RSS Flat For 200 Months (Now Includes July Data)

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

[NOTE: RSS is a satellite temperature data set much like the UAH dataset from Dr. Roy Spencer and John Christy – Anthony]

Image Credit: WoodForTrees.org

Guest Post By Werner Brozek, Edited By Just The Facts

The graphic above shows 3 lines. The long line shows that RSS has been flat from December 1996 to July 2013, which is a period of 16 years and 8 months or 200 months. The other slightly higher flat line in the middle is the latest complete decade of 120 months from January 2001 to December 2010. The other slightly downward sloping line is the latest 120 months prior from present. It very clearly shows it has been cooling lately, however this cooling is not statistically significant.
In my opinion, if you want to find out what the temperatures are doing over the last 10 or 16 years on any data set, you should find the slope of the line for the years in question. However some people insist on saying global warming is accelerating by comparing the decade from 2001 to 2010 to the previous decade. They conveniently ignore what has happened since January 2011. However, when one compares the average anomaly from January 2011 to the present with the average anomaly from January 2001 to December 2010, the latest quarter decade has the lower number on all six data sets that I have been discussing. Global warming is not even decelerating. In fact, on all six data sets, cooling is actually taking place.

The numbers for RSS for example are as follows: From January 2001 to December 2010, the average anomaly was 0.265. For the last 31 months from January 2011 to July 2013, the average anomaly is 0.184. The difference between these is -0.081. I realize that it is only for a short time, but it is long enough that there is no way that RSS, for example, will show a positive difference before the end of the year. In order for that to happen, we can use the numbers indicated to calculate what is required. Our equation would be (0.184)(31) + 5x = (0.265)(36). Solving for x gives 0.767. This is close to the highest anomaly ever recorded on RSS, which is 0.857 from April 1998. With the present ENSO conditions, there is no way that will happen.

A word to the wise: do not even mention accelerated global warming until the difference is positive on all data sets.

I have added rows 23 to 25 to the table in Section 3 with the intention of updating it with every post. This table shows the numbers that I have given for RSS above as well as the corresponding numbers on the other five data sets I have been discussing. Do you feel this would be a valuable addition to my posts?

(Note: If you read my last article and just wish to know what is new with the July data, you will find the most important new things from lines 7 to the end of the table.)

Below we will present you with the latest fact, 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 several data sets. 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 2013 to date compares with 2012 and the warmest years and months on record so far. 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. 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.
On all data sets below, the different times for a slope that is at least very slightly negative ranges from 8 years and 7 months to 16 years and 8 months.
1. For GISS, the slope is flat since February 2001 or 12 years, 6 months. (goes to July)
2. For Hadcrut3, the slope is flat since April 1997 or 16 years, 4 months. (goes to July)
3. For a combination of GISS, Hadcrut3, UAH and RSS, the slope is flat since December 2000 or 12 years, 8 months. (goes to July)
4. For Hadcrut4, the slope is flat since December 2000 or 12 years, 8 months. (goes to July)
5. For Hadsst2, the slope is flat since March 1997 or 16 years, 4 months. (goes to June) (The July anomaly is out, but it is not on WFT yet.)
6. For UAH, the slope is flat since January 2005 or 8 years, 7 months. (goes to July using version 5.5)
7. For RSS, the slope is flat since December 1996 or 16 years and 8 months. (goes to July) RSS is 200/204 or 98% of the way to Ben Santer’s 17 years.
The next link shows just the lines to illustrate the above for what can be shown. 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 sloped wiggly line shows how CO2 has 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. It goes from 0.1 C to 0.6 C. A change of 0.5 C over 16 years is about 3.0 C over 100 years. And 3.0 C is about the average of what the IPCC says may be the temperature increase by 2100.

So for this to be the case, the slope for all of the data sets would have to be as steep as the CO2 slope. Hopefully the graphs show that this is totally untenable.

The next graph shows the above, but this time, the actual plotted points are shown along with the slope lines and the CO2 is omitted.

Trend1B

Source: WoodForTrees – Paul Clark – click to view at source

Section 2

For this analysis, data was retrieved from SkepticalScience.com. This analysis indicates for how long there has not been statistically significant warming according to their criteria. The numbers below start from January of the year indicated. Data go to their latest update for each set. In every case, note that the magnitude of the second number is larger than the first number so a slope of 0 cannot be ruled out. (To the best of my knowledge, SkS uses the same criteria that Phil Jones uses to determine statistical significance.)

The situation with GISS, which used to have no statistically significant warming for 17 years, has now been changed with new data. GISS now has over 18 years of no statistically significant warming. As a result, we can now say the following: On six different data sets, there has been no statistically significant warming for between 18 and 23 years.

The details are below and are based on the SkS Temperature Trend Calculator:

For RSS the warming is not statistically significant for over 23 years.
For RSS: +0.120 +/-0.129 C/decade at the two sigma level from 1990
For UAH the warming is not statistically significant for over 19 years.
For UAH: 0.141 +/- 0.163 C/decade at the two sigma level from 1994
For Hadcrut3 the warming is not statistically significant for over 19 years.
For Hadcrut3: 0.091 +/- 0.110 C/decade at the two sigma level from 1994
For Hadcrut4 the warming is not statistically significant for over 18 years.
For Hadcrut4: 0.092 +/- 0.106 C/decade at the two sigma level from 1995
For GISS the warming is not statistically significant for over 18 years.
For GISS: 0.104 +/- 0.106 C/decade at the two sigma level from 1995
For NOAA the warming is not statistically significant for over 18 years.
For NOAA: 0.085 +/- 0.102 C/decade at the two sigma level from 1995

If you want to know the times to the nearest month that the warming is not statistically significant for each set to their latest update, they are as follows:
RSS since August 1989;
UAH since June 1993;
Hadcrut3 since August 1993;
Hadcrut4 since July 1994;
GISS since January 1995 and
NOAA since June 1994.

Section 3

This section shows data about 2013 and other information in the form of a table. The table shows the six data sources along the top and bottom, namely UAH, RSS, Hadcrut4, Hadcrut3, Hadsst2, and GISS. Down the column, are the following:
1. 12ra: This is the final ranking for 2012 on each data set.
2. 12a: Here I give the average anomaly for 2012.
3. year: This indicates the warmest year on record so far for that particular data set. Note that two of the data sets have 2010 as the warmest year and four have 1998 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 two 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.
8. sig: This is the whole number of years for which warming is not statistically significant according to the SkS criteria. The additional months are not added here, however for more details, see Section 2.
9. Jan: This is the January, 2013, anomaly for that particular data set.
10. Feb: This is the February, 2013, anomaly for that particular data set, etc.
21. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months. However if the data set itself gives that average, I may use their number. Sometimes the number in the third decimal place differs by one, presumably due to all months not having the same number of days.
22. rnk: This is the rank that each particular data set would have if the anomaly above were to remain that way for the rest of the year. Of course it won’t, but think of it as an update 30 or 35 minutes into a game. Due to different base periods, the rank may be more meaningful than the average anomaly.
23.new: This gives the average anomaly of the last 31 months on the six data sets I have been discussing, namely from January 2011 to the latest number available.
24.old: This gives the average anomaly of the 120 months before that on the six data sets I have been discussing. The time goes from January 2001 to December 2010.
25.dif: This gives the difference between these two numbers.
Note that in every single case, the difference is negative. In other words, from the previous decade to this present one, global warming is NOT accelerating. As a matter of fact, cooling is taking place.

Source UAH RSS Had4 Had3 Sst2 GISS
1. 12ra 9th 11th 9th 10th 8th 9th
2. 12a 0.161 0.192 0.448 0.406 0.342 0.57
3. year 1998 1998 2010 1998 1998 2010
4. ano 0.419 0.55 0.547 0.548 0.451 0.66
5. mon Ap98 Ap98 Ja07 Fe98 Au98 Ja07
6. ano 0.66 0.857 0.829 0.756 0.555 0.93
7. y/m 8/7 16/8 12/8 16/4 16/4 12/6
8. sig 19 23 18 19 18
Source UAH RSS Had4 Had3 Sst2 GISS
9. Jan 0.504 0.441 0.450 0.390 0.283 0.63
10.Feb 0.175 0.194 0.479 0.424 0.308 0.50
11.Mar 0.183 0.205 0.405 0.384 0.278 0.58
12.Apr 0.103 0.219 0.427 0.400 0.354 0.48
13.May 0.077 0.139 0.498 0.472 0.377 0.56
14.Jun 0.269 0.291 0.451 0.426 0.304 0.66
15.Jul 0.118 0.222 0.514 0.490 0.468 0.54
Source UAH RSS Had4 Had3 Sst2 GISS
21.ave 0.204 0.244 0.459 0.427 0.339 0.564
22.rnk 6th 8th 9th 8th 10th 10th
23.new 0.158 0.184 0.436 0.385 0.314 0.562
24.old 0.187 0.265 0.483 0.435 0.352 0.591
25.dif -.029 -.081 -.047 -.050 -.038 -.029

If you wish to verify all of the latest anomalies, go to the following links, For UAH, version 5.5 was used since that is what WFT used,, RSS, Hadcrut4, Hadcrut3, Hadsst2,and GISS.

To see all points since January 2012 in the form of a graph, see the WFT graph below.

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

Appendix

In this section, we summarize the data for each set separately.

RSS

The slope is flat since December 1996 or 16 years and 7 months. (goes to June) RSS is 199/204 or 97.5% of the way to Ben Santer’s 17 years.
For RSS the warming is not statistically significant for over 23 years.
For RSS: +0.122 +/-0.131 C/decade at the two sigma level from 1990.
The RSS average anomaly so far for 2013 is 0.248. This would rank 7th if it stayed this way. 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 2012 was 0.192 and it came in 11th.
Following are two graphs via WFT. Both show all plotted points for RSS since 1990. Then two lines are shown on the first graph. The first upward sloping line is the line from where warming is not statistically significant according to the SkS site criteria. The second straight line shows the point from where the slope is flat.
The second graph shows the above, but in addition, there are two extra lines. These show the upper and lower lines using the SkS site criteria. Note that the lower line is almost horizontal but slopes slightly downward. This indicates that there is a slight chance that cooling has occurred since 1990 according to RSS.
Graph 1 and graph 2.

UAH

The slope is flat since July 2008 or 5 years, 0 months. (goes to June)
For UAH, the warming is not statistically significant for over 19 years.
For UAH: 0.139 +/- 0.165 C/decade at the two sigma level from 1994
The UAH average anomaly so far for 2013 is 0.219. This would rank 4th if it stayed this way. 1998 was the warmest at 0.419. The highest ever monthly anomaly was in April of 1998 when it reached 0.66. The anomaly in 2012 was 0.161 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to UAH.
Graph 1 and Graph 2.

Hadcrut4

The slope is flat since November 2000 or 12 years, 7 months. (goes to May.)
For Hadcrut4, the warming is not statistically significant for over 18 years.
For Hadcrut4: 0.093 +/- 0.107 C/decade at the two sigma level from 1995
The Hadcrut4 average anomaly so far for 2013 is 0.450. This would rank 9th if it stayed this way. 2010 was the warmest at 0.547. The highest ever monthly anomaly was in January of 2007 when it reached 0.829. The anomaly in 2012 was 0.448 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut4.
Graph 1 and Graph 2.

Hadcrut3

The slope is flat since April 1997 or 16 years, 2 months (goes to May, 2013)
For Hadcrut3, the warming is not statistically significant for over 19 years.
For Hadcrut3: 0.091 +/- 0.110 C/decade at the two sigma level from 1994
The Hadcrut3 average anomaly so far for 2013 is 0.414. This would rank 9th if it stayed this way. 1998 was the warmest at 0.548. The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to go back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2012 was 0.405 and it came in 10th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut3.
Graph 1 and Graph 2

Hadsst2

For Hadsst2, the slope is flat since March 1, 1997 or 16 years, 2 months. (goes to April 30, 2013).
The Hadsst2 average anomaly for the first four months for 2013 is 0.306. This would rank 11th if it stayed this way. 1998 was the warmest at 0.451. The highest ever monthly anomaly was in August of 1998 when it reached 0.555. The anomaly in 2012 was 0.342 and it came in 8th.
Sorry! The only graph available for Hadsst2 is this.

GISS

The slope is flat since February 2001 or 12 years, 5 months. (goes to June)
For GISS, the warming is not statistically significant for over 18 years.
For GISS: 0.105 +/- 0.110 C/decade at the two sigma level from 1995
The GISS average anomaly so far for 2013 is 0.57. This would rank 9th if it stayed this way. 2010 was the warmest at 0.66. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2012 was 0.56 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to GISS. Graph 1 and Graph 2

Conclusion

So far in 2013, there is no evidence that the pause in global warming has ended. As well, all indications are that RSS will reach Santer’s 17 years in three or four months. The average rank so far is 8.5 on the six data sets discussed here. ENSO has been neutral all year so far and shows no signs of changing. The sun has been in a slump all year and also shows no sign of changing. As far as polar ice is concerned, the area that the north is losing is close to what the south is gaining. So the net effect is that there is little overall change and this also shows no sign of changing.

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200 thoughts on “RSS Flat For 200 Months (Now Includes July Data)

  1. Sorry for going OT here but I have a question. Does anybody know the global average SST vs the global average air temperature over the oceans? If the former is lower, how can heat transfer (net) from atmosphere to ocean?

  2. Intesting overview.

    May be more appropriate to show log CO2 (probably not possible in the challenged limitations of WTF website) , also why the offset?

  3. So for this to be the case, the slope for all of the data sets would have to be as steep as the CO2 slope. Hopefully the graphs show that this is totally untenable.

    No, this is not the case. For so very many reasons it is difficult to cover them all. First of all, you are comparing apples to oranges when you compare anomaly slopes. Second of all, there is obviously a constant (needed just to change the UNITS!) between the two quantities, and the value of this constant determines the comparative steepness of slope. Third, the problem with this SORT of analysis is that one cannot separate out the “natural climate variation” and the “CO_2 caused climate variation” and the “feedback caused climate variation” and the “anthropogenic but also warming or cooling or both factors” such as aerosols and soot and the “influence of water vapor” — so asserting a simple linear dependence of one on another either way is absurd. CAGW could easily be correct and the current flat trend is natural noise that will eventually be overwhelmed by the CO_2 forced signal, or CAGW could easily be incorrect, and the current flat trend is mostly natural and UNDERWHELMED by any CO_2 forced signal. Or any of a slew of other alternatives.

    The best conclusion one can draw from the curves you present above is “this data does not support the assertion that the increase in CO_2 over the last 16 years has caused additional warming”. That’s all that the data really means, and all it will ever mean until we can reliably separate causal components contributing to the climate that probably cannot be separated in a complex nonlinear system.

    rgb

  4. Yes, your normalised CO2 is pretty meaningless and hence misleading. How about you normalise the temps too ? ;)

    If you plot the log of CO2 conc over the same period it’s probably almost as flat, though technically non-zero.

  5. Leif,
    the RSS trend 2001-2013 is – 0.08. Probably not a big deal (no new Ice Age in sight), but cooling nevertheless.

  6. Woodfortrees is being abused by overanalysis by “chartists” playing with their PCs.
    The criteria for statistical significance is vastly abused. It amounts to looking at an elephant with an electron microscope.
    Northern hemisphere glaciers began melting naturally before 1800.
    Satellite radiometers show no significant warming since 1979. An anomaly of 0.2 degrees is not significant.
    Rejecting UHI contaminated surface temps leaves a few good surface station data.
    The remaining good data show show zero waming. eg Antarctica.
    The long term temp trend is visible when looking at longer term temp data.
    Using Best data with satellite data added to show the UHI contaminated data since 1980.

    http://www.woodfortrees.org/plot/best/scale:1/plot/rss-land

  7. I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?

  8. The half way trends are a good idea.

    There may be no overall warming but there sure is a change from warming to cooling centred on 2005, which Willis pointed out some time ago appears to be a ‘regime change’.

    A change from +ve to -ve slope is also called a decelleration.

  9. GISS flat for 294 months, eh?

    That’s what you get for artificially increasing your temperatures to make things look more dangerous. But, of course, Hansen does have an answer.

    If he simply confesses to a few of his little tricks and lowers the temperatures over the last three years, he will magically have a rising graph again. I wonder if he’ll do that?

  10. Ivan says:
    August 25, 2013 at 10:32 am
    the RSS trend 2001-2013 is – 0.08. Probably not a big deal (no new Ice Age in sight), but cooling nevertheless.
    -0.08 is not statistically different from zero or even +0.08 for that matter.

  11. I do like the subtle poking of fun at Michael Mann with the upside down grapth you show. It’s OK to turn a graph with a flat line upside down. The result is the same. Unlike Mann’s Tiljander effort.

  12. @Greg: Actually, the log of CO2 for 1996-2013, increased 25% faster than for 1980-1996. WFT can’t calculate such things, but you can click on the link to download the data and do it yourself.

  13. So, the heat is still busy hiding in the depths of the oceans and/or hopscotching around the globe, playing hide-and-seek. C02 heat is tricky that way.

  14. This can not be. Did not Obama say there has been accelerated warming in the last 10 years? Who is not telling the truth?

    (oh, it’s the climate models you say…)

  15. Well, sorry if I am wrong, but I don’t see an explanation of the meaning of RSS at the start of the post.

    According to the glossary RSS means ‘remote sensing system’ but I have the feeling in this post is means something different, temperature data.

    What is more, In the paragraph Climate Science Abbreviations of the glossary there is no RSS.

    So what is the exact meaning of RSS in this post?

  16. Let’s not lose sight of the big picture which is that this flat line temperature data does not in any way match up with the IPCC temperature predictions/projections for the first two decades as published with fanfare in their 5 year reports.

    Thus their AGW conjecture fails once again.

  17. I noticed that the CO2 concentration graph appears to show a trend that is very linear. If the anthropogenic contribution to the overall concentration is significant, would this not imply that the trend of this component alone also be linear? I understand that a method of smoothing has been applied to create the graph, yet I am still inclined to think that some variation in the human CO2 output should reflected in the slope in this graph.

