Note: This is my analysis of a new paper by Joe D’Aleo, I’ve tried to simplify and explain certain terms where possible so that it can reach the broadest audience of readers. You can read the entire paper here.
Joe D’Aleo, an AMS Certified Consulting Meteorologist, one of the founders of The Weather Channel and who operates the website ICECAP took it upon himself to do an analysis of the newly released USHCN2 surface temperature data set and compare it against measured trends of CO2, Pacific Decadal Oscillation, and Solar Irradiance. to see which one matched better.
It’s a simple experiment; compare the trends by running an R2 correlation on the different data sets. The result is a coefficient of determination that tells you how well the trend curves match. When the correlation is 1.0, you have a perfect match between two curves. The lower the number, the lower the trend correlation.
|
Understanding R2 correlation |
|
| R2 Coefficient | Match between data trends |
| 1.0 | Perfect |
| .90 | Good |
| .50 | Fair |
| .25 | Poor |
| 0 or negative | no match at all |
If CO2 is the main driver of climate change this last century, it stands to reason that the trend of surface temperatures would follow the trend of CO2, and thus the R2 correlation between the two trends would be high. Since NCDC has recently released the new USHCN2 data set for surface temperatures, which promises improved detection and removal of false trends introduced by change points in the data, such as station moves, it seemed like an opportune time to test the correlation.
At the same time, R2 correlation tests were run on other possible drivers of climate; Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Total Solar Irradiance (TSI).
First lets look at the surface temperature record. Here we see the familiar plot of temperature over the last century as it has been plotted by NASA GISS:
The temperature trend is unmistakeably upwards, and the change over the last century is about +0.8°C.
Now lets look at the familiar carbon dioxide graph, known as the Keeling Curve, which plots atmospheric CO2 concentration measure at the Mauna Loa Observatory:
A comparison of the 11year running mean of the USHCN version 2 annual mean temperatures with the running mean of CO2 from CDIAC. An r-squared of 0.44 was found.
The results were striking to say the least. An R2 correlation of only 0.44 was determined, placing it between fair and poor in the fit between the two data sets.
Now lets look at other potential drivers of climate, TSI and PDO.
Scafetta and West (2007) have suggested that the total solar irradiance (TSI) is a good proxy for the total solar effect which may be responsible for at least 50% of the warming since 1900. To test it, again the same R2 correlation was run on the two data sets.
In this case, the correlation of TSI to the surface temperature record is better than with CO2, producing an R2 correlation of 0.57 which is between fair and good.
Finally. Joe ran the R2 correlation test on PDO, the Pacfic Decadal Oscillation. He writes:
We know both the Pacific and Atlantic undergo multidecadal cycles the order of 50 to 70 years. In the Pacific this cycle is called the Pacific Decadal Oscillation. A warm Pacific (positive PDO Index) as we found from 1922 to 1947 and again 1977 to 1997 has been found to be accompanied by more El Ninos, while a cool Pacific more La Ninas (in both cases a frequency difference of close to a factor of 2). Since El Ninos have been shown to lead to global warming and La Ninas global cooling, this should have an affect on annual mean temperature trends in North America.
This PDO and TSI to surface temperature connection has also been pointed out in previous post I made here, for former California State Climatologist, Jim Goodridge. PDO affects the USA more than the Atlantic cycle (AMO) because we have prevailing westerly wind flow.
Here is how Joe did the data correlation:
Since the warm modes of the PDO and AMO both favor warming and their cold modes cooling, I though the sum of the two may provide a useful index of ocean induced warming for the hemisphere (and US). I standardized the two data bases and summed them and correlated with the USHCN data, again using a 11 point smoothing as with the CO2 and TSI.
This was the jackpot correlation with the highest value of r-squared (0.83!!!).
An R2 correlation of 0.83 would be considered “good”. This indicates that PDO and our surface temperature is more closely tied together than Co2 to surface temperature by almost a factor of 2.
But he didn’t stop there. He also looked at the last decade where it has been commonly opined that the Top 11 Warmest Years On Record Have All Been In Last 13 Years to see how well the correlation was in the last decade:
Since temperatures have stabilized in the last decade, we looked at the correlation of the CO2 with HCSN data. Greenhouse theory and models predict an accelerated warming with the increasing carbon dioxide.
Instead, a negative correlation between USHCN and CO2 was found in the last decade with an R or Pearson Coefficient of -0.14, yielding an r-squared of 0.02.
According to CO2 theory, we should see long term rise of mean temperatures, and while there may be yearly patterns of weather that diminish the effect of the short term, one would expect to see some sort of correlation over a decade. But it appears that with an R2 correlation of only 0.02, there isn’t any match over the past ten years.
