. The new station located at Darwin airport from January 1941 used a standard Stevenson screen. However, the previous station at Darwin PO did not have a Stevenson screen. Instead, the instrument was mounted on a horizontal enclosure without a back or sides. The postmaster had to move it during the day so that the direct tropical sun didn’t strike it! Obviously, if he forgot or was too busy, the temperature readings were a hell of a lot hotter than it really was.
This might make sense if there were any “dramatic change in 1941”. But as I clearly stated in my article, <b>there is no such dramatic change</b>. The drop in temperature was gradual and lasted from 1936 to 1940. The change from 1940 to 1941 was quite average. So that claim of yours is nonsense as well. In any case, the change in screening did not coincide with the 1941 move. In my article I cited a reference to a picture of a Stevenson Screen in use in Darwin at the turn of the century. Perhaps you didn’t bother to read that.
So, to sum up your first arguments, changes in the Stevenson Screens and other local conditions cannot be the explanation for any of the GHCN adjustments because 1) the GHCN doesn’t use local conditions to make adjustments and 2) the timing of the screen change is wrong. In addition, there was no “dramatic change in 1941”.Next, you point out two actual mistakes I did make.
First, in my proofreading I did not catch that I that I had written “the 1941 adjustment” when I meant the 1930 adjustment. That should have been obvious to me, because there is no 1941 GHCN adjustment. My bad.
Second, I had said that the Darwin temperature data couldn’t have been adjusted by using the GHCN method. This method requires five neighboring stations to which Darwin can be compared. Why couldn’t the GHCN method be used? I said it was because in the earlier time periods like the 1930s, there were no such stations covering that time period within 500 km of Darwin. I was wrong, it fact there is one such station.
Neither of these errors of mine affect my point, which is that there are not enough neighboring stations to adjust Darwin using the main GHCN method. The GHCN folks mention this possibility, saying:
Also, not all stations could be adjusted. Remote stations for which we could not produce an adequate reference series (the correlation between first-difference station time series and its reference time series must be 0.80 or greater) were not adjusted. The homogeneity-adjusted version of GHCN includes only those stations that were deemed homogeneous and those stations we could reliably adjust to make them homogeneous.
Unfortunately, they adjusted Darwin anyway. Consider the GHCN adjustment in 1920. To find five stations around Darwin covering 1920, you have to go out 1,250 km. Nor is there any guarantee that those stations will be suitable. You need to have five stations with an 80% correlation with the Darwin record … I wish you the best of luck finding those five stations.
So while my statement about stations nearer than Daly Waters was wrong as you point out (there is one nearer station that covers the 1930 adjustment), my point was correct – there are not enough neighboring stations to adjust Darwin using the GHCN method. The first GHCN adjustment to Darwin was a single year adjustment in 1901. To get five “neighboring” stations for that adjustment, you have to go out 1728 km. You fail to deal with that issue at all. Instead, you say:
“So is it reasonable, if the GHCN is using complex statistical tools to adjust the temperature readings at Darwin based on surrounding stations, that they might come up with the figures they came up with? Sure. No. Yes. I have no idea. And neither does Mr Eschenbach. Because in order to judge that, you would have to have a graduate-level understanding of statistical modeling. … I don’t understand that formula. I don’t have the math for it.”
“Surrounding stations”? We’re talking about stations a thousand km away and more, not surrounding stations.
And while I am sorry to hear of the lacunae in your math education, please don’t make the foolish assumption that others are similarly limited. I have no problem with the GHCN math. If you truly have no idea on the question as you say … then why are you excoriating my ideas on the question?
Nor is it inherently a complex question. The question is, should temperatures more than a thousand km away from Darwin be used to arbitrarily adjust Darwin’s temperature by a huge amount? You don’t have to be a rocket scientist to figure that out.