  18. mpcraig (August 25, 2013 at 10:14 am) asks: “Does anybody know the global average SST vs the global average air temperature over the oceans? If the former is lower, how can heat transfer (net) from atmosphere to ocean?”

    Don’t know of a data source, but your logic only holds if atmosphere to ocean heat transfer is linear. But we know it is quite nonlinear. For example, the trade winds during neutral and La Nina conditions are able to move warmer surface water west in the Pacific and then down into deeper ocean out there. Another example is downwelling areas in Arctic and Antarctic are very efficient at transferring heat into the ocean even with relatively colder ocean temperatures in those locations.

  19. If temperatures are flat but CO2 is rising for 16-23 years doesn’t the inescapable warming due to more CO2 have to be counterbalanced by some negative natural cooling to keep the temperatures flat or is that too small to affect things?

  20. Heh, I also just fixed it. Problem is related to how some graphics programs save images and the X-Y origin point. Browsers don’t handle some output well.

  21. RSS stands for Remote Sensing System: a satellite-based global reading of temperature equivalents. They don’t read temperature directly.

  22. JustTheFacts fixed it the third time it got a mention, and Anthony fixed it as well.

    Guy’s you should have left it upside down and instead added a note saying that it was to help Mann and his fans who otherwise wouldn’t be able to understand it.

  23. Every “flat” month, year, decade further reduces the 30 year (WMO standard for Climate) rate of warming. The rate of warming that you are “professionally” advised is accelerating?

    Now if you find out that the rate of return on the investments your financial advisor had described as “accelerating” had actually been reducing for a over decade, how would you describe that person?

    Global 30 year rate of warming (WMO standard for Climate) peaked, for one month, in early in 2003 at the implied “Armageddon” rate of +2c/century. Since then it has declined, presently circa +1.6c/century and every “flat” print can only reduce it further.

    Ladies and Gentlemen, the Pope is about to elope!

  24. Sunsettommy says:
    August 25, 2013 at 11:57 am
    Let’s not lose sight of the big picture which is that this flat line temperature data does not in any way match up with the IPCC temperature predictions/projections for the first two decades as published with fanfare in their 5 year reports.

    Thus their AGW conjecture fails once again.
    ========
    Ummmm. Likewise ahhhhhhhhhhh –
    Thus their AGW BLOVIATING fails once again. A suggestion, merely.

    Sunsettommy –
    Your analysis looks spot-on. Magic.
    Your choice of phraseology – meiosis, deliberately chosen, perchance?
    After all, they’re a bunch of [Self-snip – can y o u guess which Anglo-Saxon expletive was snipped??] stalinists, who wish to drive the ‘West’ back to the medieval period [at least].
    Life expectancy in the thirties or forties, unlikely to know grandchildren, living in squalor. Etc.

    Auto.

  25. Greg says:
    August 25, 2013 at 10:16 am

    I am limited to what I can do with WFT. As for the offset, that is to fill the page nicely. Of course we cannot have units for two things so the CO2 has no units. But the important thing that I wanted to illustrate was that CO2 was steadily climbing while temperatures were not.

  26. Jimbo says: Even many climate scientists agree that there is a surface temperature standstill. Dr. Hansen is among them.

    Yeah, let’s examine this from their point of view.
    1. They predicted catastrophic warming.
    2. The warming stopped, for around 20 years. This they refer to as a “pause” or “standstill”.
    3. They have absolutely no explanation for the “pause”.
    4. They continue to predict catastrophic warming to a 95% certainty, blah, blah, blah.

    My seven year old comes up with more plausible and credible reasoning than this!

  27. rgbatduke says:
    August 25, 2013 at 10:22 am

    I will make the adjustment in the next report. I agree that if one wants to compare apples to oranges, one cannot be too quantitative in this case. I should have been more qualitative in my description and said that while the oranges (CO2) were rising, the apples (temperature anomalies) were not rising. Thank you very much for the correction!

  28. “Well. I tell you what, these graphs need some dicen and splicin and that’s all there is to it by gum dad burn it. You all are in need of more scientificity in order to properly demonstrate the AGW scienceyness hidden behind the curtain over there that you are to ignore. Dr. Mann is the most sciencific person we know and we are sending him right over to lecture you on knob control. See, you forgot to turn the knob up. You gotsta turn the knob thingy up in order to calculate the thing that CO2 does to your graphs. And then you halfta tilt it a bit but not too much soes it won’t tip over. And then you gotsta send your manuscript stuff to the following pal of Dr. Mann cuz he is up to speed on the talking points about all this tilting, and massages, and hotspots, and really really really big hurricanes…and all that there.”

    This email will self-destruct in 5…4…3…2…1……….(damn…it’s still on the server. Maybe if I call up Dr. Mann he can make it go away. Mann! Make the email go away!)

  29. Genghis says:
    August 25, 2013 at 10:38 am
    I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?

    You may find the following interesting which shows how the temperatures vary by about 3.8 C during the year:

    http://theinconvenientskeptic.com/2013/03/misunderstanding-of-the-global-temperature-anomaly/

    As for how much temperatures went up over the last 50 years, according to Hadcrut3, I would say about 0.6 C.

  30. Its very simple. Ramanathan in 1989 used ERBE data to show that the net effect of global cloud cover is cooling (a forcing of -11 watts/m2) – 4 times larger than that for a doubling of CO2. Clouds are not a feedback to climate change – they are the main driver of climate change! Global cloud cover fell from 1983 to 1998 coinciding with warming. Since then cloud cover has remained constant coinciding with flat temperatures thereafter. AGW (CO2) is a smaller effect than clouds. If cloud cover were now to increase then the earth would cool despite CO2 levels.

  31. mpcraig says:
    August 25, 2013 at 10:14 am

    > Sorry for going OT here but I have a question.

    Ask in an Open Thread or a two day old post and I’ll give you my reply. It’s rude to redirect the comments of a new post right away.

  32. rgbatduke says:
    August 25, 2013 at 10:22 am

    “For so very many reasons . . .

    Agreed.

    Also, it is worth mentioning that Ben Santer’s “17 years” is not a natural constant such as gravity or light speed. If someone does another 100K Monte Carlo runs likely they can claim the number of years without warming in a model has gone to 18, 19, 20, . . . n. This is an easily moved ‘goal post’.

    Still, the perception of GW or lack thereof is important. The ongoing “lack of” is what makes the current USA administration seem clueless, wasteful, and ideological driven.

  33. The details are below and are based on the SkS Temperature Trend Calculator:

    Why are skeptics using this SkS product? Who has vetted it for accuracy, besides SkS?

    Given the fine examples of their l33t h4x0r 5k1||z, how can you trust it without verification?

    I could possibly believe that product alone accounts for half of SkS’ normal site traffic. Why haven’t skeptics tried to replicate it? Isn’t replication something skeptics regularly demand as part of the scientific process, when they demand data and code to attempt replication as part of verification?

    Where have all the real skeptics gone?

  34. Greg says:
    August 25, 2013 at 10:39 am

    A change from +ve to -ve slope is also called a deceleration.

    You are of course correct. However I think it is important that we differentiate between climate getting warmer, but at a slower rate, and actual cooling taking place. The slight cooling taking place over the last decade is certainly not statistically significant, but at the same time, no one can look at the data and say warming is accelerating.

  35. Jurgen says:
    August 25, 2013 at 11:49 am

    Well, sorry if I am wrong, but I don’t see an explanation of the meaning of RSS at the start of the post.
    So what is the exact meaning of RSS in this post?

    I apologize for not defining it. RSS is a satellite data set. I see that others have sent links to RSS.

    In addition, the data set comes from here.
    ftp://ftp.ssmi.com/msu/monthly_time_series/rss_monthly_msu_amsu_channel_tlt_anomalies_land_and_ocean_v03_3.txt

    My plots for RSS come from WFT such as:

    http://www.woodfortrees.org/plot/rss

    WFT (Wood for Trees) allows you to plot any period you want and to get the slope of any period you want. It shows all data sets that are plotted in my graphs.

  36. lsvalgaard says:
    August 25, 2013 at 10:06 am

    RSS Flat For 200 Months (Now Includes July Data)
    Thus no global cooling…

    ————————————————————

    For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

    But then you are almost rabid in shouting down anyone who has the temerity to suggest the sun might be playing a significant role in recent changes to our planets climate.

    IMHO ideology poisons true science.

  37. kadaka (KD Knoebel) says:
    August 25, 2013 at 2:17 pm

    Why are skeptics using this SkS product? Who has vetted it for accuracy, besides SkS?

    When we did the Crowdsourcing about 6 months ago, we asked about other sources for this information but found none. However one person who commented said the numbers are correct and were derived from a very straight forward calculation. I also compared this to WFT and found them the same. For example with RSS since 1990, SkS says the slope is 0.120 +/- 0.129/decade. WFT says 0.0120364/year. So no problem here. As for the statistical significance part, since the site shows that RSS has almost 24 years of no statistically significant warming, which must be very embarrassing for them, I see no reason to question their site.

  38. David W says:
    August 25, 2013 at 3:10 pm
    “Thus no global cooling…”
    For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

    That your feathers appear ruffled by my comment seems to say something about your ideology.
    You did not react to:

    justthefactswuwt says:
    August 25, 2013 at 10:11 am
    I agree, it all seems quite average to me…

  39. Werner Brozek says:
    August 25, 2013 at 1:38 pm

    >>>… the important thing that I wanted to illustrate was that CO2 was steadily climbing while temperatures were not.

    This is worth shouting out. Some posters on these threads have the ability to tease out subtle quantitative relations between carefully researched factors, and I admire their skills, but this relation that you mention hits the floor with a clunk. In the approximately seventeen year “pause” in global warming, CO2, the main causal factor, has increased by approximately 8%, without measurable effect. This is strong evidence that CO2 is a less effective driver than thought or that other factors that we haven’t been studying are able to overcome the effect of CO2. Either of these conclusions is bad news for the consensus view.

  40. “Now if you find out that the rate of return on the investments your financial advisor had described as “accelerating” had actually been reducing for a over decade, how would you describe that person?”

    I Love this characterization, can I borrow it and use in my emails to friends?

  41. Personally, I found the graph with the co2 vs T quite interesting. As I understood it, the scales were chosen to indicate the rough range of expected T increase for the given amount of co2 increase. Granted the co2 is a log function but it has diminishing effect with increases so a small section of linear comparison should net a steeper curve of T increase than the overall which should have been at least to go from bottom to top of the graph at that scale. The flatline response shows us nothing happened. Since all of these supposed positive feedbacks are actually temperature based, no increase in temperature means no positive feedback is going to happen at any time scale from this increase – unless there was some temporary and immediate situation that existed which worked against the co2 and kept the T from rising.

    I am afraid I encountered the current or next facet of the assault. I attended a training seminar put on by a ‘scientist’ educator who made lots of efforts – like ad hom attacks, straw man arguments, non sequiters, etc to promote the CAGW and that education (and science education) must overcome these deniers and to present a solution currently being tested that dillutes science education more than it already is. Somehow, the claim that the Earth has been warming magically turned into catastrophic anthropogenic global warming. Also, somehow, their solution to educating included the use of pseudo scientific topics to train the students to distinguish between the real and the false, but somehow, while distinguishing between real authorities (true believers?) and non authorities (blasphemers?) was described when talking a bit about the scientific method, there was no mention of analyzing actual data as being an important part of the scientific method.

    I am still somewhat traumatized by the recent event and I know that most of the attendees were not prepared to even recognize these things.

  42. David W says:
    August 25, 2013 at 3:10 pm
    “Thus no global cooling…”
    For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

    There are two camps of alarmists: the CAGW camps and the ‘it’s the Sun, stupid’ camp. One way of interpreting a ‘flat RRS curve’ is note that by colossal coincidence, the effects pushed by the two camps just cancel out Another way is [what I would consider the null-hypothesis] to note that neither effect is operating to any significant degree. Which one do you subscribe to, or what is your ideology?

  43. Reblogged this on CACA and commented:
    On six different data sets, there has been no statistically significant warming for between 18 and 23 years, despite record and rapidly increasing ‘carbon pollution’ emissions over the same period ~ settled science?

  44. lsvalgaard says:
    August 25, 2013 at 4:29 pm
    Another way is [what I would consider the null-hypothesis] to note that neither effect is operating to any significant degree.
    =========
    Another option would be to say there is insufficient evidence. While the later is more likely, co-incidence is not impossible.

    humans tend to see things in black and white. we all too often equate long odds with a sure thing. However, Is there any bet more risky than to bet the farm on the “sure thing”?

  45. wbrozek says: August 25, 2013 at 3:26 pm
    “When we did the Crowdsourcing about 6 months ago, we asked about other sources for this information but found none.”

    I am now keeping the all periods, all sources diagrams here updated. For example, here is the RSS plot. You can choose the interval for data display by either clicking on the triangle, or using the controls on the graph. You can choose to display significance levels, t-values etc.

  46. JimS says:
    August 25, 2013 at 11:34 am
    This can not be. Did not Obama say there has been accelerated warming in the last 10 years? Who is not telling the truth?
    ===========
    Looking at the data there has been a decrease in the rate of warming, so technically there has been accelerated warming, in a negative direction.

  47. Dan Pangburn says:
    August 25, 2013 at 3:13 pm
    “The influence of CO2 is separated from natural influence at…”

    No it hasn’t. Solar variations have been shown to be a very poor proxy for temperature trends. In addition you have no mechanism. Therefore your solar connection to the trend is about as good as the fact that I have grown older during the same time period. Therefore I am just as good a candidate as your solar sunspot number is as a driver.

  48. For those interested in decadal change, is the decade to June 2013 warmer than the preceding decade ending June 2003?

  49. The CO2 is just reserving its strength, waiting for the opportune moment – probably coinciding with great humungous glob of heat rising, like Leviathan out of the cold ocean depths where it has been dodging ARGO floats and such, to the surface, – to give us a serious roasting. Or not.

  50. Barry said on August 25, 2013 at 5:46 pm:

    For those interested in decadal change, is the decade to June 2013 warmer than the preceding decade ending June 2003?

    http://woodfortrees.org/plot/wti/from:1993.45/to:2003.45/plot/wti/from:1993.45/to:2003.45/trend/plot/wti/from:2003.45/to:2013.45/plot/wti/from:2003.45/to:2013.45/trend

    Notation note: Dates include decimal years, June is 0.42, so June 2003 is 2003.42. Call-out uses 0.45 as that’s between June and July and WoodForTrees works with whole months anyway. So 1993.45 to 2003.45 indicates July 1993 to June 2003 inclusive.

    Decade ending 6/2013 was warmer than that ending 6/2003, which was expected since there was still warming in the first decade.

    But as you can see, in the second decade there was cooling. Whether it was statistically significant or not, eh, who knows.

  51. I want to coin the term for a great belch of heat from the abyss, if and when it happens: a “Trenberth”.

  52. ferd berple says:
    August 25, 2013 at 4:55 pm
    Another option would be to say there is insufficient evidence.
    You mean to say there is insufficient evidence to say that the warming has stopped?
    I’ll go so far as to agree that there is insufficient evidence for anything. Most people would say that if their pet theory is not supported, there clearly is insufficient for the opponents theory.

  53. Unfortunately, some years ago the data became too readily available, and they couldnt make adjustments anymore, strange that the warming stopped at about the same time.

  54. Nick Stokes says:
    August 25, 2013 at 5:12 pm

    Thank you! However I will need time digest it.

  55. kadaka (KD Knoebel) says:
    August 25, 2013 at 6:47 pm

    But as you can see, in the second decade there was cooling. Whether it was statistically significant or not, eh, who knows.

    The SkS site for RSS from 2003.58 to 2013.58 gives a slope of “Trend: -0.047 ±0.409 °C/decade (2σ)”. So it is no where close to being statistically significant. It is not even close at the 1 sigma level which I presume would be +/- 0.205, but I could be wrong here. Perhaps Nick Stokes can figure it out. Perhaps a 54% chance that it is cooling? But I am just guessing here.

  56. Genghis says:
    August 25, 2013 at 10:38 am
    I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?

    Approximate decadal absolute global surface air temperatures, correct to 1dp
    August 1953 to July 1963, 13.9(+0.4, -0.7)°C
    August 2003 to July 2013, 14.5(+0.4, -0.7)°C

    (1) The figures of 13.9, and 14.5 are as per GISTEMP’s “LOTI”.

    http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt

    (2) The assymetric error estimates, (+0.4, -0.7), are as per GISTMP’s “The elusive absolute surface air temperature”, which is one of the most remarkable, and subversive, documents in climatology. If you’ve not read it already, I urge you to read it.

    http://data.giss.nasa.gov/gistemp/abs_temp.html

    (3) The temperature for 08/1953 to 07/1963 could have been as high as 14.3°C.
    (4) The temperature for 08/2003 to 07/2013 could have been as low as 13.8°C.

  57. Wasn’t there a period between 1944 and 1976 when the global temperature was flat or even falling slightly?

  58. I will make the adjustment in the next report. I agree that if one wants to compare apples to oranges, one cannot be too quantitative in this case. I should have been more qualitative in my description and said that while the oranges (CO2) were rising, the apples (temperature anomalies) were not rising. Thank you very much for the correction!

    Not a problem. A second suggestion. You, like everybody else in the known universe, present not the absolute values of the quantities in question, but the so-called “anomalies”. If you want to see something very, very instructive, plot them in their actual units — parts per million (for example) for CO_2, degrees kelvin for temperature.

    There are a number of reasons this is basically never done. One is that on a 300 degree kelvin (give or take a hair) scale, in a figure perhaps 300 to 600 pixels high total, the entire thermometric climate record is pretty much a single totally flat line — at most it varies over a single pixel in height. If you plotted it in absolute units and included error bars, the error bars would be several pixels thick everywhere but in the very last tiny bit, pretty much the stretch from the 1970s to the present, and the line would get thicker fast as one proceeds into the past from there. If you presented this in any public forum, it would be rather difficult to convince people that the world is at risk. The CO_2, on the other hand, has increased by 1/3 over the last seventy years — a substantial change, it would show up on any graph.