As another test, this analysis was also done on Britain’s Hadley Climate Research Unit (CRU) data and MSU’s (John Christy) satellite temperature data:
To ensure that was not just an artifact of the United States data, we did a similar correlation of the CO2 with the CRU global and MSU lower tropospheric monthlies over the same period. We found a similar non existent correlation of just 0.02 for CRU and 0.01 for the MSU over troposphere.
So with R2 correlations of .01 and .02 what this shows is that the rising CO2 trend does not match the satellite data either.
Here are the different test correlations in a summary table:
And his conclusion:
Clearly the US annual temperatures over the last century have correlated far better with cycles in the sun and oceans than carbon dioxide. The correlation with carbon dioxide seems to have vanished or even reversed in the last decade.
Given the recent cooling of the Pacific and Atlantic and rapid decline in solar activity, we might anticipate given these correlations, temperatures to accelerate downwards shortly.
While this isn’t a “smoking gun” it is as close as anything I’ve seen. Time will give us the qualified answer as we have expectations of a lower Solar Cycle 24 and changes in the Pacific now happening.
References:
US Temperatures and Climate Factors since 1895 , Joeseph D’Aleo, 2008
Persistence in California Weather Patterns, Jim Goodridge, 2007
Phenomenological reconstructions of the solar signature in the Northern Hemisphere surface temperature records since 1600 Scafetta and West, 2007
The USHCN Version 2 Serial Monthly Dataset, National Climatic Data Center, 2007
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Oh, and Chris, you won’t win many friends (and apparently you don’t intend to) by calling them “wingnuts”.
Dear chriscolose, many thanks for the references. I’ll have a look. I’ve gotten two or three good leads now from this blog.
By the way Chris, if your actually interested in looking at ALL the data of trends from January 1998 to December 2007, Although I can’t be bothered to do GISS right now (And I’m sure it is your favorite and all the others are “wrong” somehow:
RSS:
http://i23.photobucket.com/albums/b370/gatemaster99/rsslastten.png
UAH:
http://i23.photobucket.com/albums/b370/gatemaster99/uahlastten.png
NCDC:
http://i23.photobucket.com/albums/b370/gatemaster99/ncdclastten.png
HadCrut:
http://i23.photobucket.com/albums/b370/gatemaster99/hadcrutlastten.jpg
Well, there are no negative trends but RSS shows a pretty insignificant one, and the others (Except NCDC) pretty small ones.
As a nuclear engineer and published astronomer I was asked to look at this global warming issue. My conclusion was a doubling of CO2 would merely halve the atmospheric depth required for CO2 to “do its dirty work”. So 15 feet of atmosphere needed for aborption rather than 30 feet…big deal.
Sea level rise is nearly perfectly related to simple V sub f (density change) for the highly touted 0.6 deg C ocean temperature increase. So no added water to speak of from ice melt.
Your website has made me feel vindicated.
ahh noisy, noisy. de mortuis nil nisi bonum dicendum est. two points for anyone who can show the problem with looking at this “trendline” from 1998 in Andrew’s analysis.
Oh, I know, its cherry picked! Do I win a prize? Or how about, its weather! Now do I win?
Heard it. I don’t care what the significances of the trends are, I only wish people wouldn’t lie about them.
good…then run the data through excel, and the “lack of trend” disappears. Then actually look at trends, maybe try linear regression, instead of taking big El Nino year minus some random year around 2005-2007 and concluding “global warming stopped.” No lies needed, GW hasn’t slowed down.
C
“actually 2005 and 2007 could be said to have beaten out 1998 (from GISS)”
Isn’t that because they “adjust out” El Nino? (Which is understandable, but at the same time” not the real temperature”.
Andrew/timetochooseagain: Aha.
RB: So it’s thermal expansion only? (This coincides with what grumpy old “Axe” Moerner has to say.)
“No lies needed, GW hasn’t slowed down.”
It has compared with the 1979-2000 trend. The slope is much more from 1979-2000 than from 2001 on when I run the datasets I clipped off the NASA site (2 ERSSTs and a HadCRU). Of course it’s hard to get much of a trend from so short a stretch.
Besides, that’s the measurement. What this site is mainly about is how the surface stations have been incresingly compromised from c. 1980 to date. The masurements may be dead wrong. Satellites show much more mild warming.