Next, as an aside you make the scurrilously false statement that I said that claims of damage due to sea level rise in Tuvalu “stemmed from attempts by locals to blame subsidence problems on the developed world, and cash in on it”. I said no such thing nor do I believe it. The claims stemmed from misguided environmentalists.
Next, you say “He makes it sound as if he’s just happened to stumble across this one site whilst perusing a debate over climate change in northern Australia. But as his link to that conversation from 2000 makes clear, Mr Eschenbach is already aware that climate change denialists have been trumpeting the apparent anomalies at Darwin for nine years.” BZZZZT, poor understanding of the implications of chronology. I looked up the conversation after I stumbled across Darwin. How dare you accuse me of lying? As I said, I went to AIS to see if what Professor Karlen had said was true. I called up a list of all of the stations in Australia that covered 1900-2000. Darwin was the first on the list, so that’s the one I looked at. Try it and see. You accusation is both wrong and totally unfounded.
“[Climate change denialists] do so because of that errant data at Darwin from before 1941, which makes it look as though there was a cooling trend there. The fact that climate-change researchers have to do a particularly strong correction on the data at Darwin, because they moved their dang instruments from the downtown post office to the airport, makes Darwin a perfect place to look for support if you want to claim that climate-change scientists are cooking the data.”
While a correction in Darwin is perhaps necessary, it is cannot be because they “moved their dang instruments” in January of 1941. LOOK AT THE DATA. There is no big change in January of 1941. It occurred gradually over the previous five years. So your theory falls apart upon the simplest examination of the facts.
Next you say: “Average guys with websites can do a lot of amazing things. One thing they cannot do is reveal statistical manipulation in climate-change studies that require a PhD in a related field to understand.”
Your understanding of statistics is as poor as your understanding of chronology. The statistics used by GHCN are average college level tools. You are dazzled by the fact that you don’t understand them, so you make the incredibly foolish assumption that no one without “a PhD in a related field” can understand them either. Some of us actually paid attention in class, you know.
Finally, you use your closing arguments to cheerlead for peer review. Curiously, I agree with you in theory … but the peer review system in climate science is badly broken. First, as the CRU emails clearly show, it has been subjected to enormous “old-boy” pressures to pass through bad studies without a second glance, and to deny opposing papers a fair hearing. How do you think we got the Hockeystick and its cousins? Here’s Phil Jones from the emails, talking about keeping peer-reviewed papers out of the IPCC report:
I can’t see either of these papers being in the next IPCC report. Kevin and I will keep them out somehow – even if we have to redefine what the peer-review literature is!
And you give your article the URL “trust_scientists”???
Second, the peer-review system is ripe for abuse. This is because the reviewers often know who the author is, while the reviewers (like you) hide in anonymity. This invites malfeasance. The system needs to be changed so that after the review, the [authors] sign their names to the paper as well as reviewers. At present, we have no way of knowing whether the paper was seriously reviewed by inquiring scientists, or simply passed through by the authors friends.
So I, like you, support peer review. I just want a peer review system that works. It must be double blind during the review period, with neither the reviewers nor the author knowing the others’ names. And the reviewers should reveal their names at the end, so that we know it wasn’t just the author’s best mates doing the author a favor.
Since we have an easily manipulated system instead of a real peer review system, I opt for public peer review by putting my work on the web. This lets anyone, even anonymous innumerates like yourself, register your objections.
Finally, the Economist did not contact me before publishing an article full of false accusations, incorrect assumptions and wrong statements … looks like peer review is not the only system in trouble here. I thought journalists were under an obligation to check their facts before making accusations …
Willis Eschenbach
Why the mean anyway? Why not study the trend in the mode? Since you have a range large enough to go from freezing to scorching, why not simply study the trend in the mode? Makes sense in my head, is there a good reason not to do this?