    It is presenting the CO_2 change next to the temperature change presented as an anomaly measured only from 1870 to the present — that is, from the Dalton minimum and functional end of the Little Ice Age to the present — that provides the illusion of a “good” correlation. If you present the over longer intervals, the natural range of variation becomes apparent, and the LACK of good correlation between CO_2 and temperature over even the last 140 years becomes equally obvious — it warmed almost as much from 1870 to 1950 as it did from 1950 to the present, enough to make it very, very difficult to be able to discern the CO_2 linked fraction of any temperature changes that might or might not have occurred across this interval. This both weakens and strengthens your argument. It strengthens in that it shows that natural variation is sufficient to explain all or most of the observed late 20th century warming as the Earth is demonstrably capable of warming substantially and rapidly without CO_2 forcing; it weakens it because the flip side of that coin is that even if CO_2 is indeed acting as a GHG that “should” be making it warmer all things being equal, natural variation could be cancelling all or most of the warming because all things are NOT, actually equal. That does not mean, however, that when the natural cooling cycle ends that warming will not resume.

    I generally dislike arguments that attempt to prove something about the climate on the basis of correlation or a lack thereof, because post hoc ergo propter hoc is a logical fallacy whichever way you swing it. Correlation between CO_2 increases and temperature increases does not prove CAGW, and a lack of correlation between CO_2 increases and the temperature does not disprove it. The only safe thing to say, as I said, is that is certainly not good evidence for the proposition. Otherwise, you can take any generally increasing monotonic quantity and claim it is the “cause” of the generally increasing temperature post 1870, or get involved in the arcane numerology of fitting planetary cycles or misreported sunspots or possibly miscalculated solar magnetic field strength data (known by means of proxies) to temperature data (ignoring the error bars in the latter, as usual).

    There was an op ed on CNN recently where the writer was defending Al Gore’s Category 6 hurricane invention (and carefully sidestepping the facts that Pielke, Jr presented to congress recently, that there is no statistically observable trend in strength, frequency, or normalized damage of any kind of extreme weather over ANY time interval that makes a hash of Gore’s entire, oft-repeated, untrue assertions to the contrary). The writer then went on (after asserting that “even category one hurricanes can be very damaging”, well duh, but there isn’t any evidence of the slightest anthropogenic influence on the frequency or damage of even category one hurricanes) to assert that we are sure to get 3 to 6 feet of SLR by the end of the century.

    Say what? This is Hansen’s old argument and its associated egregious claims, now with an independent life of its own. It is directly contradicted both the tide gauge data and the new (and still somewhat shaky) satellite data. Even Trenberth no longer claims anything like this in public (IIRC, his claim is currently for perhaps 15″, which is high but not completely insanely unreasonable). I replied, and was immediately told that I was wrong because (for example) the rate over the last 15 years was 3.3 mm/year while its average rate from 1870 to 1995 or so was less than 2 mm/year, proof that it is “accelerating”. I pointed out that if you look at the actual tide gauge data on SLR from 1870 to the present, there are four distinct periods of a decade or longer where the rise rate was 3.3mm/year or even more — including a decade at the very beginning of the 20th century and the twenty years from 1930 to 1950 (both of which are pre-CO_2). It is no more reasonable to look at the last 15 years as evidence of acceleration or a linearly extrapolatable 15″ by 2100 than it would have been to look at 1930 to 1950 and conclude that the ocean should be several inches higher now than it is, or to look at an interval from e.g. 1910 to 1920 (IIRC) where SLR was almost perfectly flat and conclude that THIS was an extrapolatable trend.

    The point being that reason is almost entirely absent at this point from the entire climate debate, on both sides. Post hoc ergo propter hoc has become the foundation of all arguments, and any claim, no matter how outrageous, now has an effectively infinite lifetime in the public debate. How do you refute the assertion that SLR will rise six feet by 2100? Point out that six feet is 72 inches, so that the ocean would have to rise an average of an inch a year where it is currently rising at an eighth of that rate in what could easily be an entirely natural rate fluctuation? Point out that in order for this to occur Greenland and Antarctica would both have to lose a rather large fraction of their land-based glacial icepacks in a matter of a few decades, where there isn’t any real evidence that they are losing ice at all, or at most are contributing significantly less than 1 mm of the current SLR (even according to climate scientists looking for that “warming signal”, which one can interpret as open season on cherrypicking any or all data that supports it). Point out that every year that the rate of SLR peskily persists at 3 mm/year means that it has to rise even faster than an inch a year later on? Point out that the only basis for believing this is an “ensemble” result obtained by averaging GCMs most of which individually would fail a bone-simple statistical hypothesis test when compared to the actual climate data at the 95% confidence level or more, and adding in a dose of voodoo magic because it would take a few centuries to melt a significant fraction of the icepacks of either greenland or antarctica assuming that the climate DID warm by a couple of degrees by the end of the century?

    Which brings us around to your top post, which quite correctly demonstrates — again, since this is hardly secret knowledge — that there has been no discernible warming trend since the 1997-1998 Super El Nino. Or cooling trend. One can play games and cherrypick intervals a bit this way and show some cooling, a bit that way and show some warming, but the really important divergence isn’t between CO_2 on some arbitrary scale and a temperature anomaly on an even more arbitrary scale across an arbitrary interval it is the divergence between the GCM predictions from 1998 to the present and reality.

    That’s not a matter of cherrypicking a start. The GCM predictions were made at a (set of) definite times. Most GCMs ran, at that time, an ensemble of possible futures given continuously increasing CO_2 (as it has in fact continued). The actual performance of the climate is outside of the range of 95% or more of the ensemble predictions over almost the entire interval. Worse, if one tracks the individual trajectories themselves, none of them behaved at all like the climate for most of the models — at least the ones I can see e.g. reported in AR5 or AR4. Typically the models make future trajectories that oscillate up and down, oscillate differently per run but still over a wide range, and the observed climate is at the bottom of the envelope of these oscillatory outcomes. This isn’t really failure at the 95% confidence level — per model — it is failure of the model, the kind of failure that one doesn’t even question, it is “certain failure” at more than 99%, an amount so much more that is difficult to calculate. That is, if you compared each model-generated trajectory to the actual data, you would instantly say “nope, no, not that one, not even close…” one at a time for all of the trajectories. The best thing one could say is that some comparatively small fraction of them descend to spend some small fraction of their time down close to the observational data.

    That is one of several reasons that the AR4 summary for policy makers is egregious statistical fraud, and I’m very much afraid that AR5 is set up to make exactly the same mistake. It might not even be “deliberate” — not many people are competent in statistics, and by plotting the composite envelope (which in some cases barely catches the data on the bottom) one is misled into believing that it is this envelope that determines the variance of the models overall, rather than the fraction of time any given model trajectory spends anywhere near the observational data, per model.

    I repeat — this is not cherrypicking an interval, it is comparing a prediction made at a certain time to the only data we have that follows. Yes, the models were built to fit the prior data, so fitting it is not a surprise or an endorsement of the predictive power of the models. It is how the models do at actually predicting the future that matters.

    This final step is the constructive one. Suppose that you are the keeper of a GCM, and you honestly appraise your model’s performance over the last 16 to 20 years. You note that — let’s be blunt — your model fails to predict this interval, not at any “confidence” level but at the level of pretty much certainty. You can then go into your model and try adjusting its adjustable parameters to improve the model. For example, you could turn the climate sensitivity way down, completely retune the way water vapor is handled, allow for a lot more natural variation that (if you are honest) you cannot predict and do not even understand as your model does not hindcast any of it, try to once again fit it to the trial set pre-1998 (or whenever) and see if it can fit the actual data THEN.

    This is the kind of thing those of us in the predictive modeling game for actual money call “training and testing a predictive model”, and when there is money on the line, you dasn’t fail or you go broke. If a major wall street investment company sold its clients a bull market prediction that went up like CAGW was supposed to go up, and the market turned flat to bearish for 16 years (where that investment firm kept going back to its clients, year after year, and claimed “the market is about to go up, look at our models, they are sky high, we have found a secret pathway where money has been diverted into rails and has been building up and the market will come roaring back, any day now”) how many clients would they still have? Would “zero” be a reasonable guess, given that all of its clients would by now be bankrupt from shorting themselves into a supposedly rising market?

    The thing is, building a predictive model for a complex, nonlinear, multivariate system like the climate or the stock market is goddamn difficult! Or rather, it is stunningly easy, with readily available tools. It is building one that works that is difficult, no matter what tools and how much insight you bring to bear. For example, the performance of the stock market is almost certainly tied not only to the actual climate (in many ways) but at this point it is tied into the public perception of the climate in as many or even more ways! And for all of that, this is only a possible/probable causal factor that can easily be swamped my many, many other things acting singly or collectively — the cost of money, how many wars we are fighting, and where, whether or not the next major public scandal involving corporations acting like banks illegally or banks acting like banks stupidly is ready to fling shit at the fan, monetary policy and unemployment in Greece, the rate that the Chinese are modernizing, and mere weather events like Sandy that can shut the market down and make a few tens of billions of dollars disappear overnight.

    How the hell do you model that?

    The climate is really not much simpler, for all that we can in principle describe the physics of each parcel of atmosphere and water and land and the sun down to a stunningly fine resolution, although with a number of approximations and attendant errors that are very difficult to estimate. That is because the climate system is chaotic, nonlinear, and highly multivariate.

    All that is really missing in climate science is honesty. I was on jury duty a few days ago with an area meteorologist, and while we were debating the Bayesian merits of the evidence in the criminal case at hand he made a comment that I — correctly — interpreted as his being highly dissatisfied with climate science. After the verdict was in, we chatted about the weather and climate for almost an hour before finally going home. He pointed out that the one really sad thing about climate science isn’t that the science that is being done isn’t terribly good, that the GCMs are failing and so on. It is a goddamn hard problem, one expects to fail. It is the lack of honesty, the assertion of results from failed models as if it were reality, even in the face of a reality that directly contradicts those predictions!

    It is not too late for AR5, even now. All they need to do is publicly acknowledge what almost all the scientists involved already know as a most inconvenient, uncomfortable truth. The GCMs upon which predictions of future catastrophe rely have more or less failed, and the statistical relevance of those predictions has been erroneously computed and horrendously misrepresented in previous AR reports. This doesn’t mean that AGW is an incorrect hypothesis, and it does not disprove even CAGW, but it does mean our certainty of the magnitude of AGW past, present and future is a lot less than has been asserted.

    A tiny bit of honesty, and it would make all of the difference in the world. It would enable science to be carried out that for once was not trying to verify CAGW (so that it could get funded at all). It would allow world leaders to come back to sanity and back off on the expensive and pointless attack on Demon Carbon and instead concentrate on constructive things, such as supporting research and development of e.g. PV solar not to Save The World but because it will ultimately save US taxpayers money as the price per watt continues to plummet. I communicated today with a chance-met slashdot person who sells PV solar systems, and he tells me that they sell PV solar full retail with warranty for $0.69/watt. That is down by almost $0.30 in only three or four years. He’s installed it for himself at break even to win a bit in Toronto, driven not by any desire to “be green” but because energy prices plus regular inflation make it a decent investment even that far north. Power companies can get wholesale cells at $0.50/watt for large scale installations.

    We are thus within a hair of making solar energy not just a positive ROI (without subsidy) investment. We are within two hairs of it becoming a no-brainer, the next gold rush as every household puts PV solar on the roof. Just as natural gas caused the US to actually reduce its carbon footprint not because it is saving the environment but because it is cheap and methane is one carbon per four hydrogens so a lot of the energy comes from burning hydrogen, not carbon, PV solar will reduce its carbon footprint still further not because it is saving the environment but because there is something dazzlingly attractive about paying out about the same amount that I just paid for three household air conditioners and never have to pay for the electricity to run them again!

    It would let coastal communities STOP preparing for meter-plus SLR that will start — honestly, trust me — any day now (as if it will all happen overnight, so we need to go ahead and spend a fortune now because it is certain). It would let Europe stop building windmills that — curiously — don’t generate power when the wind doesn’t blow, which is a lot of the time in most places. It would let third world countries build coal-burning power plants without spending two or three times their normal cost trying to control CO_2 as a “pollutant”, which in turn will save countless lives and improve the living conditions of millions of people right now, not in 80 years. And yeah, in ten more years they too can benefit as the price of solar continues to drop, allowing them to eke out a coal burning generator during peak daylight demand when air conditioners are most needed, when most manufacturing takes place, when water can be purified and pumped without burning coal at all not to save the Earth but to save money.

    Perhaps it will be saving the Earth, perhaps not. It’s hard to say at this point. We really don’t know. We have some reason to think that it would be wiser not to pump up atmospheric CO_2 more than we have to in order to bring the world up to a uniform degree of civilization as rapidly as possible, but we also have some excellent reasons not to let the fact that building up civilization quickly and inexpensively (still) requires the burning of oil and coal stop us from doing it, at least until the science is a lot clearer than it is at the moment. By which time, as I said, the issue might well be moot. We are almost to the point where mere engineering will lead to the utter dominance of PV solar (that is, nuclear energy once removed) supplemented by natural gas and, perhaps, eventually, by nuclear energy, and there are a couple of technological game changers that could happen literally overnight (or not). Invention of a viable, cost-effective long distance energy transmission scheme — something that could move power from Arizona to Maine, or from the Negev to the Netherlands. Development of a scalable technology that would permit solar power to be “banked” for overnight delivery, e.g. pumping up underground caves with compressed air and using the air to run a conventional generator during the night and to buffer power fluctuations. Reduce solar costs to $0.25/watt, or $0.10/watt, and we’ll have power to (not) burn, so to speak — we could afford to put 3 GW of generation in where we only need 1 and bank 2 to get us through the night.

    rgb

  59. From wbrozek on August 25, 2013 at 7:58 pm:

    The SkS site for RSS from 2003.58 to 2013.58 gives a slope of “Trend: -0.047 ±0.409 °C/decade (2σ)”. So it is no where close to being statistically significant.

    Except my link was for the WoodForTrees Temperature Index (WTI). The SkS trendy toy doesn’t do WTI.

    So do you know if the WTI cooling trend is statistically significant?

  60. kadaka (KD Knoebel) says:
    August 25, 2013 at 8:43 pm

    So do you know if the WTI cooling trend is statistically significant?

    WTI is a combination of Hadcrut3, GISS, RSS and UAH. They discontinued Hadcrut3 very recently, but they do have Hadcrut4 which has a slightly lower slope, but even so, the numbers are no where close to being statistically significant over the last 10 years. Here are the 4 numbers for Hadcrut4, GISS, RSS and UAH:
    Trend: -0.055 ±0.219 °C/decade (2σ)
    Trend: -0.019 ±0.243 °C/decade (2σ)
    Trend: -0.047 ±0.409 °C/decade (2σ)
    Trend: 0.040 ±0.412 °C/decade (2σ)

  61. August 25, 2013 at 10:38 am
    I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?

    Approximate decadal absolute global surface air temperatures, correct to 1dp
    August 1953 to July 1963, 13.9(+0.4, -0.7)°C
    August 2003 to July 2013, 14.5(+0.4, -0.7)°C

    (1) The figures of 13.9, and 14.5 are as per GISTEMP’s “LOTI”.

    http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt

    (2) The assymetric error estimates, (+0.4, -0.7), are as per GISTMP’s “The elusive absolute surface air temperature”, which is one of the most remarkable, and subversive, documents in climatology. If you’ve not read it already, I urge you to read it.

    http://data.giss.nasa.gov/gistemp/abs_temp.html

    (3) The temperature for 08/1953 to 07/1963 could have been as high as 14.3°C.
    (4) The temperature for 08/2003 to 07/2013 could have been as low as 13.8°C.

    A marvelous reply. I agree that the GISS document is remarkable and subversive. It is also wrong, rather horribly wrong. Specifically, the paragraph that justifies using not only the anomaly, but the anomaly in an offhand, casual, almost anecdotal way, in a way that if anything shows a sort of disdain for the actual temperature is shocking. Shockingly wrong. Wrong minded.

    This is wrong in a way that can only be compared to the error involved in reporting a global average anomaly when the only quantity that actually matters in the Earth’s radiative budget is the spatiotemporal integral of the fourth power of the temperature. This is still inadequate — outgoing radiation is emitted everywhere from the surface itself to a whole region in depth in the upper troposphere and lower stratosphere, so one really has to deal with the fourth power of temperature in a vertical volume of atmosphere down to at least the surface of either ground or water, and quite possibly at down further to some depth in at least water. Incoming radiation has to be handled as well.

    “Surface Air Temperature” is thus a truly, remarkably, meaningless quantity no matter how it is computed or reported, the more so given the enormous error. And what KIND of error is it, he wonders, given its asymmetry? Surely not a normal error, e.g. standard deviation. How is the error computed, or “estimated”? Since it isn’t normal (and certainly isn’t sharp) what are the probabilities that the real temperature is actually (say) 0.5C warmer than the reported value, instead of 0.4C? Surely not zero. If the error was a standard deviation (and hence symmetric) we could actually make a definite statement, such as it is 96% probable that the true SAT was within one whole degree C either way of the reported value. What kind of statement can be made for these asymmetric limits, and why are they so very asymmetric with the lower error almost twice the upper?

    But in the end, the real point is that the SAT from 1953 to 1963 is within the mutual error of the SAT from 2003 to 2013. That means that one would be justified in reporting that there was no statistically discernible warming over that interval, that the increase in the anomaly might be a result of statistical noise, not even natural variation.

    The final (very interesting indeed) observation is that the rate of warming over this entire interval is 0.12 C/decade (with error limits on the rate that are larger than the value as noted). Simply linearly extrapolating this to 2100 implies a total warming of a single, solitary degree Centigrade over the rest of the century. And yes, that includes the effects of CO_2, since the fifty years in question are all in the “rising CO_2″ era that began with World War II and beyond. This in turn implies that average feedback from all sources (all things being equal) is almost perfectly neutral (zero amplification) as 1.2 C is what one expects from doubling the CO_2 alone.

    rgb

  62. rgbatduke says:
    August 25, 2013 at 8:36 pm

    Thank you! I know it has been done before with one of your replies. I am wondering if someone in charge who may be reading this would consider making your reply a separate post.