Evan,
run annual means from (ex) 2000-2007 with a base period of 1979-00 at http://data.giss.nasa.gov/gistemp/maps/
tamino also put up a good post on the different temperature data sets if you want to comment there, he’ll know a bit more than me on that- http://tamino.wordpress.com/2008/01/24/giss-ncdc-hadcru/
It is also not true that satellites show a mild warming (at least not on any long term scale), see IPCC Ch. 3 for much more detail on this
…and for the part I didn’t answer, 1998 was anomalously warm because of the strong El Nino; 2005 didn’t get that boost, and as for 2007, the equatorial Pacific Ocean is in the cool phase of the El Niño-La Niña cycle, and also at solar minimum. No one is ignoring these factors.
“Then actually look at trends, maybe try linear regression, instead of taking big El Nino year minus some random year around 2005-2007 and concluding “global warming stopped.””
What makes you think 1. That I “subtracted” any random years? That’s the actual monthly anomalies from each data set from December 1998 to January 2007. Yes, big El Nino year. You seemed to me to be claiming that if you drew a trend line from then to now, it would have a big positive slope. Well, you tell me, looking at the data. Is there? 2. The linear regression is already done. Apparently you are blind and can’t look at data! 3. That I reached any such conclusion? I said the trends were small, or, in RSS’s case, insignificant. Look again. 4. Yes, drawing a trend line from solar max and El Nino to Solar Min and La Nina produces unimpressive trends. But yes, it would appear that, quite literally, whether it portends anything or not, these data sets have not warmed over these periods as rapidly as in the past. What does this mean? I don’t know, maybe I don’t care. But that’s whats going on. The Solar Max/Min El Nino/La Nina is a good explanation, I think, and this does require one.
Oh yeaH?!? Well take this buddy! “I yam what I yam and that’s all what I yam.”
😀
Because it’s mostly an artifact of bad data and scientific practicies…
I believe this will answer your questions Chris… http://climatesci.colorado.edu/publications/pdf/R-321.pdf You may not like the answer.
Interesting, but it didn’t really have much to offer. As (I think) I mentioned, you’ be be much better off reading the various NAS reports on the subject, the IPCC, or a basic climatology textbook…or maybe e-mailing some of the people at GISS, or other data sets instead of the non-scientific opinions and other hogwash that sites such as surfacestations is likely to spew out. Taking photographs is cute (not really how one can assess the credibility of the data) at an extremely limited number of stations, and you can also ignore sea level rise, ocean heat content, ice loss and glacier retreat, species response, satellites, etc.
I think you’d be much better off reviewing the evidence for AGW like radiative physics, paleoclimatic analogs, etc as well as the unequivocal data showing a warming signal of roughly 0.7 K than spending too much time on climate denial blogs, which have nothing but conspiracy theories (like Jeff’s comment above), and blatent manipulation of evidence (See the swindle video), and in general just a lot of sloppy work. If you are getting much information from people who are associated with the political end of things, and show up everywhere like ExxonSecrets and SourceWatch, and have not published in the mainstream literature (Pielke is an exception, though I would not qualify him as a climate skeptic by his own admission), and are only known for their reputation of lying and/or poorly presenting evidence, then you are probably not off to a good start.
If anyone else has something productive to add, rather than how the scientific community is all frauds (which only applies to climate science, and actually that only applies to climate change, or rather that just applies to every major scientific organization and thousands of scientists who accept AGW), then there would be something to discuss. I’ll give it a few posts, I thought that one more blog might have something good to stay, but this will probably be a short visit.
MODERATORS REPLY: My goodness Chris! Perhaps then you shouldn’t frequent here. We certainly wouldn’t want any of that “hogwash” to stain your purity of thought.
Oh BTW the “extremely limited number of stations” is up to 482 now. at http://www.surfacestations.org and closing now on half of the entire 1221 USHCN set. We’ll get the majority of those. On second thought, given your comments, did you not know that http://www.surfacestations.org and this blog are run by the same person, or were you purposely insulting? Your tone of addressing people and their work certainly doesn’t reflect well upon you or gain friends here.
It seems your mind is closed to the possiblity that there could be any measurement or microsite bias in the surface temperature records. I don’t know that to be true or false yet, but I’m taking the steps to find out.
If you have a better way to determine the quality of the measurement environment of each station, then please, lets hear it.
Anthony, could you or Joe superimpose the TSI over the PDO+AMO and display the graphic showing the R^2? I think it would instructive for people to visually see the “possible” relationship between the two.
Disclaimer: Correlation is not Causation.
REPLY: I’ll see what I can do.
And your belittling of legitimate questions is typical of someone who is afraid they might be wrong.