Just did a major scan of all MSM in NA and ma finding very little prominent stories on Cope 15. Ant theories on this lack of coverage of what is supposed to be a major conference? Maybe I am missing something?
http://en.wikipedia.org/wiki/File:MonthlyMeanT.gif
Note how insanely bitterly cold the Antarctic is, yet the oceans play damper well during the SH winter. During the NH winter, the landmasses in the NH bear the brunt of absorbing the cold. This shows that atmospheric physics play a smaller than believed role in the climatic processes of Earth. The oceans are a very effective damper on temperature. This is because the oceans radiate heat much more slowly than the landmasses.
So, I really think that analyzing Tmax/Tmin would be helpful to debunking AGW. It seems that the time of day when energy escapes the system would be the more important way to look into the problem. Unfortunately, I believe that the best way to analyze this would be to take an entire years worth of data in a desert scenario, where there is very little water vapor, and track the hourly temperature to note the daily energy absorption and energy release phases. This should also be compared to jungle settings where the water vapor plays a dominant role. The changes have to happen on a daily basis because the system fluctuates between absorb and release on a daily basis. If radiative physics are the crux of CO2 causing global warming, then you have to observe each process to note what is different, right? This stuff about averaging Earth’s wildly variable temperature is nonsense as far as proving anything goes.
Why not study the absorption/release rates? Energy (temperature as a proxy here) should release more slowly and absorb more quickly if CO2 is preventing radiation from escaping, right? Why not study that for the so-called fingerprint? I am confused as to the general methodology, I guess. I don’t understand how averaging temperature over tons of different actual physical differences (jungles and plateaus of Tibet for starters) can be at all helpful. Why hasn’t this been done yet?
Sorry, I meant to delete ‘an entire’ in front of ‘an entire years’. I mean that it would take loads of actual hourly observations, noting all circumstances relevant to radiative forcing, to really determine whether or not radiative forcing plays an integral part in climate fluctuation. I may be wrong, but I would like to know how.
Ot but is it possible that SH compensates for NH iceand vice-versa? look at this
http://en.wikipedia.org/wiki/File:MonthlyMeanT.gif
re previous SH v NH Ice (should have added temps as well sorry). I have observed this time map (days)
http://www.esrl.noaa.gov/psd/map/images/fnl/sfctmpmer_01a.fnl.anim.html
regularly and have noticed that invariably/repeatedly, when “cold in SH pole”, “Hot in NH pole” then a flip/flop occurs “Hot in SH Pole and Cold in NH Pole”. Anyone noticed as well?. Probably described already.. Is this a mechanism of earth temp control to within ~14oC?
VG (22:40:41) :
I posted that link because it illustrates the silliness of averaging temperature. The Tibetan plateau is a great example. Note when it goes blue. What I think that illustrates is Milankovitch cycles and the tendency of water to damp temperature changes drastically. Notice that because the SH is mostly water, Antarctica is bitterly cold in the winter, but the Arctic is not. This is because of the landmass on the South Pole. There is no land mass on the North, but the landmasses in the NH lose their temperature much further south in the winter. I felt this illustrates how 1) it is silly to average temperature that includes SSTs and 2) that average temperature is essentially meaningless when you consider that temperature changes based on physical properties of the point in question. How can you add it all together without accounting for the physical differences of any given point?
Da Capo:
. Is there a meaning to temperature measurements and predictions?
Absolutely yes for the locality. From airport conditions to planting conditions to dressing conditions, our lives improve by knowing the temperature,wind, humidity etc, and the predictions for the locality. When I go to my vacation cottage I do not look at the weather in New York, but at Corinth, Greecce.
. Is there a meaning in trends of temperature?
Yes. Except they are not reliable for more than a few days presently. Almanacs (distilled folk wisdom from previous experiences?) have a use though, and farmers seem to rely on them.
. Is there a meaning in averaging all temperature trends globally and projecting for a century?
A qualitative, yes. Qualitative because we do not know the underlying physics/mathematics/statistics to the detail needed for a rigorous summing and averaging to get one number. Qualitative also because the meaning is fuzzy: it might tell us that a little ice age is arriving , it might tell us a medieval maximum is coming, but not more.