  63. stryNo it hasn’t. Solar variations have been shown to be a very poor proxy for temperature trends. In addition you have no mechanism. Therefore your solar connection to the trend is about as good as the fact that I have grown older during the same time period. Therefore I am just as good a candidate as your solar sunspot number is as a driver.

    Damn! I knew it was your fault! I was thinking that it might have been caused by my weight gain over the same period and didn’t look forward to starving myself and exercising heavily to save the whales.

    So what we should be working on to prevent global warming is a time machine, so we can reverse your personal aging process.

    Time to write a grant proposal!

    rgb

    P.S. — good proxy, bad proxy, everybody needs to visit:

    http://en.wikipedia.org/wiki/Post_hoc_ergo_propter_hoc

    and memorize it! Seriously, nobody (not you, Pam) should ever do it again. Correlation is not causality. In a complex, nonlinear, highly multivariate system, causality itself is blurred. For example, it makes little sense to describe my thoughts in terms of quantum mechanical transitions and transfers of electrons in molecular orbitals, even though at some level that is what they are. As my good friend and founding father of the science of complex systems used to say (in the class I took on them, long long ago) “more is different”, and in physics it is a bitch and a half to go from one domain (say, pure quantum mechanics) to the one a single notch up (say, quantum chemistry) and makes almost no sense at all to do something like describe organic chemistry in general in terms of pure quantum theory, and even less sense to try to describe biochemistry as an extension of organic chemistry in terms of pure quantum theory.

    One of many reasons I am more than a bit cynical when CAGW enthusiasts assert that the GCMs are all “based on physics”. Sure they are. The question is, are they a correct implementation of that physics, and is the answer computable? Not so clear. I suspect that predicting the climate on the basis of “physics” is even harder than predicting the emergence of living forms and their subsequent biochemistry by solving a really big example of Schrodinger’s equation. More is different. The rules of biology bear almost no resemblance to the quantum physical laws that ultimately support them, and that is long before one reaches the point in biology where one is trying to (say) understand Shakespeare by understanding electronic transitions!

    Ordinarily, in physical modeling in the real world, we build semiempirical models by coming up with rules of thumb that we often CANNOT microscopically derive or generalize, to the point where one builds entire ontologies out of rules of thumb, heuristic ontologies. For a long time, thermodynamics was such an ontology; then statistical mechanics allowed most of it to be derived from more fundamental principles. Chemistry was another — rules and laws for chemistry preceded their quantum mechanical explanation by decades and their moderately accurate quantum mechanical computation for over a century. It is almost impossible to conceive of jumping two or more level in this sort of game of self-organizing complexity.

    Weather prediction was at one point such an heuristic ontology, then it got better; it turned out to be borderline computable using macroscopic physics and thermodynamics (plus a heft dose of heuristic correction).

    I wonder how many levels GCMs attempt to bridge? Radiation physics is purely quantum mechanical, although there are some derivable semi-heuristic rules like Stefan-Boltzmann. Petty’s book is pretty complicated, and he simply shrugs and inserts one of several not particularly compatible approximations where the going gets too tough to be computable otherwise. Then there is the Navier-Stokes equation — a nonlinear PDE so fiendish that mathematicians cannot yet prove that solutions to it always exist, let alone compute them. Oh, make that two of them, one for the atmosphere, one for the ocean. While we are at it, don’t forget to figure out clouds and water vapor and water in general, because water has the peculiarity of being most dense at 4 C instead of in solid form, which really bends the usual Navier Stokes equation even further. Don’t forget to take into account the specific shapes and structures of the continents (at least) because the physics on the spinning, tilted, oblate spheroid that is being diurnally and differentially heated and cooled by a moderately variable star as it careens around it in a slowly varying but remarkably elliptical orbit somehow conspires to make it coldest (globally) when it is closest to the sun and hottest when it is the farthest away, while its top of atmosphere insolation varies by 6.6% (90 watts per square meter) over the course of the orbit.

    Can’t we ignore this? After all, all we care about is the anomaly, the change, whether or not it is going to get warmer or colder. In a linear system, perhaps, although it would bother me to linearize any system that has a thermal oscillation in precise counterphase with the primary driver. But this is not a linear system. It isn’t even close to being a linear system. The system itself is perfectly capable of ripping off decades of aggressive warming — or cooling — even though none of the macroscopic drivers we know of are changing in a way that migth explain it. It is demonstrably capable of starting a glacial era — or even progressing through an entire ice age — straight into the teeth of CO_2 levels ten times higher than they are today. We are in the middle of just such an ice age right now — in an interglacial era of the ice age. We have no good idea why the last glaciation ended, why we warmed and then bobbled back down into glaciation, then warmed again to the Holocene Optimum that was even warmer than it is today, spent most of the last 9000 years as warm or warmer than it is today, cooled to the coldest century in the last 11,000 years a mere 400 years ago, and then warmed, at first gradually, and then more aggressively, since then.

    How can anyone even think of linearizing a system like that? Or pretending that they can predict the feedbacks and average over the nonlinearities?

    Is it really all that surprising that GCMs have a hard time giving consistent results even for toy problems, ones that are missing almost all of the complexity of the real Earth?

    rgb (again)

  64. RGB
    “I agree that the GISS document is remarkable and subversive. It is also wrong, rather horribly wrong. “

    It’s neither remarkable nor subsersive. It is something Hansen has been saying for over 30 years. The NOAA has a very similar statement (see para 7).

  65. rgb I rather like the last half of my life. So skip the reverse aging machine. Who in their right mind would want to relearn all those life lessons?!?!?!?! Sure as hell not me. I can’t wait to get to retirement age! And I intend on getting there with as many fishing poles as my allowance allows. So, sorry about the temperature rise everyone because I intend on getting older. I like older.

  66. Leif. I am not a scientist so perhaps I would phrase my words differently to you. I am a professional though and highly skilled in the profession I work in which is motor insurance where I take massive amounts of data and attempt to predict risk moving forward.

    In terms of the measurement of temperature trends I would say that the current data is insufficient to make conclusions about what might happen in coming decades.

    Some of the SHORTER term data displays indications of cooling whilst SOME displays indications of warming dpending on what time frame you choose to look at. I think such trends either way are somewhat meaningless in terms of their predictive values.

    I would also argue that even when your looking at terms in excess of 20 years we are yet to have sufficent data and knowlege of multi-decadal climate influences to the extent it allows us to make accurate predictions.

    One of the most important aspects of the work I do is to recognise the limitations of the data you have.

    My biggest hope to arise out of the climate change debate is that we have improved our ability to monitor our climate that in another 30 years our predictive models develop some degree of effectiveness.

    Whilst I understand and respect your immense capabilities in your field I am not convinced your understanding of the suns impact on our climate system is as conclusive as you seem to believe.

  67. We have another line of evidence on the temperature stability timeline.

    That of the lower stratosphere temperatures. These have now been stable (perhaps increasing slightly) since the start of 1995 after they reached their new equilibrium level post the Pinatubo eruption.

    The stratosphere is supposed to cool in global warming theory. But it has been stable for going on 18.5 years now.

  68. David W says:
    August 25, 2013 at 3:10 pm
    “Thus no global cooling…”
    For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

    David, Leif is quite capable of defending himself, but I would like to suggest that his comments are entirely valid based on the data. Also, Leif correctly predicted that SC24 would be weak, contrary to the “official” NASA prediction (Hathaway?) that it would be strong. That history provides Leif with some predictive credibility.

    Leif’s position is that solar variability is too small to be the primary driver of observed temperature changes on Earth. Even though I hold a different opinion, I also accept that there is a real possibility that Leif is correct. I also suggest that Leif s position is based on his expertise and on scientific principles.

    Sallie Baliunas, Tim Patterson and I published the following statement in 2002 that appears to be correct, since there has been no significant global warming for approx. 10-20 years:
    “Climate science does not support the theory of catastrophic human-made global warming – the alleged warming crisis does not exist.”

    http://www.apegga.org/Members/Publications/peggs/WEB11_02/kyoto_pt.htm

    In the same article we also predicted the current debacle in “green energy”:
    “The ultimate agenda of pro-Kyoto advocates is to eliminate fossil fuels, but this would result in a catastrophic shortfall in global energy supply – the wasteful, inefficient energy solutions proposed by Kyoto advocates simply cannot replace fossil fuels.”

    I suggest we have also demonstrated a track record of predictive credibility.

    Regarding the temperature data, I believe Earth experienced mild warming from about 1975 to 2005, and that temperatures have now leveled off and Earth is probably entering a natural global cooling period. I (we) predicted in an article published in 2002 that natural global cooling would commence by about 2020-2030, but the timing is approximate. I really hope this prediction is incorrect, because global cooling has caused great suffering for humanity in the past.

    I suggest that global warming hysteria will soon be fully discredited, and its advocates will be held responsible for our lack of preparedness should global cooling occur.

  69. David W says:
    August 25, 2013 at 11:33 pm
    I would say that the current data is insufficient to make conclusions about what might happen in coming decades.
    I didn’t say anything about ‘coming decades’, I simply noted that the flat RSS shows that for the last 16 or so years, there has been no cooling and no warming. This contradicts the folks who say that the warming continues and the folks who claim that the cooling has begun. This is contrary to the wishful thinking of both camps. I also noted that had there been warming, the warming camp would claim vindication while the cooling camp would say the data is insufficient, and had there been cooling, the cooling camp would claim vindication while the warming camp would say the data is insufficient. That is: if the data goes your way you believe the data, but if the data does not go your way, you say the data is insufficient or inclusive. I suggest that at present the data shows that both camps are incorrect or at least that the data cannot be taken as support for either of the views. I fail to see how that ‘says more about my ideology’. I do note that I was talking about the data while you were talking about my person. I suggest we stick to the data.

    • My point is that just because the RSS trend doesn’t show cooling doesn’t mean it is not now cooling which surely when you read the context of the entire article is what is being discussed. No one would argue that the 200 month RSS trend is flat but this in no way empirically shows the globe is not now cooling,

      Just because a method of measurement is incapable of measuring something doesn’t disprove its existence.

      If we were 5 years into what turned out to be a 30 year period of cooling would it not be “cooling” during those first 5 years because we couldn’t yet measure it with any degree of statistically relevant accuracy?

      In fact at 5 years the best we could say is that the climate might be cooling. And then at the end of the 30 years we could say it was.

      Your statement “thus no global cooling” seemed rather absolute. I know its somewhat nit picking but I think when a scientist speaks he should choose his words very carefully.

  70. David W says:
    August 26, 2013 at 4:59 am
    My point is that just because the RSS trend doesn’t show cooling doesn’t mean it is not now cooling
    Cooling can only be defined over an interval of time. Cooling ‘now’ is meaningless.
    I’m rather sure that if the trend had shown a strong cooling, that you would not have said ‘just because the RSS trend shows strong cooling doesn’t mean it is cooling’
    But, regardless, your statement was an un-called-for attack on my person which is more than just nit picking.

  71. Thus no global warming…
    No global cooling, yet.
    In fact, global temperatures have basically flatlined.
    We have killed our climate!

  72. Pamela, brilliant hypothesis! (@5:24PM).
    I must confess though that I encountered a little glitch. The correlation of WW temps with your age works from 1988 to 1996 but a temp plateau after the turn of the century gave me pause.
    But have no worry! Being a long time student of Manniac Science I quickly discovered the answer.
    Clearly you are no longer getting older!!
    (You may even be getting younger but I have to make some adjustments to the data in order to confirm.)

  73. Ok I apologize for the personal attack.

    Now in terms of the other part of your last post. Let me put it differently.

    If the RSS trend for 200 months showed strong cooling except for the last 5 years which showed warming I would then assert that just because 200 month trend does not show warming it doesn’t mean there’s no warming. And if someone said “thus no global warming” I might post my disagreement depending on who they were.

    I don’t react to everything people post or I would never get anything else done in life. When someone such as yourself whose contribution here is generally insightful and well respected posts something I strongly disagree with then I probably will respond if I see it. As far as what justthefactswuwt posts I’m not familiar with him or any of his previous posts and so I didn’t respond to his post.

    At this point in time if I had to place a bet on what I think the next decade will bring I might as well toss a coin. I think solar will have a cooling influence but to what degree I couldn’t tell. I think CO2 also provides a not insignificant degree of forcing too so I’m not sure how things will balance out. The longer term I’d probably bet my house on cooling.

    What does worry me is if Camp and Tung found an average 0.2C temp amplitude for the last 4 solar cycles of the 20th century I suspect the accumulated energy reduction from 2 very quite solar cycles might see us lose far more than 0.4 C. If the temp drops 0.2C in 5 years during the path to solar minimum, what is going to happen when it drops to minimum and remains there for 20 years? How much of the current global temp is represented by 5 decades of historically strong solar activity (note I don’t say unprecedented). Will the rate of temp decrease remain constant. Will it accelerate will it decrease? How much reliable data do we have from history.

    Have we had 2 very quite cycles that followed a period of 50 years of strong cycles in the past? If the Lean reconstruction of TSI is to be believed it shows that at least over the past 400 years we’ve seen nothing like the rapid transition from a sustained period of strong solar activity to very low activity that were just about to see.

    The Lean TSI reconstruction shows that the transition into the Dalton minimum was preceded by TSI levels considerably lower than those seen in the later solar cycles of the 20th century. Likewise the transition into the Maunder minimum. As far as I can tell the solar transition were about to encounter is not something that has a mirror over the past 400 years. Beyond 400 years its a little more murky. The TSI and temperature reconstructions are far less reliable.

    It would have been nice to have a clearer understanding of how much the current temperature level is a result of 5-6 decades of solar forcing. Instead everyone has been focused on CO2 so the answers really aren’t clear. We will find out in coming decades.

  74. Bill Illis says:
    August 26, 2013 at 1:13 am
    We have another line of evidence on the temperature stability timeline.

    That of the lower stratosphere temperatures. These have now been stable (perhaps increasing slightly) since the start of 1995 after they reached their new equilibrium level post the Pinatubo eruption.

    The stratosphere is supposed to cool in global warming theory. But it has been stable for going on 18.5 years now.

    Nice sleight of hand there Bill, you quoted data for the Lower Stratosphere and implied that this represented the whole Stratosphere! If you look more carefully you’ll see that the upper Stratosphere in fact shows a sharp decline.

    http://www.ssmi.com/msu/msu_time_series.html

  75. Pam – You need to get past your fixation on sunspot numbers, which don’t work, to the [INTEGRAL] of sunspot numbers which works. It works because the equation is physical; an expression of conservation of energy.

    The TSI effect, which is what most are talking about, happens to be complimentary but is an insignificant factor.

  76. David W says:
    August 26, 2013 at 8:08 am
    What does worry me is if Camp and Tung found an average 0.2C temp amplitude for the last 4 solar cycles of the 20th century I suspect the accumulated energy reduction from 2 very quite solar cycles might see us lose far more than 0.4 C.
    The solar cycle is cyclic, so after each cycle the temperature is back to where it was.

    If the Lean reconstruction of TSI is to be believed
    I don’t think it is to be believed. Lean has made several recontructions of TSI and each new one has had a smaller variation. In one of her presentations she says: “longer-term variations not yet detectable…do they occur?”
    http://www.leif.org/research/Does%20The%20Sun%20Vary%20Enough.pdf slides 15 and 16.

    My views on solar activity the past several centuries are summarized here http://www.leif.org/research/swsc130003p.pdf
    I end with:
    “Observations by Livingston and Penn since 1998 until the present show that the average magnetic field in sunspots has steadily decreased by 25% (Livingston et al. 2012), regardless of the fact that we are now again at the maximum of a solar cycle, so there has not been a solar-cycle-related reversal of the trend. Since their magnetic fields cool sunspots, a decreasing field means that sunspots are getting warmer and that their contrast with the surrounding photosphere is getting smaller, making the spots harder to see. There is a minimum field strength in visible spots of about 1500 Gauss (0.15 T) and as that 1500 G threshold is approached, magnetic fields appear at the solar surface which do not seem to form dark sunspots or pores. Owens et al. (2012) suggest that the photospheric flux emergence in such cases may take place in flux tubes with field too weak, or of too small a diameter, to form sunspots, citing Spruit (1977). The observed distribution of number of spots vs. field strength has been shifting steadily toward that limit. If, and that is a big IF, this trend continues, the number of visible spots in the next cycle (and perhaps beyond) may fall to values not seen since the Maunder Minimum, but without dramatic changes in the emerging magnetic flux. Without the dark spots, Total Solar Irradiance might even be a bit higher. It is not clear what this will mean for the impact of solar activity on the Earth’s environment, if any, but it portends exciting times for solar physicists.”

  77. Dan, my logic was entirely valid and within the context of your preceding comment which referred to SSN and was very much a part of the link you provided.

    It’s your fixation, not mine. Are these not your words copied from your link?

    “Conclusions

    This assessment demonstrates that the annual average temperatures of the planet, for at least as far back in time as accurate temperatures have been measured world wide, are accurately calculated by considering only natural oscillations and the sunspot numbers, and that credible changes to the levels of non-condensing greenhouse gases have no significant influence on average global temperature.”

  78. Dan Pangburn says:
    August 26, 2013 at 9:16 am
    Pam – You need to get past your fixation on sunspot numbers, which don’t work, to the [INTEGRAL] of sunspot numbers which works. It works because the equation is physical; an expression of conservation of energy.
    Apart from your physics being wholly, the integral doesn’t work either. Here is a plot of the integral of the sunspot number’s deviation from their mean value [if you just integrate the SSN you get an ever-rising curve which clearly is nonsense]: http://www.leif.org/research/Roger-Integral-Comparison.png Where is the high temperatures in the 1930s, for instance? And note the strong maximum around 1790 [even higher than today].

