Note that there is also a global meteorological-station-only record; graph can be found at the Source URL.
Posted on 08/10/2007 8:24:21 AM PDT by cogitator
There's been some ballyhoo about an adjustment to the U.S. temperature record from GISS (it will be interesting to see if the NOAA record will require a similar adjustment). What some are apparently forgetting is that the U.S. warm temperature anomaly (the Dust Bowl) in the 1930s, and the cooling of the 1960s and 1970s, was somewhat disconnected from the global temperature trends. The two graphs below illustrate this.
Global land-ocean temperature record
Note that there is also a global meteorological-station-only record; graph can be found at the Source URL.
U.S. Temperature Record 
A substantial difference can be perceived.
But why?
[Important note: First notice that the global land-ocean temperature record includes the anomalous tropical warmth of the 1930s into the 1940s, which was apparently "magnified" (see below) by interactions with the North American land surface.]
What Caused the Dust Bowl in the US Midwest in the 1930's?
Was the Dust Bowl predictable?
An excerpt from the latter link is provided below:
"The inability to correctly model the spatial pattern of the Dust Bowl drought, and its deviation from the typical pattern of tropical SST-forced drought, makes us wonder how unusual the Dust Bowl pattern was. Analyses of instrumental data since the mid nineteenth century - shows that none of the other five multiyear droughts in this interval (1856-65, 1870-77, 1890-96, 1948-57 and post 1998) had a similar pattern. For a longer record we examined the updated version of the gridded tree ring records within the North American Drought Atlas. Computation of the spatial correlation between the Dust Bowl pattern and six year low pass filtered data revealed only three prior droughts that had an anomaly correlation exceeding 0.4 (Figure 4). All were in the Medieval period. No other droughts had an AC exceeding 0.31 presenting a clear separation between Dust Bowl type droughts and the more commonly occurring pattern with a center in the Southwest and southern and central Plains."
MY SHORT SUMMARY: The warm temperatures of the 1930s were extremely unusual in the United States. This has been known for quite awhile. The adjustments to the United States temperature record do not significantly change the current climate understanding: i.e., the 1930s were anomalously warm in the United States for one particular and unusual reason; the current warm temperatures in the United States are linked directly to the warming trend over the entire globe (with some minor exceptions like central Antarctica).
I don't really want to be attacked for my political motivations for posting this, because I don't have any. I will not respond to any non-scientific discussion - that's why I posted this in the "Science" forum and not "News/Current Events". I'm attempting to help people to understand the issue better, and not to get "carried away" with the latest "global warming refutation". My advice: don't get too excited. Keep reading. Try to separate knowledge from belief.
Oh yeah; you can also read my profile.
“I still have yet to see anything that embarrasingly contradicts global warming. “
Contradiction? No. Embarrassment? Yes.
The big story here is not the disproof of global warming, but the disproof of that anti-scientific claim from the AGW alarmists that “the science is settled”, which even recently Al Gore repeated. The hell it is.
When even the basic question of the underlying data is in question, most of the studies done up to now should be considered tainted and in need of review and revision.
Arguing global GISS data to ‘prove’ the changes are not significant is a bit of a non sequitor.
The questions are about US data, which is now being revised in a way that dampens some of claimed ramp up in recent temperatures and leaves us with 1934 as the hottest year on record, in the US.
But these revision to US data are a tip of the iceberg that could come:
- US temp records have been considered the ‘cleanest’ of the records globally, and it calls into question reliability of all the data
- there has been way too much secrecy in the algorithms used to make the temp adjustments; the light of day needs to shine on how these records are being constructed; when that happens, surely a lot more than this dataset will be affected
The AGW alarmist camp keeps hand-waving everytime
“There are 4.7 million station months of temperature data in GHCN starting in 1701 and continuing to the present. This embodies the systematic observations of our environment by tens of thousands of individuals over centuries of human history.”
Such a statement in no way refutes the main thing at issue, explained on Coyote blog:
http://www.coyoteblog.com/coyote_blog/2007/08/official-us-cli.html
“One of the interesting aspects of these temperature data bases is that they do not just use the raw temperature measurements from each station. Both the NOAA (which maintains the USHCN stations) and the GISS apply many layers of adjustments, which I discussed here. One of the purposes of Watt’s project is to help educate climate scientists that many of the adjustments they make to the data back in the office does not necessarily represent the true condition of the temperature stations. In particular, GISS adjustments imply instrument sitings are in more natural settings than they were in say 1905, an outrageous assumption on its face that is totally in conflict to the condition of the stations in Watt’s data base. Basically, surface temperature measurements have a low signal to noise ratio, and climate scientists have been overly casual about how they try to tease out the signal.”
Unless and until the ‘internals’ of how termperature adjustments are calculated are made public *and* a deep and thorough review of the actual quality of temp. instruments used to construct global means, charts such as “global average temperature” will be of dubious validity.
Is there evidence the global temperature data should be reviewed? Yes, consider this:
http://www.uoguelph.ca/~rmckitri/research/nvst.html
That’s how science has to work. Get the facts right. If even the facts are not settled, the science can hardly be said to be so.
Coyote blog has some informative posts on the subject:
This explains the issue of ‘adjustments’:
http://www.coyoteblog.com/coyote_blog/2007/07/an-interesting-.html
suspicious adjustment factors and quality of temp sites:
http://www.coyoteblog.com/coyote_blog/2007/06/signal_to_noise.html
temperature numbers revised:
http://www.coyoteblog.com/coyote_blog/2007/08/official-us-cli.html
Now that Mr Snowman has been exposed as a Democrat primary voter, with his recent exposure on YouTube sucking up to Democrats running for President, I say: Let him melt. :-)
When even the basic question of the underlying data is in question, most of the studies done up to now should be considered tainted and in need of review and revision.