There is no way to get from these numbers watts/meter^2 in a one to one fashion with reasonable errors. The equations needed are an enormous number and depend on constants that have not been measured, like the gray body constants that differ in microlocalities and make the microclimate , the wind turbulances, the evaporation sublimation, photsynthesis water use etc.etc. . This makes the problem intractable by even envisaged computer power for the future.
What the GCMs do is whitewash over the physics problems with approximations and assumptions that cannot hold water in a rigorous physics/statistics/mathematics analysis. This is evident from the weather predictions, that are given by programs with similar mathematics/assumptions/logic. The predictions fail after a few days.
At best, GCMs are models of an ideal world with ideal black body behavior that allows them to connect temperatures to watts/meter^2. This cannot apply to the real world, to the accuracy of 1watt/meter^2 that is claimed to boot. It is a video game after a few iterations.
In this whole mess how can the CO2 contribution be untangled except with handwaving by using the GCM virtual world as if it represents the real world? And the western world is asked to commit hara kiri on the basis of these video games.
This is an inherent problem that cannot be overcome with more computing power, as others have analyzed. The system is chaotic, it has deterministic equations but they have to be applied in too many three dimensional and fractal ( think of forests, think of craggy mountains, wavy oceans) localities and times to be able to process in a digital computer.
The only future for climate modeling lies in chaos and complexity techniques, which is a vigorous new field in all sciences growing by leaps and bounds. Tsonis et al have made a start, but it is only a start.
Nick Stokes (14:16:26) :
Tenuc (13:42:05) :
Great piece of work, Willis, and now at last it seems we’re getting down to the nuts and bolts of why CRU/GISS/IPCC took great pains to stop access to the raw data. This deception has been exposed in all it’s despicable glory.
This is totally muddled. Willis has queried GHCN adjustments to Darwin’s raw data (which have been available for years). CRU and GISS have published their data for Darwin, and it shows no significant adjustment to the raw GHCN data that Willis used. The IPCC used CRU data, not GHCN adjusted.
Nick part of the issue, if your read CRU responses to our FOI, was that they didnt have to make their data public because IT WAS ALREADY AT GHCN!
except for the bit held under confidentiality agreements.
At some point in this whole MESS, somebody needs to draw a diagram of what data goes into what index, what is raw what is adjusted.
For example GISS say they use USHCN raw, but raw means after USHCN adjustments.
At least with GISS I can look at the CODE, I can see what data file they ingest and I can then hunt that puppy down. Sadly with CRU we dont have that yet
In the end, when its all in the Open, these issues will become easier to sort out.
David thanks for explanation on SH NH Ice etc… The point in general too is I think that no one here is/was particularly interested in denying AGW. I certainly believed it when I saw the old hadcrut graphs on wikipedia etc..> After looking into it more carefully ie Svensmarks theory, SM analysis on tree ring data ect we started to look into and looking even at the cooked data it does not stand up. This affair climategate has now confirmed it further. I think this will sink in to the majority of people and scientists as they realize that since their childhood the climate has not changed.
More on Halls Creek.
Mean minimums
http://members.westnet.com.au/rippersc/hallsmin.jpg
Data from
http://www.bom.gov.au/cgi-bin/climate/hqsites/site_data.cgi?variable=minT&area=wa&station=002012&period=annual&dtype=raw&ave_yr=T
http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_display_type=dataGraph&p_stn_num=002011&p_nccObsCode=38&p_month=13
http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_display_type=dataGraph&p_stn_num=002012&p_nccObsCode=38&p_month=13
And the mean temperature and net adjustments
http://members.westnet.com.au/rippersc/hallsmean.jpg
I think that illustrates the problems trying to homoginise two stations with 62 metres difference in elevation and 12 odd km apart..
Take two flat trends and end up with a warming trend and manage to get rid of the 1940 blip as well.