  79. The global cooling trend will pick up as this decade proceeds, and the prolonged solar minimum becomes more established.

    Their theory will be obsolete before the decade ends.

    solar readings needed for cooling sustained following several years of sub-solar activity

    solar flux sub 90
    ap index 5.0 or lower
    solar wind 350 km/sec or less
    solar irradiance off .015% or more
    UV light off upwards of 50%

    Those solar conditions if persistent enough should along with the secondary effects associated with those solar conditions set the climate toward a definitive cooling trend going forward.

  80. Pam – I’m not questioning your logic and perhaps ‘fixation’ was a poor choice of words. I am trying to convey that while SSNs don’t work the INTEGRAL of SSNs works astoundingly well (Of course, the radiation from the planet must be subtracted out which the next part of the equation does). The equation does the (numerical) integration.

  81. Salvatore Del Prete says:
    August 26, 2013 at 9:53 am
    The global cooling trend will pick up as this decade proceeds
    This proves my point about the wishful thinking flying in the face of the fact of ‘flat RSS’.

  82. Dan Pangburn says:
    August 26, 2013 at 10:02 am
    Pam – I’m not questioning your logic and perhaps ‘fixation’ was a poor choice of words. I am trying to convey that while SSNs don’t work the INTEGRAL of SSNs works astoundingly well
    Well it doesn’t.
    Apart from your physics being wholly, the integral doesn’t work either. Here is a plot of the integral of the sunspot number’s deviation from their mean value [if you just integrate the SSN you get an ever-rising curve which clearly is nonsense]: http://www.leif.org/research/Roger-Integral-Comparison.png Where is the high temperatures in the 1930s, for instance? And note the strong maximum around 1790 [even higher than today].

  83. Bravo. This has been one of the very best discussions EVAH!

    Allan MacRae says:
    August 26, 2013 at 2:50 am: “…I suggest that global warming hysteria will soon be fully discredited, and its advocates will be held responsible for our lack of preparedness should global cooling occur….”

    One hopes you are correct on two accounts (discredit and attribution of responsibility) but wrong about cooling of any significant sort occurring (if that is something you are in fact projecting).

  84. Dr Svalgaard:

    I “think” what these latest writers are trying to propose is the following:

    They believe, or think that they have observed, or have actually found that the number of solar cycles have increased recently, and that the maximum number of sunspots in these “faster” cycles has changed from the previous period when temperatures were declining or rising before.

    -> Which means they believe there is are more cycles recently, so each cycle with a shorter cycle length than the normal 11 year length. This would mean that, for example, 17-18-19 are slower (longer period) and lower (fewer sunspots) than the group 20-21-22. Now, in the last 15 years, the 23-24 cycles in the period we are in now are even longer and much lower than 20-21-22.

    Thus, their theory would hold that: if you integrate several different a series of sunspot cycles, then divide that integral over the same number of years each time, you’d find that the “average integral” – if you want o coin that term – of sunspots per time is changing, and that change corresponds to the past century’s changes in global temperatures: increasing at times, steady at times, and decreasing at times.

    Now, I don’t know if this works or not: Maybe it works if you use 33 years (over three normal cycles), or if you use 22 or 11 as the length. Alternately, a shorter cycle with the same peak number of spots means that, over the same length of time, you get more sunspots total. If – BIG IF THERE – sunspots do relate to global temperatures, the latter seems logical, but not necessarily correct!

    After all, is not the entire CAGW dogma based on extrapolated “logical” thoughts “projected” into the fat future with “simplistic” straight lines?

  85. Isva – The physics is correct and has been peer reviewed.

    An earlier version of the equation, with more-detailed description of its derivation can be seen by searching ‘Verification of natural climate change’. I can’t determine what Leif did but the correct graph of the equation is shown as Figure 1 in the climatechange90 link.

  86. Dan Pangburn says:
    August 26, 2013 at 10:25 am
    The physics is correct and has been peer reviewed.
    How many peer-reviewed papers are there promoting AGW?
    The ‘equation’ is just curve fitting with many parameters [enough to wiggle the elephant’s trunk] and is not ‘physics-based’. The ‘conservation of energy’ bit is the ‘wool’.

  87. I found lots of published peer-reviewed papers on AGW. I have not found a single peer reviewed paper authored by Dan Pangburn. A blog post is not an author-vetted, peer reviewed research article. I want to see an online journal or paper journal that has a standard vetting and peer-review process of a paper submitted by Dan Pangburn. Is there such a thing? If you make the claim back it up.

    I have published in an accepted journal. Been vetted and my work has been peer reviewed. In fact it was rejected by the first journal we submitted to. It was accepted by the second after an improved re-write. But I would certainly not put that stamp of approval out there as some kind of green card that says I know what I am talking about. Having had only 1 article successfully published in a peer-reviewed paper journal is not any kind of seal of approval that I am right, even though I might say, occasionally, and only on this website, and then very rarely, indeed hardly ever, that I am right (right?).

    But let’s use Dan’s measuring stick. Heck, I’ve commented enough on WUWT to say that if you put all my comments together I have blogged in public and therefore what I have said has been peer reviewed. Seems pretty thin doesn’t it. Dan are you saying that your blogs have been peer reviewed and therefore demonstrate that your equation is right? That also seems rather thin to me.

  88. Dan Pangburn says:
    August 26, 2013 at 10:25 am
    The physics is correct and has been peer reviewed.
    Well, let us look at the sunspot term: s(i)-43.97*(T(i)/286.8)^4. The first member, s(i), varies from 1.4 to 190.2 while the second member [with T(i)] varies between 44.5 and 45.2 [both for 1895-2013]. That small variation is smaller than the error with which we can determine s(i), so already there the physics goes out the window.

  89. Werner, I have been playing with SkS trend calculator using your RSS example, from 1990 to 2013 that you have as +0.120/decade with +- 0.129/decade. Your figures do not match what the SkS calculates.

    I must be entering the wrong dates. What fractional (decimal) dates did you enter into the ‘Start’ and ‘End’ fields at SkS?

    Thanks.

  90. RACookPE1978 says:
    August 26, 2013 at 10:20 am
    ” Which means they believe there is are more cycles recently, so each cycle with a shorter cycle length than the normal 11 year length. This would mean that, for example, 17-18-19 are slower (longer period) and lower (fewer sunspots) than the group 20-21-22. Now, in the last 15 years, the 23-24 cycles in the period we are in now are even longer and much lower than 20-21-22. ”

    First of all, there is no “normal” 11 year cycle. Second of all, I have no idea what the rest means. Have a look:

    No Length SSN
    1 11.0 87
    2 9.0 106
    3 9.2 154
    4 13.6 131
    5 12.1 47
    6 12.9 46
    7 10.6 71
    8 9.6 138
    9 12.5 125
    10 11.2 96
    11 11.7 139
    12 10.7 64
    13 12.1 85
    14 11.9 66
    15 10.0 104
    16 10.2 78
    17 10.4 110
    18 10.1 152
    19 10.6 190
    20 11.6 105
    21 10.3 155
    22 9.8 158
    23 12.1 120

  91. Pam – Congratulations on getting all the way through the process.

    As I said, the physics has been peer reviewed (it is a straight-forward application of the first law of thermodynamics and some calculations using readily available data). The paper has not yet been published.

    I have yet to see a single paper that actually demonstrates AGW without using the results from GCMs. There are lots of things wrong with the GCMs. I discuss some of them in http://consensusmistakes.blogspot.com/. There is also a plethora of published papers that describe various catastrophes IF the planet warms much more.

    Hundreds of billions of dollars have been wasted in failed attempts using super computers to demonstrate that added atmospheric CO2 is a primary cause of global warming and in misguided activities to try to do something about it. A lot of reputations are at stake. It is not going down easy.

    The CO2 level continues to go up while the average global temperature doesn’t. Apparently, the separation between the rising CO2 level and not-rising agt will need to get much wider for the AGW mistake to become evident to the deniers of natural climate change.

  92. JackT says:
    August 26, 2013 at 12:11 pm

    Werner, I have been playing with SkS trend calculator using your RSS example, from 1990 to 2013 that you have as +0.120/decade with +- 0.129/decade. Your figures do not match what the SkS calculates.
    I must be entering the wrong dates. What fractional (decimal) dates did you enter into the ‘Start’ and ‘End’ fields at SkS?
    Thanks.

    If you want to start with 1990 and end with the latest date, do not put in an end date but leave it blank. By putting in 2013 as an end date, you are really only going to December 31, 2012.
    In order to calculate the month where the warming is not significant, I plot the following for January to December respectively: 1989.00, 1989.08, 1989.17, 1989.25, 1989.33, 1989.42, 1989.50, 1989.58, 1989.67, 1989.75, 1989.83, and 1989.92. It turns out that 1989.50 gives: Trend: 0.124 ±0.124 °C/decade (2σ) (July). And 1989.58 gives: Trend: 0.123 ±0.125 °C/decade (2σ) (August). So I made the claim that warming was not significant since August. You may ask why not July? The reason is that I cannot be sure about July. The numbers are given to 3 significant digits and 0.124 ±0.124 could in fact be 0.1242 ±0.1238 for example. This would not include 0 so I play it safe.

  93. Isv – Apparently you do not understand how numerical integration works. Your statement is not relevant.

  94. Tom in Florida says:
    August 26, 2013 at 1:28 pm

    Remember, I have no “side” or position in this discussion. I’m simply trying to determine what one possible interpretation of “integral of sunspot count” might mean.

    Maybe it matters, maybe it doesn’t matter. Don’t know.

    But, note that your value for “sunspot count” is only for the peak of the cycle, at its peak.

    How many spots – total! were in each cycle, and how long did the sunspots last in each cycle? Perhaps the spots in 20-21-22 lasted substantially longer than did those appearing now? Perhaps we have more small spots now, fewer cluster than before? We do know we are seeing a lower visible sunspots. Perhaps some other change is occurring as well.

    If I looked only at reflected light in the Arctic, but didn’t know that there were many times less cloud cover in Feb and March than in August and July, I would generate the wrong heat balance for all 4 months. Can you say we know everything about the sun’s long-term cycles today? Can you tell WHY the present cycle is so much lower than 20-21-22? We do know it IS lower, but why is it lower now, instead of for example, being lower cycle 25 or 27 instead of 24?

  95. Dan Pangburn says:
    August 26, 2013 at 2:01 pm
    Isv – Apparently you do not understand how numerical integration works. Your statement is not relevant.
    Regardless, to show that you understand your own equation, give us here for the first five years [1895, 1896, …] the values of s(i) and of 43.97*(T(i)/286.8)^4 and of T(i), as your reply was not responsive. It is a common subterfuge of pseudo-scientists to claim that nobody understands their methods and that everybody else is a moron, so show us that you do not fall in that category.

  96. Isv – Apparently you don’t see that conservation of energy is applied. In the equation, energy IN is proportional to the integral of S(i). Energy OUT is proportional to the integral of T(i)^4. The difference between them, ENERGY CHANGE, is proportional to the temperature anomaly. The excellent correlation (R2=0.9) is demonstration that the initial hypothesis (energy IN is proportional to sunspot number time-integral) was valid.

    An earlier version of the equation, with more-detailed description of its derivation can be seen by searching “Verification of natural climate change”. That might help.

  97. Werner Brozek says:
    August 25, 2013 at 2:49 pm

    (…) RSS is a satellite data set (…)

    Thanks for the reply, Werner. I was off for a while, so am a bit late in responding.

  98. Well, somebody must have entered the data calculations to get the graph you have Dan. If you were the one to enter this information for each variable and calculate the results, you should be able to pound out those first 5 data sets in about 5 minutes (and don’t be like the warmers who say they have lost the hard copies). I guess if you don’t have the first 5 years of the values for each part of the variables, who does?

  99. Dan Pangburn says:
    August 26, 2013 at 2:49 pm
    Isv – Apparently you don’t see that conservation of energy is applied. In the equation, energy IN is proportional to the integral of S(i). Energy OUT is proportional to the integral of T(i)^4. The difference between them, ENERGY CHANGE, is proportional to the temperature anomaly.
    Apart from what you just said being nonsense, you are not responsive. Please post the s(i) and T(i) for the first five years.

  100. The tired line that “this 10 warmest years were all in the last 11 years” is very irrelevant. Let’s use an analogy of a flooding river (river level compared to temperature anomaly). Once the river crests, residance don’t care that it is still higher than usual, they only care that the water level is going down. Allegidly, 2012 was the 8th or 11th warmest year on record. Well, that is great, that is well down from the peak in 1998 or 2010.

  101. Isv – I am not sure how the formatting works so here are the values that you asked for in sequence 1895, 1896…:
    S(i)
    63.9667
    41.8083
    26.2417
    26.7167
    12.1083
    T(i) (This is an average of the 4 reporting agencies normalized to HadCRUT4)
    286.741
    286.896
    286.872
    286.709
    286.825
    43.97*(T(i)/286.8)^4
    43.9337
    44.0290
    44.0139
    43.9144
    43.9854
    After applying the effective capacitance factor and the coefficient, B, the resulting influence of sunspot number on average global temperature is
    0.03622
    0.03558
    0.03046
    0.02550
    0.01631
    To this must be added the ocean oscillation effect as determined using coefficient A,
    0.175
    0.1625
    0.15
    0.1375
    0.125
    and the offset, D giving the final result
    -0.2088
    -0.2219
    -0.2395
    -0.2570
    -0.2787
    As shown in the Figure 1 graph at the climatechange90 link.

    It is an EXCEL file. I had combined the variables a bit differently. EXCEL does the heavy lifting (calculating R2 for non-linear data is especially comput intensive).

  102. rgbatduke: some exelent posts. An error I noted in your second large post. Although fresh water is most dense at 4°C, sea water acts like other compounds. It gets more and more dense until it freezes at aroung -1.7°C. I was courious about this last week, and did a bit of googling. It was kind of supprising. I figured the temperature of maximum density would very, but to find out that the anomaly compleatly dissapears was not expected.

  103. rgbatduke: Two things:

    (1) Great explanation of why I (and so many others) know without inspecting them that those models have to be wrong.

    (2) But throwing things in like “In a linear system, perhaps, although it would bother me to linearize any system that has a thermal oscillation in precise counterphase with the primary driver” is bound to make people scratch their heads. What does that mean? Surely you’re not saying a linear system couldn’t respond 180 degrees out of phase with its stimulus.

  104. Dan Pangburn says:
    August 26, 2013 at 4:03 pm
    Lsv – I am not sure how the formatting works so here are the values that you asked for in sequence 1895, 1896…:
    S(i) 63.9667 41.8083 26.2417 26.7167 12.1083
    T(i) 286.741 286.896 286.872 286.709 286.825
    2nd mbr 43.9337 44.0290 44.0139 43.9144 43.9854
    After applying the effective capacitance factor and the coefficient, B, the resulting influence of sunspot number on average global temperature is
    0.03622 0.03558 0.03046 0.02550 0.01631

    Using your numbers I get
    0.00519 -0.00058 -0.00461 -0.00446 -0.00994
    Let me do that in steps for the first number for 1895:
    1) T(1895)/286.8 = 286.741/286.8 = 0.999794
    2) to fourth power 0.999177
    3) multiply by 43.97 = 43.9338, close to yours 43.9337
    4) subtract from S(1895) 63.9667 – 43.9338 = 20.0329
    5) apply capacitance factor 20.0329/17 = 1.1784
    6) multiply by B 0.004407 * 1.1784 = 0.00519
    and so on for the other years.

    But then you forgot to integrate [doesn’t matter for the first year]. If I integrate, I get:
    0.00519 0.00462 0.00001 -0.00445 -0.01439
    Adding the A and the D has nothing to do with the sunspots, but we can add in D [=-0.4145, as it just moves the curve a bit], to get -0.40931 -0.40988 -0.41449 -0.41895 -0.42889

    Plotting everything gives me this:

    I would not call that “astoundingly well”. Actually, I would say it is “crummy” instead.
    Now, your good correlation comes from the A term which does not depend on the sunspot number, but is actually a bit of circular ‘logic’ as you inject knowledge of the climate into your formula.

  105. Well done, Dr. Svalgaard.

    I throw you a rose for your persevering patience with Mr. Pangborn. LOL, first he calls you “Isva,” then, “Isv”. To your glory, you overlooked his insults. Leif Svalgaard knows nothing of integrals. (head shake)

    “Rock is heavy and sand a burden,
    but the provocation of a fool who can bear?”

    WAY TO GO, LEIF SVALGAARD! (yes, I SHOUT it, #(:))

    (and Pamela Gray and others, too!)

    P.S. I was so relieved to read your comment at 4:29pm on August 25th. For months, I have wanted very much for you to be one of the “good guys” (defined: one NOT promoting CAGW). Until this evening, I was not sure; you only seemed to be adamant to not let us anti-CAGWers use the Sun to argue against CAGW and that implied (I did not conclude) you were pro-CAGW. I’m so glad to discover that you who were not (overtly) for us were not against us.
    .
    .
    .
    “Dan’s Folly” lol. Sounds like a name for a race horse. Hm.

    OKAY, OKAY!

    Back to science!

  106. JustAnother says:
    August 26, 2013 at 12:37 pm
    I think rgbs mini essays are utterly brilliant

    Me too.

  107. Werner,

    Using RSS 1990 & ‘blank’ @ SkS: .120 +-.129
    Using RSS 1990 & 2013.5 @ SkS: .121 +-.130
    Using RSS 1990 & 2013.42 @ SkS: .121 +-.131

    Then tried the following:

    Using 1990 & 2013: .123 +-.125
    Using 1990 & 2012.92: .127 +-.135

    Obviously the SkS trend calculator is interpreting the ‘End’ date differently if it is ‘blank’. And entering just ‘2013’ with no decimal produces a number that’s neither for July (2013.5) nor for December (2012.92) – my guess is that ‘2013’ represents end of month January 2013.

    Anyways, based on this tiny experiment, I’m not confident what time period ‘blank’ really represents when used as ‘End’ and SkS provides no confirmation of what time periods are being used in the calculations (not sure if that’s a bug in the design or a feature).