And let’s look at some of these things. Sea level rise. It’s been pretty constant for the last several thousand years, as best we know. Show me where it has increased appreciably due to CO2? Do you think Tuvalu and the Maldives are being overwhelmed by CO2-induced warming of the oceans? Or due to local mismanagement of the protective reefs, using beach sand for construction (therefore greatly exacerbating natural erosion), or tectonic subsidence?
Glacier retreat. Gosh, I don’t know about you, but I’m sure glad those glaciers retreated, otherwise I wouldn’t have a place to live. And if you’ve actually looked, the majority of glacial retreat this century occurred before 1950, before the majority increase in CO2, at least for those glaciers scientists have kept tabs on. And of course some glaciers are advancing. You can’t lump them all in together and you can’t blame ambient air temperature for glacial retreat.
Species response. Again, I’m sure glad species respond to changes in their ever-changing environment. Otherwise they would have died off long ago, like every time winter rolled around. I suppose you’re one of those who believes that 40,000 species go extinct every year, but can’t name them.
You can continue to spew out the same old tired rhetoric, but unless you can show us something truly unprecedented and catastrophic is or even CAN happen because of a couple of tenths of a degree of temp change in SOME places, then STFU.
Correction: Glacial retreat “this century” should read “last century”.
Oh, and as for Exxonsecrets.org, they’re pretty selective in who they want to spill the beans about. And sometimes they put people on there with no mention of why they are there, except that they don’t agree with the AFW consensus. For example, Dr. Tim Ball: http://www.exxonsecrets.org/html/personfactsheet.php?id=1164
Show me where on that page it says he’s funded by big oil or any other energy company. Why is he there?
And why isn’t David Suzuki there? After all, he gets monetary support from oil and natural gas companies:
And of course there’s no factsheet on Al Gore and his imtimiate relationship with Occidental Oil, still ongoing to this day.
Sorry, anything presented by Greenpeace is pretty much a big load of garbage, especially when they have people at grocery stores telling consumers that eating GM foods can cause you to grow an extra arm or a third eye. Not only is it complete BS, it’s not even good science fiction.
Anthony, I was doing a rather unscientific comparison of the PDO+AMO to TSI by taking your two graphs and stretching them to get the time and degree scales to be the same. Just on a very rough comparison, the PDO+AMO looks to LEAD the TSI by about 5 years. This suggests to me that something else is driving PDO+AMO or that the time lag of the PDO+AMO response is really long on the order of decades. This leads me to believe that the cloud response to cosmic rays may be a better fit as to the “cause” of the PDO+AMO shift. As we have recently found out, cloud cover increases as cosmic rays increase due to the waning solar cycle not deflecting them away from the solar system. Since clouds affect albedo in a significant manner, thus the amount of energy hitting the earth’s surface, it could be that as cloud cover increases, the PDO+AMO response will be more apparent?
Could you or Joe run a R^2 on the cosmic ray count. The data is here: http://cosmicrays.oulu.fi/
REPLY: “PDO+AMO looks to LEAD the TSI by about 5 years.” I think thats an artifact of the stretching you did. Note that one graph starts at 1900 and the other at 1905 due to differences in data sets.
1900 & 1905, I accounted for that on my stretching. Like I said, it was an unscientific comparison, however, it did serve a purpose, it raised important questions. Answering those questions brings us closer to a better understanding of climate. I’m not going to use the word “Truth” since we clearly don’t have all the facts.
REPLY: Just pointing out an easy possible error. And I agree, it brings important questions forward. I’ll pass on to Joe.
Chris your work is certainly not developed from first principles, what’s the point then? My elementary text is “Thermal Physics”, Kittel and Kroemer, 2nd. edition, what do you suggest?
In any case the emmissivity of CO2 at STP is 9*10^-4, the radiative fluence directed earthward is next to nothing.
“It’s a simple experiment; compare the trends by running an R2 correlation on the different data sets. The result is a coefficient of determination that tells you how well the trend curves match. When the correlation is 1.0, you have a perfect match between two curves. The lower the number, the lower the trend correlation.”
Except you didn’t do this, you calculated the correlation of 11 yr running means which introduces a spurious correlation so your results are meaningless, maybe you should take the ASA’s advice and hire a statistician!
REPLY: Thank you for your comment. The “results aren’t meaningless” as you assert, though the R2 may be enhanced by the filtering. If unsmoothed data is used there will still be some correlation. If you look through other peer reviewed literature, you’ll find examples where this sort of running average analysis technique has been used successfully. In this case, there’s an emotionally charged reaction to the idea, which is to be expected.