I start to think that this kind of blog science is actually destructive. My guess is that a year from now hundreds of posts have been produced alluding fraud and incompetence, thousands of cheering comments have been written praising the free thinking scientist at WUWT, but in the end the sum of the nitpicks (some legit and some not) will probably have an impact on the global trend that is a full order of magnitude less than the decadal trends in the official record, that is, instead of being a nail in the coffin for the official record it will be an affirmation of the robustness of the official record. The problem is that no one will take a step back and contemplate this fact. The lasting impression will be that climate scientist are all frauds while the actual results of the blogposts add up to confirm the exact opposite. It’s kind of absurd and in my opinion destructive.
@ur momisugly Fredrik
“The lasting impression will be that climate scientist are all frauds…”
No, you’ve missed the point. It’s not about the scientists as much as it is about the science. Most people here want the raw data, the adjustments made to that raw data, the reasoning behind those adjustments and the computer code making those adjustments.
If those requests are not met with, then of course there will be the accusation of fraud. Because there cannot be any other reason for withholding it. And if they continue to withhold, of course people are going on a quest to prove the fraud. It’s logical.
So the destructiveness that you notice is a direct consequence of the continued withholding of data and methods. And to be honest, anyone claiming to be a scientist who withholds data and or methods is not a scientist in my book, hence worthy of being destroyed. (not literally of course. let’s not resort to ‘Santer-ising’)
steven mosher (23:49:41) :
I think if you look back at the FOI requests CRU very early on said that the free data was already available at GISS / GHCN. It’s just that no one believed them
Fredrik (01:06:15),
Then what is your suggestion? What should we do?
If you haven’t noticed, things are improving. The very last thing these crooked CRU climatologists want to do is explain. Slowly but surely, they’re being forced to start explaining.
It’s entertaining to hear them try to explain that the emails were ‘taken out of context’. Here’s one example [out of many] of an email from Harry_read_me:
“The 1990 – 2003 period is missing… what the hell is supposed to happen here? Oh yeah – there is no ‘supposed’, I can make it up. So I have.”
That is an admission of thirteen years of fabricated data. And that’s not all.
There are over a thousand emails, plus plenty of code comments and code showing they did ‘make it up’. They fabricated the record to show artificial warming. That has caused others to look at the record of rural stations unaffected by UHI, which show little to no warming.
The entire mainstream media is run by people who have a Leftist bias. They would prefer to never mention climategate again, but the very obvious fraud involved is forcing them to begin to cover it. They will print and broadcast one-sided propaganda when they can, but their bottom line is too important: if they don’t cover the story, their competition will — and the public is beginning to wake up and demand answers. When they see that the CRU data was fabricated, and that data is being used as the pretext to jack up everyone’s taxes, they will tune in to the news programs and papers that report the story.
The same thing happened in Watergate. At first, it was dismissed as “a third rate burglary attempt.” No major papers wanted to connect the dots, because President Nixon had just been re-elected by a huge majority. But eventually they had to cover the story. Best sellers appeared, like All the President’s Men. Watergate was lucrative for lots of people, and it brought down the President.
The same thing happened in the Monica Lewinsky story. President Clinton had just been re-elected, and who cared about rumors of his philandering? But then Drudge was tipped off about the blue dress, and Clinton’s carefully constructed edifice started to crumble, until the President was finally impeached.
You are correct in saying that this will taint honest scientists; the ones who don’t get million dollar
grantsbribes to ‘study global warming’, and who aren’t accorded rock star status in return for lying about the global warming edifice they have constructed out of their fictional climate data. As you say, that is destructive: honest scientists in other fields have already started to speak out. More will follow. Because their fields have been starved by the $Billions that have been diverted to ‘study global warming’.The CRU emails are the 2009 version of Monica’s blue dress: proof that a relatively small clique of climate scientists, who wield enormous influence over the mainstream climate peer review process, are corrupt. And the U.S. ringleader of the Hockey Team is a 30-something upstart who is arrogant and steps on a lot of toes. Surely other scientists with sore toes won’t mind the opportunity to give a little payback.