    For future users of SkS, I would caution against using ‘blank’ and instead rely exclusively on the decimal dates you supplied for each month.

  108. But, our “camp” is not trying to hijack the world economy, virtually shut down western industry, transfer wealth from producing countries to failed countries, and silence real discussion about the climate. That is the difference, so it might have been more worthwhile if you had said ” thus, now warming”.

  109. oops- meant to say “no warming”. At a minimum, couldn’t we agree that the science is not settled?

  110. JackT says:
    August 27, 2013 at 5:23 am
    Werner,
    Using RSS 1990 & ‘blank’ @ SkS: .120 +-.129

    This is the number I gave. To prove it is correct, you can put in any date after July 2013 and you will get the same answer. For example put in 2013.58 or any higher number such as 2014, and you will get the above number. The way to prove to yourself exactly what numbers are being used, you need to know what the numbers for RSS are. The last 3 months in RSS are 0.139, 0.291 and 0.222. So if you see an uptick followed by a down tick at the end, you know you have the latest. As for just putting in 2013, that is just to January 1, 2013. To prove this, 2013 gives the same number as 2012.99.

  111. In terms of research, when you want to consider the effects of a tiny variable, don’t include the big variable in the recipe. So your first step is ALWAYS to consider how to exclude the big variable, in this case the very thing that predominantly determines land temperatures. The big cahoona is the oceanic/atmospheric sourced driver of weather pattern variations.

    The CO2 crowd and Dan make the same mistake but in different ways. They fail to properly remove the effects of the big variable so they can study a tiny little variable. The CO2 crowd thinks that oceanic/atmospheric variables are random and will cancel out if you run the model enough times (we do this with brainwaves). But oceanic/atmospheric variables are not random and they do not cancel out. Dan actually keeps the big variable in his calculation by incorporating a value based on actual observations that is different for each observed year, thus burying his tiny gnat of a variable in a room he has purposely filled with very large elephants. To make matters worse, he then proclaims that the poop in the room is being influenced by his gnat.

    Weather, and thus climate, is a savory soup you cannot undo once it is cooked. Anyone who tries to pick apart the soup, aka weather data, into its original separate driving components is nuts.

  112. Dr. I – Thanks for checking EXCEL’s arithmetic. I looked back to see why you got different numbers. My bad. I failed to mention that I started the integration from 1850. My feeble excuse is that I did the work a few months ago. The integral 1850-1894 (including the 43.97 & T^4 factors) is 105.6212 so add this to 20.0329 = 125.6541.
    125.6541/17 = 7.3914.
    I used the factor for no CO2
    7.3914 * .0049 = 0.03622 as stated.
    If I had used the factor including the CO2 effect it would be
    7.3914 * 0.004407 = 0.0326 but the difference on the graph would be barely detectable.

    The equation and graph at the climatechange90 link are correct.

    Sorry about the missing information and wasting your time. If I could figure out how to publish the EXCEL file I would do it. That might reduce this kind of foolishness.

  113. Dan Pangburn says:
    August 27, 2013 at 9:22 am
    My bad. I failed to mention that I started the integration from 1850. My feeble excuse is that I did the work a few months ago.
    So much for so-called peer review…
    BTW, which journal did you submit the paper to?

    The equation and graph at the climatechange90 link are correct.
    If you mean this link:

    http://climatechange90.blogspot.com/2013/05/natural-climate-change-has-been.html

    The equation states that the integration started in 1895. The graph starts the ‘calculated’ curve in 1880. So much for ‘correct’.

    Your link says:
    “43.97 = average sunspot number for 1850-1940.
    286.8 = global mean surface temperature for 1850-1940, °K.
    294.8 = ppmv atmospheric CO2 in 1895

    To be ‘correct’ all these things should be consistent.
    And why use 1850-1940 averages. One would expect 1850-2013. The 1940 is too arbitrary.

  114. Nick Stokes says:
    August 25, 2013 at 5:12 pm

    I tried it out, but the numbers did not match for what I knew to be true for UAH from 2005 to date from WFT and SkS. But when I realized the following, it made sense.
    “Update –  data has been updated to Jan 2013 (where available), and Hadcrut 4 replaces Hadcrut 3.”

    With my monthly updates, I have to have the very latest available so I cannot use your product for my purposes.

  115. Dr S – Sorry about the name tag errors. I misread the first character in your earlier posts as an upper case ‘I’ instead of a lower case ‘l’. I also apologize for being unfamiliar with your work. That will change.

    Thanks for checking MY work. It looks like you caught something that was missed in peer review. I agree that the ‘integration’ should have been zero in 1894 to be consistent with the equation. I fixed it in one of the EXCEL files and it appears to make a tiny bit of difference. The most noticeable difference is a prediction of the trend to be approximately 0.05 K cooler in 2020. The coefficients shifted a bit but R2 is still 0.9 (very tedious to walk the coefficients up to max R2). I will be sure to correct the paper before it gets published.

    The coefficients, A, B, C, D, were determined for max coefficient-of-determination for the equation compared to the data from 1895-2012. After the coefficients are determined, the results of the equation can be plotted for any time period. Starting the plot in 1880 is interesting but arbitrary.

    1940 was picked because that is where the sunspot number time-integral starts its rapid climb (which ended about a decade ago). Graphs that show this can be seen at http://hockeyschtick.blogspot.com/2010/01/blog-post_23.html or at http://climaterealists.com/attachments/ftp/Verification%20Dan%20P.pdf (this shows an earlier version of the equation and HadCRUT4 data was not used. This also shows CO2 data. Mauna Loa data was used when available.)

    It appears from the equation that using a different time range would change the values of the coefficients but not influence the value of R2 or the anomaly ‘prediction’ or the graph trace. The prediction is in quotes because of uncertainties in the future sunspot time-integral and uncertainty that ocean cycles will continue as they have for more than a century. I expect the ocean cycle factor to fade eventually.

    It is the influence of the change in CO2 that is under investigation. Since 1895 is the start point, it is the change from 1895 that is needed. I rechecked to make sure that I did this correctly in EXCEL.

  116. Dan Pangburn says:
    August 27, 2013 at 2:07 pm
    1940 was picked because that is where the sunspot number time-integral starts its rapid climb (which ended about a decade ago).
    Cherry picking 1940 because of some property of the data invalidates the whole analysis. There is no way to ‘save’ the analysis except doing it right, that is: having the same begin and end times for all data and for all averages.

  117. Dan Pangburn says:
    August 27, 2013 at 2:07 pm
    It looks like you caught something that was missed in peer review.
    which journal did you submit your work to?

  118. Nick Stokes says:
    August 25, 2013 at 10:01 pm

    RGB
    “I agree that the GISS document is remarkable and subversive. It is also wrong, rather horribly wrong. “

    It’s neither remarkable nor subsersive. It is something Hansen has been saying for over 30 years. The NOAA has a very similar statement (see para 7).
    ———————-

    You are aware are you not that Hansen is a raving lunatic?

    The loon imagines that the oceans of Earth could boil & our planet become another Venus at 500 to 600 ppm (or less), even though the Cenozoic high for CO2 was around 2500 ppm, without any such dire consequences having happened then. I might add that solar radiance was practically the same as now when our planet last experienced that level of carbon dioxide (about 42 Ma; the sun gains strength at about one percent per 110 M years).

    Nor of course did Earth become Venus when CO2 was 7000 ppm or 90,000 ppm (or more) in the past five to seven hundred million years.

  119. Dan, trust me, been there, done that. If you want to submit that pdf for publication with just a tweak here and there, you are in for a very sad experience. However, on the bright side, because it is so far away from any kind of serious consideration, it will be a very short, sad experience. Mine was more than a year’s worth of rewrites for journal publication AFTER a year’s worth of rewrites just for the University’s archive publication. That it eventually got considered at all for professional journals is likely due to the addition of a very talented and well-respected researcher who made the manuscript sing with discussion. It was a humbling experience. While he said my data was a well-controlled “gold-mine”, I had a long way to go in interpreting the results. How right he was.

    By the way, one of the hallmarks of a true researcher, let alone a Ph.D., is that you get to say on a regular basis that you don’t know something and therefore you need to study it. Else why would any of us ever do research? You seem convinced a priori that the Sun is the deciding factor, so you came up with a calculation that in your mind shows it. That makes you not a researcher. And you would be joining the ranks of several AGW researchers who have done the same thing.

    Spare yourself the embarrassment. Do not let your manuscripts see the light of day.

  120. Dear Pamela Gray,

    If you would ever care to share, I’m sure many of us would enjoy hearing about your research (in summarized, layperson’s language if I, at least, am to understand it). Perhaps, when this thread goes essentially defunct (if you don’t mind going OT, go for it, now!), you might feel comfortable posting about yourself, here? Please forgive me if this comes off as too nosy.

    An admirer from the “cheap seats,”

    Janice

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

    @ Dan Pangburn — I apologize for accusing you above of deliberately misusing Dr. Svalgaard’s name. Good for you to tell him that you did not mean to do that. You may be mistaken in your research, but, at least you are (it appears, anyway) willing to learn. (Your initial arrogant tone created a bad impression). GOOD LUCK!

    *****************
    @ Leif Svalgaard — your silence tells me you thought little of my praise above. If I offended you, please forgive an overenthusiastic encourager (sometimes, it is a blessing, sometimes, not).

  121. Janice Moore says:
    August 27, 2013 at 3:06 pm
    @ Leif Svalgaard — your silence tells me you thought little of my praise above. If I offended you, please forgive an overenthusiastic encourager (sometimes, it is a blessing, sometimes, not).
    On the contrary, it was appreciated, but my experience is that it is better just to humbly bow one’s head when praise is heaped upon it.

  122. Well, good for you, Dr. Svalgaard. But, LOL, I can’t “hear” you bowing, you stoic, stalwart, Dane, you! #(:))

    Thanks for taking the time to respond.

    Janice

  123. Janice Moore says:
    August 27, 2013 at 3:19 pm
    I can’t “hear” you bowing, you stoic, stalwart, Dane, you! #(:))
    You can’t hear me cringe either at times, when that is called for.

  124. Janice I am nothing but a flash in the pan. I decided to do research for my Master’s thesis. It gave me quite more than I wanted to learn, including leaving me jaded about the political nature of Ivory Tower research. Maybe I was just too young and idealistic to be able to survive that cauldron. Those who do have my respect.

    Fausti was Head of the Audiology department at the VA medical center I was employed at. He chose to put his name first, I don’t know why. Frey was a colleague who taught me lab techniques, and Rappaport helped me with my manuscripts. Oregon State University has the original thesis archived in its library.

    Fausti SA, Gray PS, Frey RH and Rappaport BZ. (1991). Rise Time and Center-Frequency Effects on Auditory Brainstem Responses to High-Frequency Tone Bursts. J Am Acad Audiolo 2:24-31.

    Gray PS. (1986). Rise-Time and Center Frequency Effects on the Auditory Brainstem Response. A Masters Thesis, Oregon State University, Corvallis, OR.

  125. Werner Brozek says: August 27, 2013 at 1:41 pm
    “I tried it out, but the numbers did not match for what I knew to be true for UAH from 2005 to date from WFT and SkS. But when I realized the following, it made sense.
    “Update – data has been updated to Jan 2013 (where available), and Hadcrut 4 replaces Hadcrut 3.”

    With my monthly updates, I have to have the very latest available so I cannot use your product for my purposes.”

    My apologies – that update needs changing. I have recently instituted a continuous data updating scheme, described here, so that is no longer true.

    I think my trends generally match those of WFT and SkS. The CI’s are often narrower than SkS. As I mentioned above, SkS uses a somewhat novel method, but I don’t thin k that should be the reason. I’ve checked mine carefully, and I think they are right.

  126. Pamela,

    At least you flashed. I didn’t even make it into the research pan! Wow! Your research (from the only closely related article I could find, a Fausti one from 2003, yup, his name was first on that one, too….) is helping prevent the SAME hearing loss (from ototoxicity) that our wonderful host has had to live with nearly all his life! How cool that you are a pillar of WUWT.

    Medical research is a golden chain; if your link had not been there, there would be people with severely impaired hearing walking around today who, instead, are singing to the music on the radio. Your link mattered. And YOU are a flash of pure golden character, intelligence, and wit.

    Thanks, so much, for responding.

    Happy fishing!

    Janice

  127. My mother’s hearing was destroyed by the very same process. She tool copious amounts of Gentamycin. Had to. Fabulous antibiotic but sometimes the cure is worse than the disease. It can harm kidneys too. And her’s were bad to begin with. By the time she hit her 20’s she had profound bilateral hearing loss.

    On the subject of the political nature of research. If you want a very good read, pick up a copy (if you can find it) of “Molecules of Emotion” by Candace Pert. She chronicles her journey as a woman in a man’s world of medical research. The last couple of chapters are a little “out there” but the understory related to the political nature of Ivory Tower research is fascinating. Brilliant woman, no doubt. Reminded me of Rosalind Franklin.

  128. Nick Stokes says:
    August 27, 2013 at 3:47 pm

    Here are the numbers I am getting. For UAH from 2005 to date, WFT gives -0.00033/year and I know they are still using the 5.5 version.
    SkS gives +0.013/decade +/- 0.528 and I know they are using the 5.6 version.
    For yours, when I click UAH from January 2005 to August 2013, and the 1989-now and the trend button, I get 0.243/Century. What am I doing wrong? I assume you are using version 5.6 so it should be like SkS, unless of course SkS is either wrong or using a different program. And how do I get the +/- values with your program? Thanks!

  129. Dear Pamela,

    Thank you for sharing about your mom. So, you are bi-lingual (at least), I would guess, for you likely are fluent in ASL (?). I took a beginning ASL class (just in case I ever needed it — still haven’t!) and the hearing teacher’s parents were both completely deaf all his life. It really does a number on the family dynamics, at times! You were, no doubt, highly motivated (like Alexander Graham Bell!) and that must have helped you with all those long hours of often tedious measuring and recording and on and on and on…. . I hope she is still with us. If not, I’m sorry that you have had to say “Good bye” to her, too (yes, I remember what you wrote a few months ago and you’ve been in my prayers — big holes in the heart never completely heal, you just forget about them for awhile). She certainly raised a girl who can stand on her own two feet. Go, Mom!

    Thanks for the book recommendation. If I have the opportunity, I’ll read it. I hope things, as far as the sexism, anyway, have improved. We (you and I) owe so much to the pioneers. Even though there were always some good, fair-minded, men in academia (Marie Curie’s husband, for instance), it was not easy.

    Thanks again for honoring me with a response!

    Take care,

    Janice

  130. Werner Brozek says: August 27, 2013 at 5:21 pm
    I get the same as you. I am using UAH 5.6 now; the automatic update (which is new) ran last night. There are actually some glitches; some of the later options, like SST aren’t getting the new data. I’ll fix that. But the datasets you’re using should be OK.

    I’ll look into the reason for the discrepancy. The +- valies appear on the sidebar, where it says CI from … Below that, it gives the t-value – ie in sigma units. You can also click for a color plot of the upper and lower CI values.

  131. Pam – Thanks for the advice. The paper is substantially more comprehensive than the pdf and has been through peer review (although with a dumb error as Dr. S helped uncover which needs to be fixed). I won’t know for sure whether it will be published until it happens.

    You might wonder why an old, retired, unfunded engineer has been doing research in global warming (for over 6 years now). Initially I was just curious about the truth. Now I’m concerned about some politicians needlessly destroying the economy.

    Many fail to accept that I did not start with the assumption that it was the sun. Instead I started with the energy equation. I suppose the misconception happens because I didn’t talk about the energy equation much in the pdf. I talked about it a bit more in an earlier work at http://climaterealists.com/attachments/ftp/Verification%20Dan%20P.pdf I noticed that declining temperatures in the past were associated with fewer sunspots. I made the hypothesis (Feynman, in one of his lectures, would have called it a guess) that the time-integral of sunspot numbers was proportional to energy in. This established the form of the equation.

    The coefficients were adjusted to maximize R2. The final R2 = 0.9 demonstrates that the hypothesis was valid. After correcting the error identified by Dr. S, R2 is still 0.9 and the graph is barely changed.

    I realize that this is way different from what anyone else has done. Many seem to be convinced that CO2 has a significant effect. I demonstrated over five years ago that noncondensing ghg have had no significant influence on average global temperatures in a paper made public at http://www.middlebury.net/op-ed/pangburn.html .

    Some may be appalled by the simplicity of the concept but with an R2 of 0.9 with only one external forcing it is definitely not going away. Everything not explicitly considered must find room in that unexplained 10%.

  132. Nick Stokes says:
    August 27, 2013 at 7:18 pm

    The +- valies appear on the sidebar, where it says CI from … 

    So for UAH from January 2005 to August 2013 it says:
    Rate: 0.243°C/Century;
    CI from -2.769 to 3.255;
    So if I add 2.769 to 3.225 and divide by 2 I get +/- 3.012. So does this mean the range for 95% certainty is 0.243 +/- 3.012?
    That seems extremely high compared to SkS: +0.013/decade +/- 0.528.

    As for the glitch with SST, I noticed that too since when I clicked Hadsst2, Hadsst3 showed up and then it only went to about 2007.