When Clinton tried to explain Lewinsky’s accusations, he looked into the camera and said, “I did not have sex with that woman, Miss Lewinski… never, not a single time… and I never asked anyone to lie… .” That’s the stage we’re at now with Michael Mann, Phil Jones and some others. Climategate will play out more or less according to the same pattern. Human nature doesn’t change, and some enterprising reporter will get one of the players to spill the beans. Matt Drudge was a nobody before he scooped every major newspaper on Monicagate. Now he’s rich and famous.
The first reporter who gets a solid, revealing interview from one of the Team will get a big payoff, and so will the paper that prints it. Scooping the competition on a really big story like this, involving $Trillions and self-serving countries and politicians around the world is the dream of every reporter. Especially at a time when newspapers desperately need new readers. And if the mainstream media won’t report it, others will. Bishop Hill is already working on a book exposing the fraud. And the market will be hungry for more climategate tell-all books.
If you think this “blog science” is destructive, ask yourself: who is going to be destroyed? And who will turn state’s evidence? As Will S said, all the world’s a stage, and each must play his part.
Its seems that CA has shut down…or hes sleeping… We are all watching as it unfolds….No need for more auditing its (AGW) collapsing on its own…
Analysis of Some California Stations Adjustments – Forcing the fit
What I did:
• Went to GISS
• Picked out 10 Mid Northern California Stations &
Reno, Nevada. All had 100+ year records.
• Had GISS output the station data as text and
copied to Excel
• Used Data->Text to Columns Menu to convert.
• Did this for Raw and Homogenized data for each
station.
What I did #2
• Calculated the adjustment for each station to
homogenize for annual averages.
• Realized it appeared to be very manual, systematic and
in .10 of degree increments.
• Tested and confirmed it was the same adjustment for
monthly as for yearly.
• Noticed it was wildly different for each station, but the
dates and changes were not at all consistent to NCDC
station change histories. So this was excluded as the
reasons.
• The changes in the cities were not consistent with
discounting a Urban Heat Island effect, in fact most were
opposite with earlier data being changed more and
recent data changed less.
What I did #3
• Plotted for each station:
– Raw data
– Homogenized Data
– Adjustments made to homogenize
• Some adjustments were positive, some were negative, some were
big, some where small. There was no obvious formula or logic.
• They were not hiding a decline as some stations were up long term,
some were down.
• Some stations they enhanced a warming trend, other stations they
reduced it.
• What were they trying to do? The changes in all case were modest
incremental steps over time, just very different for each city.
• I played with plotting various averages
What I saw #1
• The San Francisco chart really had me perplexed. The raw data showed a strong
warming trend and they were seemingly reducing it significantly. Not for Urban Heat
Island, because they were increasing the past, not decreasing the present. Again, the
changes to the temps moderated over time and varied from early positive
adjustments to recent negative adjustments, to very recent positive adjustments.
• Then I realized what the adjustments were doing…..
• They were forcing all stations to conform to a similar curve…..and that curve told the
story they wanted to tell.
• I can’t yet figure out the exact formula used, but I’m getting close with a 6 order
polynomial fit from excel. The left scale is annual temp average
– The right scale is the homogenizing temp adjustment
– The raw and homogenized temps are plotted
– The curves are an Excel 6 order polynomial trend line
– The GREEN curve is the resulting polynomial trend after homogenizing.
• See what you think.
NOTE: I can’t upload the graphs to this comment thread..Anthony let me know how and I will. They really show what “homogenization” means in practice at least here in the US.
What I saw #2
• The story of the curve they seem to be forcing all stations to is:
– The 30s were warm, but not as warm as today.
– The past was more stable, the 90s climb is steeper and unusual
– There is a consensus story amongst the stations, rural or city.