  133. Dan Pangburn says:
    August 27, 2013 at 8:08 pm
    The final R2 = 0.9 demonstrates that the hypothesis was valid. After correcting the error identified by Dr. S, R2 is still 0.9 and the graph is barely changed.
    I don’t think this is true. Curve fitting often has a high R2 because the curve and the parameters were chosen to produce a good fit. Apart from the mathematical errors there is a much bigger physical error. You make a big deal out of ‘energy conservation’ and ‘thermodynamics’, but those are just words to impress [foremost yourself – Feynman also remarked that ‘the easiest person to fool is oneself’]. Here is the error: you say that energy IN minus energy OUT is the change. Fair enough, but then you assume that the sunspot number represents energy IN, and that is not correct. The yearly sunspot number varies by a factor of a hundred of more (and it should be obvious that energy IN does not vary by over a factor of a hundred – in fact, the variation is 0.1%) while the energy out represented by the temperature varies very little [of the order of one percent]. Integrating has nothing to do with it, because the balance between IN and OUT must hold for each year. You will find very nearly the same fit if you omit the T(i) bit altogether [try it]. You will find that you just have to adjust the value of D, and you get the same curve. So, change the sunspot term to (s(i) – AVERAGE(s)) and you will find the same curve [regardless of T(i)]. This is what I did in my curve http://www.leif.org/research/Roger-Integral-Comparison.png [the red curve is integrated s-AVERAGE(s); the Black area somebody else’s (Roger’s) curve]. Compare that to the result [the blue curve] using your formula http://www.leif.org/research/Dans-Folly.png . I can’t tell the difference. This shows that your idea of energy IN and energy OUT is wrong (which was obvious to me from the outset).
    And please tell us which Journal you submitted the paper to. I have asked you now three times. Failure to respond will be taken as admission that no paper was submitted and peer reviewed.

  134. Dan Pangburn says:
    August 27, 2013 at 8:08 pm
    The final R2 = 0.9 demonstrates that the hypothesis was valid.
    A note on integration [of which you claim I know nothing] and my graph http://www.leif.org/research/Roger-Integral-Comparison.png . The blue and pink curves are two reconstructions of the sunspot number [they are hardly different, so I can just take the average]. Calculating the average sunspot number for the interval of integration [1749-today] and subtracting that average gives me the yellow curve, which I integrate from 1749 yielding the heavy red curve. Since the yellow curve has as much area above zero as below zero, the integral over the whole interval will by definition by zero [as is also evident from the figure] and will also be zero at the left edge [as there is nothing to integrate over yet], so any interval over which you integrate [s(i) – AVERAGE(s(i))] will always start at zero and end with zero, which BTW shows that integration as such [i.e. from a fixed point far back in time] is a meaningless thing to do. If you want to integrate you should use a sliding [fixed] window that you move along, the assumption here is that heat is stored for a while only.

  135. Allan MacRae says: August 26, 2013 at 2:50 am: “…

    I suggest that global warming hysteria will soon be fully discredited, and its advocates will be held responsible for our lack of preparedness should global cooling occur….”

    JimF says: August 26, 2013 at 10:06 am

    One hopes you are correct on two accounts (discredit and attribution of responsibility) but wrong about cooling of any significant sort occurring (if that is something you are in fact projecting).

    Allan again:

    Jim, in 2002 I wrote in a published newspaper article that global cooling would start by 2020-2030. At that time, SC24 was predicted (by Hathaway et al at NASA) to be robust (~150-180), and it now looks very weak (~60). My friend who made the informal global cooling prediction at my request was Paleoclimatologist Tim Patterson, and it was based on his research of natural climate cycles.

    Based on more recent information including a very weak SC24 and ten more years of actual data, I suggest that global cooling could start sooner than 2020 (but we may not know this except in hindsight). In 2002 we did not predict the degree of severity of cooling, but SC24 and SC25 look so weak that I suggest significant cooling similar to that experienced during the Dalton or Maunder Minimums is a significant probability. SC25 was predicted by NASA in 2006 to be “one of the weakest in centuries”.

    As I stated previously, I hope to be wrong on this informal prediction, since society is completely unprepared for significant global cooling..

    On the other hand, I respect Leif’s informed opinion that solar variability is insufficient to drive significant warming or cooling. Let’s hope Leif is correct and my concerns of imminent global cooling are unfounded.

    Regards, Allan

    P.S. – More on SC25 at http://m.solarcycle25.com/index.php

  136. Leif, In a post above you mentioned a decline in solar magnetic field intensities associated with sunspots that would cause them to become essentially invisible optically. Previously, you have stated that proxies indicated that the solar cycles continued through the Maunder minimum despite the lack of observable sunspots at the time. In the recent post, you also mentioned that TSI would be higher due to the lack of spots and be problematic for cooling.

    Wouldn’t the lack of visible sunspots in the Maunder minimum most likely be caused by this same decline in magnetic field intensity and wouldn’t that have resulted in the Sun having greater TSI back then, just as it might in the near future? And, if one is to accept the Sun’s influence during the Maunder minimum was the driving force for the cooling, then the cause would not be reduced TSI? THen would that not suggest the cause was TSI-Albedo and that perhaps Albedo variation was due not to total TSI but rather to either magnet influence or to TSI spectral composition?

    best regards.

    cba

  137. Werner,
    I’ve tracked the reason for the glitches. The new update mechanism got the data right, but uploaded an older version of the javascript. I’ve fixed that.

    The older version had another glitch – it had the months for UAH and RSS out by one (because they start in Dec 1978). That had been fixed. That’s why you were able to show Aug 2013. The correct slope to July 2013 (last available) is 0.14 °C/cen. SkS gets 0.13 °C/cen, so they are probably using UAH 5.6.

    The discrepancy between my/SkS trend calc and WFT (-0.033°C/cen) is indeed just the difference between UAH 5.5 (WFT) and 5.6 (which I use). SkS has much larger confidence intervals which are a continuing puzzle. I checked using the amira() function in R recommended by Wayne above) which gave for Ar(1) CI’s similar to mine.

    In short, SkS and I agree on slope but not CIs; WFT doesn’t AFAIK give CIs, but has the trend for Ver 5.5.

  138. cba says:
    August 28, 2013 at 4:31 am
    And, if one is to accept the Sun’s influence during the Maunder minimum was the driving force for the cooling, then the cause would not be reduced TSI?
    It seems more likely to me that the assumption that the Sun was the driving force for the cooling is wrong. The cosmic ray modulation during the Maunder Minimum was as strong as today so the magnetic field was still there.

  139. Nick Stokes says:
    August 28, 2013 at 5:10 am

    In short, SkS and I agree on slope but not CIs; WFT doesn’t AFAIK give CIs, but has the trend for Ver 5.5.

    Is it possible that you and SkS are talking about different percentages within the CI? As far as I know, if SkS says that if the slope is 0.013 +/- 0.528, then there is a 95% chance the real value is in that range. If your site were to say the same thing, is it also 95% or perhaps 90%? And if there is a discrepancy, which is the one Phil Jones uses?

    The SkS site has very recently discontinued Hadcrut3 and I see that you also do not have Hadcrut3. SkS never did have Hadsst2 nor Hadsst3, however I see that you have Hadsst3 up to date now on your site. I expect my next report to be in about 2 months. I will consider switching from Hadsst2 to Hadsst3 and use your site, at least for Hadsst3 if I am satisfied your CIs are in the ball park. Thank you!

  140. Hello Leif,

    I hope you are well.

    I recall our conversation of 2009 below, and had one further thought.

    I said: “Climate change is natural and cyclical” to which you did not disagree.

    Let’s assume you are correct, and solar variation is apparently too small to be the driver of global warming and cooling.

    Let’s further assume you are correct and global warming and cooling cycles are just somewhat random cycles, and “it just goes up and down”.

    Here is my thought:

    Maybe in a natural cyclical system such as the global climate cycle that just goes up and down, the small influences of the Sun are enough to, on a somewhat irregular basis, influence the climate to move from a warming to cooling phase and vice-versa. This could explain the less-than-perfect relationship nature of observed global warming and cooling with respect to the solar cycles, for example the somewhat irregular cyclicity of the PDO, AMO etc.

    This would seem to be consistent with the nature of chaotic systems – something causes them to change, but that cause can be apparently be quite small, and not always predictable, especially in time.

    Best, Allan

    http://wattsupwiththat.com/2009/01/10/polar-sea-ice-changes-are-having-a-net-cooling-effect-on-the-climate/#comment-74024

    Allan M R MacRae (19:49:11) :
    Climate change is natural and cyclical

    Leif Svalgaard (19:57:40) :
    I would not disagree with that, except for downplaying the ‘cyclic’ bit. I don’t think there is strict cyclicity, just that it ‘goes up and down’.

    ___________________

    Allan again:
    Agree the up-and-down cycles are less than perfect – although there is something of interest in the PDO and/or Gleissberg – and possibly also in longer cycles but I haven’t looked at them.

  141. Allan MacRae says:
    August 28, 2013 at 9:25 am
    Maybe in a natural cyclical system such as the global climate cycle that just goes up and down, the small influences of the Sun are enough to, on a somewhat irregular basis, influence the climate to move from a warming to cooling phase and vice-versa.
    Maybe, perhaps, possibly, etc…
    Without a mechanism for such ‘nudges’ I would not attach much significance to hypotheticals. But, on the other hand, since we don’t know, anything is possible :-) [quoting Al Gore, I think]. For me, the issue boils down to ‘predictability': can we use the nudge to successfully predict what the outcome will be? If not, we cannot react to it, mitigate it, do something about it, plan ahead, etc… and the practical aspects wane.

  142. Werner,
    “Is it possible that you and SkS are talking about different percentages within the CI?”
    There is a very small difference. SkS uses 2σ, I use 95%. Both are common and often treated as the same, but 95% is actually 1.96σ, which is what I use. I don’t think that’s the reason.

    SkS doesn’t get the same as Phil Jones in that much discussed calc. That’s discussed in the thread at SkS – this is a good starting point. It seems clear Jones was using Ar(1), probably via the Quenouille method, which I use. That process goes back to about 1953, and is widely used. Mine agrees with Jones.

    I’ve left a comment as SkS on that same thread, and the response is that they are, following Tamino, using ARMA(1,1). So I checked that, and it does make a very large difference. It’s actually the c(1,0,1) case which Wayne mentioned above as a possibility. So I think that is the reason for the difference.

  143. Hello Nick, I am not at all concerned about the differences between 1.96 and 2 sigma. I see you are working on things when I saw: CI from NaN to NaN
    I will check your CI numbers out in about a month and take things from there. Thanks!

  144. Leif,
    Do we not have two (Maunder * Dalton) examples where Temperatures took a dive while visible sunspots ‘disappeared’? Are there any examples of the sunspots becoming invisible where we did not experience cooling? If these are correct, it would seem much more likely that there is a causality relationship between them. Granted that the magnetic field + cosmic ray flux affecting cloud cover – either fraction or reflectivity – would seem to be the most likely candidate for the cause and having no significant variation in the magnetic field might put a bit of a damper on that idea. There are still differences, such as the makeup of the higher energy component of the radiation curve which while tiny as TSI goes, still varies by quite a large fraction.
    After all, two random variation events corresponding to a visible sunspot absence with no conflicting events would seem to be a much stronger case than a single event having a random correlation with the sunspots. It does offer a falsifiable hypothesis in that any loss of visible sunspot activity that is not associated with a cold spell would falsify this idea.
    Cloud formation and cloud reflectivity provides the mechanism for a really powerful and really messy chaotic sort of driver – unlike co2. Many things both internal and external to the Earth can influence this also.

  145. Dear Dr. Svalgaard,

    If you feel so inclined (perhaps, not until tomorrow, it’s late), your help is needed on this thread (http://wattsupwiththat.com/2013/08/28/another-paper-blames-enso-for-the-warming-hiatus/) starting after about here:

    Ulric Lyons says:

    August 28, 2013 at 8:40 pm

    Pamela Gray says:
    August 28, 2013 at 8:09 pm
    !Ulric you are joking right?”

    Not at all. With a strong solar signal you have positive AO/NAO/AAO, warm temperate zones, less warmer sea water transported to the frigid zones, and La Nina conditions/episodes, and the complete opposite with a weak solar signal, simples.

    “Strong solar signal” seems a bit inaccurate to me… .

    Thanks for taking a look at that thread and (if you do try to correct mistakes over there, THANKS!).

    Your grateful student (in the cheap seats),

    Janice

  146. Janice Moore says:
    August 28, 2013 at 10:05 pm
    “Strong solar signal” seems a bit inaccurate to me… .
    Worse. It is just hand waving without evidence by one of the ‘usual suspects’. I would not attach much significance to it.

  147. Werner,
    The NaN occurs for August, and happens because there’s no data (yet) for that month. July will work. It calculates a trend to August by regarding August as a missing value, but I will disable that, as it is correct but confusing.

    I had further correspondence with SkS. Another difference is that they calculate their correlation coefficient for the period 1980-2010,rather than the period of trhe trend.


  148. lsvalgaard says:
    August 28, 2013 at 9:24 pm
    Leif,
    Are there any examples of the sunspots becoming invisible where we did not experience cooling?
    E.g. around 600 AD, see Slide 20 of http://www.leif.org/research/Does%20The%20Sun%20Vary%20Enough.pdf

    Leif,
    Looks like a nice presentation slide set. I’m missing the relationship of my question to slide 20. It shows (as I see the wiggles) that there is a drop in TSI corresponding to an increase in T which seems to wiggle agree with C14 & Be10. Considering that 600AD shows a drop in TSI, would that not indicate visibile sunspots? What is the data there which would indicate the solar magnetic field has dropped to the level of invisible spots? Wouldn’t that drop in TSI be indicative of many visible spots? Also, what I’m not seeing concerning invisible spots versus some proxy would itself be an indication of some significant effect on Earth.
    My hypothesis is that the driver is absorbed incoming solar power which equals the TSI*(1-albedofraction) or TSI-Albedo (incoming solar power – reflected power). This Albedo is a very dirty noisy signal subject to lots of things but it doesn’t require a high sensitivity to variations in absorbed power.

  149. cba says:
    August 29, 2013 at 4:36 am
    It shows (as I see the wiggles) that there is a drop in TSI corresponding to an increase in T which seems to wiggle agree with C14 & Be10.

    I was presuming too much. We have no measurements of TSI before 1978. Nevertheless it has become convenient [?] to express solar activity in tersm of ‘equivalent TSI’. The graph in question is actually based on cosmic ray proxies [10Be and 14C] ‘converted’ to TSI using a relationship derived from modern data since 1978. So, in a sense is just a plot of ‘solar activity’ in a general sense. The Maunder and Dalton periods [cold] then show up as minima, and does the [warm] period around 650 AD. This is the traditional, generally accepted view. I have been speculating [and note that this is just a ‘wild guess’ although it makes some sense, at least to me] that perhaps TSI was not at minima during the Maunder and Dalton periods, but rather a bit higher than today [because of the lack of dark spots].

    This Albedo is a very dirty noisy signal
    Agree that the albedo is important, but I consider the albedo to be rather a consequence instead of a cause of climate changes.

  150. Leif,
    The reflected power (I use here Albedo) is half the factor that matters – that of absorbed power or TSI-Albedo. That is our real determining factor of conservation of energy and what will or must be in the form of heat and in the change of temperature necessary for balance to exist on average. It doesn’t really matter what each does on their own – TSI up or down, Albedo up or down – only the difference is going to count and it’s got to balance on the moderately short time frame or there will be warming or cooling. It would appear that some large portion of Albedo is in fact a feedback (a negative feedback) so by those horrible ipcc definitions that I prefer to ignore to avoid confusion, it could be said that Albedo will vary as a consequence of other conditions.
    Also, in reference to the solar ‘oven’, cooler spots result in less flux radiating from them. However, you have a very averaged generation of energy in the Sun that must also be dealt with on the rather short term. Just because you’re not radiating as much from the spots when present doesn’t mean the total solar luminosity can drop down. The Sun could shed produced energy in other ways, like by slightly expanding the surface to accommodate a slightly lower averaged surface T. If that is true, then the makeup of the radiation spectrum will vary and hence the TSI – Albedo absorbed by Earth can vary even if TSI actually doesn’t.
    A last comment before class. Since the majority of Albedo is cloud cover generated at current times, things can work as a water cycle feedback mechanism. In the event of major glaciation or snowball Earth scenarios, the feedback is short circuited and Albedo is always high, limited recovery to typically very long periods.

  151. cba says:
    August 29, 2013 at 10:55 am
    The Sun could shed produced energy in other ways
    What is important is really not what it ‘could’ but what it actually does.

  152. Nick Stokes says:
    August 28, 2013 at 10:58 pm

    Thank you! I will go all the way with your confidence numbers for my next article. Expect it between October 26 and November 8, depending on how fast Hadcrut3 and 4 come out. If they are really late, I may wait a few days more for the November RSS and UAH to come out. Please be prepared to answer all questions with regards to your method and why I made the correct move to switch.


  153. Leif Svalgaard says:
    August 29, 2013 at 11:10 am

    cba says:
    August 29, 2013 at 10:55 am
    The Sun could shed produced energy in other ways
    What is important is really not what it ‘could’ but what it actually does.

    Well that’s rather obvious – as is my, relatively speaking, lack of knowledge concerning the Sun and these secondary factors.
    Because the effects of Albedo variation due to cloud (and possibly other atmospheric effects) is so powerful, I don’t quite see how you can maintain the view that it is a consequence of something else. Were the EArth to have no atmospheric albedo contribution, the surface now would have something like an albedo fraction of 0.08, half of that typical of Mars or the Moon. That means 0.22 fraction is the combination of atmospheric effects giving a total of around 0.30. And, clouds are the major portion of that fraction due to the atmospheric factors. As I recall over the relatively short time frame, Palle & Goode found albedo fraction varied by as much as 10% with their efforts indicating that cloud cover is not assured to be some constant value or within a very narrow range of values. Lindzen’s efforts at one time promoted the idea that cloud reflectivity varied due to the nature of the nucleation particles suggesting that a great deal of variation in albedo can occur even with a fixed amount of cloud cover. The factor that the southern hemisphere receives a significantly greater amount of incoming solar power during a year than the northern hemisphere because of the current orbital parameters combined with the fact that most of the higher albedo fraction land mass is in the northern hemisphere and the lower albedo ocean surface is mostly in the southern hemisphere indicates that clouds are doing a tremendous effort in keeping that disparity down and the temperature difference between hemispheres minimized. Clouds, water cycle etc. has to be the 10 ton gorilla in the room.

  154. cba says:
    August 29, 2013 at 1:34 pm
    Because the effects of Albedo variation due to cloud (and possibly other atmospheric effects) is so powerful, I don’t quite see how you can maintain the view that it is a consequence of something else.
    Albedo variation is due to variations in cloud cover [ignoring for a moment show and ice cover] which in turn are due to variations of climate, so I don’t see any contradiction…Albedo is a consequence, not a driver.