• The raw data does not support their story, the “homogenized” does.
– If GISS releases the reasons for every single adjustment, there could be
other explanations.
– Adherence to the scientific method demands an explanation.
– Otherwise, Ocam’s Razor suggests this was done to force all reviewed
stations to a similar set of characteristics over time regardless of the raw
data.
• There is a trend to zero adjustment in the late 90s, early 2000s for
all cities. It is the past that is being adjusted making the current first
and second order temperature trends in comparison be interpreted
differently.
Anthony, This chart is what liberals are using to say “the science is settled”.
Someone needs to construct a similar graph that represents the unmanipulated change in temperatures.
http://krugman.blogs.nytimes.com/2009/12/09/a-picture-thats-worth-a-thousand-stolen-emails/
“The lasting impression will be that climate scientist are all frauds”: although not the end I hope for, it would certainly be one acceptable solution to this manufactured crisis. The people who have hidden the data and squashed all criticism have only themselves to thank if this happens.
Anything that serves to destroy the justification for further government action is a consummation devoutly to be wished.
You need a sticky for the one by the sixth-grader, too, just in case any talking heads or info-babes do a drive by of this site. It’s probably still way over their heads, but they might be able to get something out of it.
Do none of you get the hypocrisy of criticizing the RAW data for siting errors while simultaneously saying that adjusting for those errors constitutes fraud? Probably not, because there is so much hypocrisy inherent in climate skepticism. I’ve listed 11 ways here:
http://akwag.blogspot.com/2009/12/climate-of-hypocrisy.html
Also, Tim Lambert has done an excellent job of pointing out the problems in Willis’s “analysis” here:
http://scienceblogs.com/deltoid/2009/12/willis_eschenbach_caught_lying.php
Great work Anthony. I’m seeing links to your research all over the web.
I’m also noticing folk talking more about CO2’s effect on ‘Ocean Acidification’, shifting the pH down from around 8.2. Lots of discussion on effects on plankton, shellfish, food chain, etc. My intitial research seems to indicate that ocean pH was probably about the same as many years ago when CO2 concentrations were much higher.
The key concern seems to be (relatively) big pH changes in the last 30 years (naturally, caused by man-made CO2) that may not allow sea life to adapt quickly enough. I get that life ALWAYS adapts, but perhaps not a great idea if we lose a big chunk of our food supply in the transition period.
As always, I’m skeptical of big headline threats and would appreciate if anyone could point me in the direction of the scientific equivalent of ‘non-homogenised’ ocean CO2 research.
I believe this is a reasonable explanation
http://scienceblogs.com/deltoid/2009/12/willis_eschenbach_caught_lying.php
Anybody care to comment?
WAG (07:48:36) :
“Do none of you get the hypocrisy of criticizing the RAW data for siting errors while simultaneously saying that adjusting for those errors constitutes fraud?”
Unlike WAG, I understand the meaning of conflate.
The siting issue is completely different from the raw data issue.
WAG,
Good engineering demands independent verification of the details. When I did my check of 10 california stations such as others did for Australia, there were no adjustments made when the sites had documented changes. Such changes would be warranted. There was zero correlation.
The 6th grader’s work on UHI states the obvious that IPCC seems to deny.
The adjustments in CA, like in Australia were very stepwise and incremental over time. They defy any common sense for UHI or any other known effect.
Siting change adjustments would be one time events. What I saw was clearly curve shaping where the raw data of all 10 stations were being reshaped to fit a model curve.
You don’t change the data to fit your model, you go back to find out why your model is broken. Scientists publishing papers may get away with this for a while. Engineers that must build stuff that actually works quickly lose their jobs.
A detailed review and criticism is standard procedure. If they can justify all these adjustments in Darwin, CA, Nordic, Alaska, and otherwise, then they should. In detail.
Hand waving and generalities don’t cut it when we want to reengineer the world economy. I’ll be green without being extreme..