  155. Werner,
    There’s isn’t really one “correct” method for calculating CI’s here. Tamino/SkS have quite a good argument to support what they do, but it may overshoot a bit on se. I’ve adopted what has been a long-time standard (AR(1) with Quenouille, which may undershoot) – there’s also the practical issue that it’s simple enough for me to program in Javascript.

    I’m planning to write a blog post on the issue.

  156. Nick Stokes says:

    “Tamino/SkS have quite a good argument to support what they do…”

    As if.

    Yo, Nick, why don’t you submit your blog post here? Then you can see what it’s like to have your argument ripped to shreds.

    So there’s your challenge. Post your article here. Find out what peer review is like in the real world.

  157. Nick Stokes says:
    August 29, 2013 at 4:13 pm

    Thank you. I have compared some numbers and the earliest date with SkS for RSS was August 1989, but yours was December 1992. And for Hadcrut4, SkS had July 1994 and yours had July 1996. That spread of two or more years is a bit more than I would have liked to have seen.
    You say one method may overshoot and the other may undershoot. Are you suggesting the ideal is somewhere in between? On the other hand, as far as I know, all of your numbers show more than 15 years at the 95% level as per NOAA’s criteria, so I will point that out in my next article. So if a method that may undershoot shows climate models to be in trouble, that makes a strong point.


  158. Leif Svalgaard says:
    August 29, 2013 at 1:46 pm
    cba says:
    August 29, 2013 at 1:34 pm
    Because the effects of Albedo variation due to cloud (and possibly other atmospheric effects) is so powerful, I don’t quite see how you can maintain the view that it is a consequence of something else.
    Albedo variation is due to variations in cloud cover [ignoring for a moment show and ice cover] which in turn are due to variations of climate, so I don’t see any contradiction…Albedo is a consequence, not a driver.

    Agreed that Albedo variation is primarily cloud cover. Cloud covers are affected by many factors – or at least hypothesized to be affected by many factors which are not variations of climate. I would think that variations of climate would be simply a difference in temperature over time.

    That I have a problem thinking about as being a factor that determines cloud cover or reflectivity which is what will change the Albedo. For one thing, the consequences of the change will render essentially a massive immediate response. A drop in T will lower the amount of cloud cover due to less h2o vapor present. More energy will come thru and where ever there is liquid h2o, you will get evaporation, heat transfer up into the atmosphere and almost assuredly, added cloud cover which will reduce the incoming power – a strong negative feedback – or more aptly in the engineering venacular – a feedback stableized setpoint control system. Too much Albedo and you’ve got a reduction of absorbed solar power and hence less power to be absorbed to drive h2o evaporation and cloud formation.
    Basically, I’m having trouble conceptualizing some sort of long term cloud cover / reflectivity shifts as being caused by some climate change. However, I can conceive of a long term change in cloud cover/reflectivity shifting the climate or rather the T to another average value. There are too many factors affecting clouds in the shorter term for there to be an actual fixed value that isn’t bouncing all over the place. It should be obvious that the cloud cover tends to have a negative feedback. There should also be a causality. Either long term shifts in Albedo cause the T shift and hence the climate change or the climate change – the T shift?- causes the Albedo long term change.
    What long term Albedo control factor do you think is controlled by the climate change?

  159. cba says:
    August 29, 2013 at 7:45 pm
    What long term Albedo control factor do you think is controlled by the climate change?
    Evaporation [for clouds]. Snow/Ice cover [glaciation]. Volcanoes [nuclear winter]. You can probably think of others.

  160. Werner Brozek says: August 29, 2013 at 5:08 pm
    “You say one method may overshoot and the other may undershoot. Are you suggesting the ideal is somewhere in between?”

    I’m basically saying there is no ideal, although if there were, then “in between” is a reasonable guess.

    I think you’ll find that it’s mainly skeptics who want to talk about statistical significance of temperature trend relative to zero, and this ambiguity is part of the reason scientists don’t focus on it. It’s really up to the people who want to talk about it to say what their version means and why they think it’s important. I quote the standard measure because I think that’s what people want.

    Normally you use stat sig when you are deducing something from observation; it saves you from misinterpreting randomness. It’s not the right consideration when you’re looking for agreement with some other theory. You can see that with Willis’ claim that UAH should no warming since Aug 94 (I think it was); he says he meant stat sig warming. But it in fact showed about 1.38°C/cen. Now it’s maybe not significant, but it’s also not so far from what AGW theory predicts. A theory can’t do better than get it right, whatever stat sig says.

    Where stat sig can be important is in establishing a discrepancy between some prediction and observations,


  161. Leif Svalgaard says:
    August 29, 2013 at 7:58 pm
    cba says:
    August 29, 2013 at 7:45 pm
    What long term Albedo control factor do you think is controlled by the climate change?
    Evaporation [for clouds]. Snow/Ice cover [glaciation]. Volcanoes [nuclear winter]. You can probably think of others.

    Whoa! Volcanoes can affect cloud covers and potentially generate a nuclear winter, affecting the climate but volcanoes are not the climate. Snow & Ice covers as in glaciation are going to short circuit the cloud feedback system by providing high albedo reflectivity at the surface negating any benefit of cloud cover reflectivity. This is important only during the glaciation phase of the climate as the cryosphere of today has a rather minimal effect due to the high latitudes. That leaves potentially evaporation and cloud formation as a climate determined (or controlled) factor. Cloud cover itself will have a significant effect on evaporation and admitedly, lower T means lower h2o vapor content. However, in the non glaciation state, a lower T with less h2o vapor and fewer clouds will result in higher absorbed power which will try to correct the situation by providing warming.
    In short, volcanoes are a factor not caused by climate change which can cause climate change. Snow & Ice as in glaciation is a short circuit of the climate setpoint system we have between glaciation periods and it is not currently in operation. Evaporation, cloud formation etc. is part of the system that will logically attempt to regulate temperature as a feedback control system and try to maintain the climate as it is despite variations in power absorption.
    Do you see how or where I might be missing your point or why we seem to be a bit at odds over the interpretations?

    best regards,
    cba
    my regards to Vera.

  162. Nick Stokes says:
    August 29, 2013 at 8:20 pm

    You can see that with Willis’ claim that UAH should no warming since Aug 94 (I think it was)

    UAH is a real problem.
    Version 5.5 has no warming since January 2005 according to WFT.
    Version 5.6 has no warming since July 2008 if I am not mistaken.
    Version 5.6 has no statistically significant warming since Jun 1993 using SkS.
    Version 5.6 has no statistically significant warming since Jun 1995 using your method.
    So Willis’ number is between yours and SkS.

  163. cba says:
    August 29, 2013 at 8:32 pm
    Do you see how or where I might be missing your point or why we seem to be a bit at odds over the interpretations?
    this comes from not being precise and specific. Let me be specific for one of the causes: assume the climate turns colder [not glaciation]. That makes the snow cover last longer and increases the albedo [at least as long as there is snow on the ground]. In fact, there is a feedback there: the higher albedo will make it colder yet, etc. To really deal with this, one needs to model the whole shebang: evaporation, precipitation, radiation, etc. Hand waving is just that.
    But going back and forth over such details detracts from the main point: was the low solar activity during the LIA a chance coincidence or not. I pointed to an example of very low activity during a warm period, and there are others. Now, you can say [I have heard that argument] that even if some events are random coincidences, others are not. That argument doesn’t do much in my book [and I think not in yours, either]. Now, can one change the albedo by changing the cloud cover by external [extra terrestrial] means such as cosmic rays? The model calculations say no, experimental verification is inconclusive, and direct measurements the past 30 years say no, so one will have to have strong faith to maintain there is an effect. And I concede that I have no such faith, because the case is not strong enough. Others may have a lower bar. That is their problem. not mine.

  164. Leif,
    Your snow on the ground will reduce the absorbed energy and so the overall total will be less and the temperature will be lower because of it regardless why or how the snow got there in the first place. Precipitation was required which means there were clouds earlier. Colder surfaces may lead to lower amounts of clouds there and hence less precipitation but Albedo has still affected the immediate area for the immediate time and potentially that my extend out into the realm of climate. I would expect clouds are way more complex to model in total than the most advanced modeling ever done on a gcm and even those are way too course geographically to deal with individual clouds.
    My response is more engineering oriented. That is we have cloud cover and we have a myriad of inputs that control or affect cloud cover. In other words we have lots of noise. Some of this noise we can maybe identify as originating from other sources, some perhaps can be quantified and hence filtered out. Unfortunately, it’s quite a coincidence that our two big cold events align with the same sort of solar event and that is compelling and makes many say they must be related. The problem is what associated with the solar event actually affected clouds sufficiently for the significant change in Albedo – or worse what combination of factors was involved – perhaps not all due to the Sun.
    Personally, after seeing your presentations concerning the lack of TSI variation, I started ignoring TSI variations as a viable alternative. The mixed results or lack of results from the cosmic ray experiments and the problems with proxies indications have me a bit frustrated over that too.
    Have you any familiarity with what pilots refer to as Cloud Glory? It’s a phenomenon occurring from backscattering off of cloud vapor droplets. It means that cloud reflectivity is a serious function of light angle and it points to the complexity of even accurately measuring the stuff.

  165. cba says:
    August 30, 2013 at 6:32 am
    Have you any familiarity with what pilots refer to as Cloud Glory?
    I have often seen a glory. From the air and even from mountain tops.
    A good friend of mine, Enric Palle has an ongoing program of measuring the albedo by observing Earthshine on the Moon. That method avoids many of the problems.

  166. doubt it could accomodate cloud glory but I check Palle out everynow and then. It’s a horrible way to try to measure Albedo but it’s probably the only actual measurements that have ever been done. Every time I’ve heard of a satellite being launched that includes serious Albedo measurements, it never achieves orbit. I can recall two over the last few years.
    The reason I mentioned cloud glory was since I’m not a pilot or frequent flyer, I ‘discovered’ it driving to work one morning. There was a lot of fog out in the fields I was driving by and the Sun had just risen in the other direction. As I drove along, I noticed that the fog always appeared the thickest as I passed by and was viewing it from the same direction as the Sun was shining from. The first person I asked about the phenomena was a private pilot who was familiar with cloud glory and told me where to find out about it on the web. Whle I was not seeing the actual cloud glory, I was seeing the backscattering as it changed while passing through 180 degrees of incidence. It was apparent that the optical thickness appeared thickest (becoming totally opaque) at 180 deg from incidence and thinner as one got further away ( permitting transmission from the other side of the point where it appeared opaque before and after passing through the 180 deg point).

  167. cba says:
    August 30, 2013 at 2:36 pm
    <i.I check Palle out everynow and then. It’s a horrible way to try to measure Albedo but it’s probably the only actual measurements that have ever been done
    Yeah, we need a satellite at L1 looking back at the Earth…

  168. Dr. S – Instead of attempting to explain it again, I will respond to your comments.
    “…R2 is still 0.9 and the graph is barely changed. I don’t think this is true.” I just finished it; it is true. R2 = 0.8982 (unchanged) for no CO2 and 0.9006 if CO2 is included.

    “Curve fitting often has a high R2…” Perhaps we differ on what ‘curve fitting’ means. To me, curve fitting means mathematically finding the polynomial (or other function) that fits the data. It is what EXCEL does and the user selects the order to use. It requires a fifth order polynomial to fit the data set with an R2 of 0.899. I did not curve fit.

    As you probably already know, curve fits have no predictive ability. That is a main reason why I did not do curve fitting. What I did do is write the physical equation using the simple concept of conservation of energy and then determine the coefficients to best match the equation to the data set. This way, the equation has predictive ability.

    “…‘energy conservation’ and ‘thermodynamics’, but those are just words to impress…” perhaps some who are technologically incompetent might be impressed but they are used because they have exact meaning.

    ‘the easiest person to fool is oneself’ I am fully aware of that and it applies to us both; well, actually to everyone.

    “…you assume that the sunspot number represents energy IN, and that is not correct” I didn’t assume anything. I made the hypothesis that the net energy IN, above (or below) the break-even energy, is proportional to the sunspot time-integral. The high R2, with only one external forcing, demonstrates that the hypothesis was correct. You may also notice that the energy OUT in the expression is that above (or below) the break-even energy.

    “The yearly sunspot number varies by a factor of a hundred of more (and it should be obvious that energy IN does not vary by over a factor of a hundred – in fact, the variation is 0.1%)” No offense intended but this clearly shows that you do not yet grasp the concept. The 0.1% is variation of TSI which isn’t enough to have the observed effect on average global temperature. But the sunspot number time integral with proxy factor, as included in the equation, does as shown in the graph. Others have looked at just magnitude or just duration and got poor correlation. The time-integral accounts for both magnitude and duration and produces the excellent fit.

    “You will find very nearly the same fit if you omit the T(i) bit altogether [try it].” In my first work on this about 4 years ago I used a constant value for T(i) which amounts to about the same thing and yes, it produces very nearly the same curve. T(i) is included to avoid the complaint of not using actual temperatures.

    “This is what I did in my curve…” You must have done something wrong because the correct curve looks very much like Figure 1 in http://climatechange90.blogspot.com/2013/05/natural-climate-change-has-been.html Fixing the error that you helped discover required new coefficients which compensated so there was no noticeable effect on the graph.

    “…the result [the blue curve] using your formula…” This looks something like what you would get if you did not account for ocean oscillation. I show this with different scale factor back to 1700 on page 3 in a paper made public 11/24/11 at http://climaterealists.com/attachments/ftp/Verification%20Dan%20P.pdf The graph on page 4 of that paper has a scale factor applied and closely matches your blue curve.

    “…your idea of energy IN and energy OUT is wrong (which was obvious to me from the outset).” The first law of thermodynamics was discovered way before my time. I have explained it to you but I cannot understand it for you.

    “Failure to respond will be taken as admission that no paper was submitted and peer reviewed.” I told you the status. Whether you believe it is not important to me.

    “A note on integration [of which you claim I know nothing] and my graph…” It doesn’t work to use the average sunspot number to today. Prior to 1940, the sunspot number time-integral (reduced by the time integral of radiation from the planet) had a fairly level trend and from 1940 to about 2005 it rises sharply. The important number in the equation is 43.97. If that number is much bigger the coefficients cannot be adjusted to make the calculated line fit the data. R2 would be lower.

    It appears that here also you did not include the effects of ocean oscillations.

    “…so any interval over which you integrate [s(i) – AVERAGE(s(i))] will always start at zero and end with zero…” That would be true if you integrated over the same range that you averaged over. Don’t do that.

    “If you want to integrate you should use a sliding [fixed] window that you move along, the assumption here is that heat is stored for a while only.” My first thought is that this is nonsense but perhaps you have an explanation.

    It is obvious that you are antagonistic to my assessment. You made graphs which you claimed proved that I was wrong when in fact your graphs are done wrong. Thus as the carbon dioxide continues to go up and the average global temperature doesn’t perhaps you will return to this and begin to understand why that is happening.

  169. Dan Pangburn says:
    August 30, 2013 at 3:04 pm
    You did not understand much, but let me note one of the biggest error:
    “It doesn’t work to use the average sunspot number to today. Prior to 1940, the sunspot number time-integral (reduced by the time integral of radiation from the planet) had a fairly level trend and from 1940 to about 2005 it rises sharply. The important number in the equation is 43.97. If that number is much bigger the coefficients cannot be adjusted to make the calculated line fit the data”
    That it ‘doesn’t work’ simply means that it is not correct what you are doing. So you are injecting into your fit the knowledge that there is a sharp rise in 1940. That invalidates the analysis and makes it circular.

    The important number in the equation is 43.97
    So you find that if you use another number things don’t work. That is precisely what curve fiddling is.

    It appears that here also you did not include the effects of ocean oscillations.
    Of course not, because that injects the observed climate into the fit and makes the argument circular.

    I told you the status. Whether you believe it is not important to me.
    You did not tell me the name of the Journal. And that is important to me.

    It is obvious that you are antagonistic to my assessment
    Not at all, I’m trying to help you avoid embarrassing yourself too much.

  170. Nick, If you are still reading here, I was working on an article and I noticed that UAH only goes to June, but RSS is up to date to July. Can this please be updated? Thanks!

  171. Werner,
    Yes, I’m still looking in. I’ll check that – thanks for the warning. I ran the automatic update mechanism again, and thought everything was OK, but…

    I’ve written a post here talking about some of these issues. I think some of the graphs there may help.

  172. Werner,
    It seemed to me to be the other way around – UAH OK but MSU lagging. I’ve fixed that, and also put in a more explanatory error message if data is not up to date,

  173. Nick Stokes says:
    August 31, 2013 at 3:22 am

    Werner,
    It seemed to me to be the other way around – UAH OK but MSU lagging.

    Nick, I am still seeing what I saw last night. Do I need some sort of refresh button or something? For RSS, I see a large uptick followed by a small down tick at the end. This is consistent with the last 3 values of RSS, namely 0.139, 0.291 and 0.222.
    However for UAH, I just see a large uptick at the end. This is NOT consistent with its last 3 values of 0.083, 0.295 and 0.174.

    (P.S. I know I said I was planning an article in about 2 months, but I may have something on RSS much sooner, depending on anomalies.)

  174. Nick Stokes says:
    August 31, 2013 at 12:28 am

    In the article that you reference, you say:

    “Conclusion
    I don’t think scouting around for a period free of significant trend is a useful activity, because it doesn’t actually prove that the theory made a bad prediction. For that you have to test the deviation from the prediction.”

    I agree with you to a certain extent, but it seems as if NOAA does not.
    ”The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.”

  175. Dr. S – Thanks for your help anyway.
    I wonder if either of us will live long enough to see who should be embarrassed.
    I need to go fix some things.

  176. Dan Pangburn says:
    August 31, 2013 at 11:24 am
    I wonder if either of us will live long enough to see who should be embarrassed.
    For some papers embarrassment is immediate. Which Journal did you submit to?

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