I disagree. It remains to be shown that there are sufficient errors in the data to significantly affect conclusions drawn from them. Remember that science is self-checking, in a lot of ways. Models indicate Arctic polar amplification of global warming, for example. The data shows similar patterns. So does the retreat of sea ice. So does increasing SST in the North Atlantic. Etc.
The questions are about US data, which is now being revised in a way that dampens some of claimed ramp up in recent temperatures and leaves us with 1934 as the hottest year on record, in the US.
The graphs I posted show that 1934 was virtually as warm as 1998 in the U.S. The revision was very minor. 1998 was globally significantly warmer than 1934.
US temp records have been considered the ‘cleanest’ of the records globally, and it calls into question reliability of all the data
Why? The U.S. has urbanized much more rapidly than other areas of the world. Why does the data have to be "cleaner" just because we're the United States? Do you think a trained weather station operator in Sri Lanka can't make a reliable temperature measurement? Your statement seems to be just an assertion.
there has been way too much secrecy in the algorithms used to make the temp adjustments; the light of day needs to shine on how these records are being constructed; when that happens, surely a lot more than this dataset will be affected.
I suggest, with no time to check right now, that this "secrecy" is illusory, and that it will turn out that much of this information is actually publically available. One of the purposes of Watt’s project is to help educate climate scientists that many of the adjustments they make to the data back in the office does not necessarily represent the true condition of the temperature stations.
It remains to be shown that the true condition of the temperature stations substantially affects the quality of the data set. Read the Peterson paper again, noting how spatial corrections from five stations have to be correlated.
” It remains to be shown that there are sufficient errors in the data to significantly affect conclusions drawn from them.”
I’ll put you down as “not getting the point”.
When errors are found in a particular process, you need to correct the process or you are exposed to the risk of further errors due to flaws in the process. The process itself has been shown flawed and should be fixed. For more on this, you can look at for example books on Six Sigma Quality or works by Deming.
“Models indicate ...” models are not data.
“The data shows similar patterns.” The data cannot be trusted unless the processes used to derive them are corrected and shown to be so with full transparency.
“Remember that science is self-checking, in a lot of ways. “
It cannot be fully self-checking if data and data adjustment methodology is not made transparent. Yes, they publish papers, but they don’t publish the underlying data that enable true reproducibility. This was part of the ‘hockey stick’ controversy as well. The climate science community has been overly lax in not making sure results are truly reproducible.
“The graphs I posted show that 1934 was virtually as warm as 1998 in the U.S. The revision was very minor.” Another ‘missing the point’ comment.
“The U.S. has urbanized much more rapidly than other areas of the world.” LOL. This is certainly news to the billions now living in cities in Asia, Africa, and South America.
“Why does the data have to be “cleaner” just because we’re the United States?” — I am merely repeating statements from climate scientists that have stated as much.
If you want to believe that stations in Yemen and Sri Lanka are as well-maintained as US stations, go ahead, but unless a thorough review of station quality and temperature adjustment metrics is done, we cannot infer that global temp measurements are reliable to the precision required to say much about global warming. The potential signal to noise is too small.
“It remains to be shown that the true condition of the temperature stations substantially affects the quality of the data set.” -— So, unlike every other branch of science where skepticism reigns and nothings is assumed true unless proven so, AGW ‘science’ is assumed true unless proven false. Sweet. It’s a nice gig to have, but it’s not science!
Here is a quote that gets to the heart of (a) non-US temperature records such as these China records are non-reliable (b) why merely statements in published papers are not sufficienct (and often completely false) (c) why one small error is just the tip of the iceberg (d) temperature record consistency is a lot worse than climate science community has let on. From newsbusters, a post about the Keenan report:
http://newsbusters.org/blogs/noel-sheppard/2007/08/10/un-s-ipcc-accused-possible-research-fraud
As Keenan stated in his full report concerning this matter (emphasis added throughout):
Meteorological stations sometimes move, and this can affect the temperature measurements of the stations. For example, one of the stations relied upon by the above two papers was originally located on the upwind side of a city and later moved, 25 km, to be on the downwind side of the city. Such a move would be expected to increase the measured temperatures, because a city generates heat. Another station relied upon by the papers was originally located in the center of a city and then moved, 15 km, to be by the shore of a sea. Such a move would be expected to decrease the measured temperatures.
Those that have read the work of Anthony Watts at SurfaceStations.org certainly can understand what Keenan was talking about. He continued:
It is clear that when a station moves, the temperature data from before the move is not, in general, directly comparable to the data from after the move. This problem can occur even if the move is over a small distance. For example, if a station moves from being in the middle of a field to being by an asphalt area, then the measured temperatures would be expected to increase, even though the distance moved might be only 100 m. (A related issue is that the land use around a station can change over time, and this can affect measurements.)
In global warming studies, an important issue concerns the integrity of temperature measurements from meteorological stations. The latest assessment report from the IPCC indicates that the global average temperature rose by roughly 0.3 °C over the period 1954-1983. Thus, if errors in temperature measurements were of similar size to, or larger than, 0.3 °C, there could be a serious problem for global warming studies. The papers of Jones et al. and Wang et al. both consider this issue. The paper of Jones et al. is one of the main 2 works cited by the IPCC to support its contention that measurement errors arising from urbanization are tiny, and therefore are not a serious problem.
With that in mind, the problem Keenan identified was that the papers in question misrepresented the static condition of a large number of weather stations:
Regarding station movements over time, the papers of Jones et al. and Wang et al. make the following statements.
The stations were selected on the basis of station history: we chose those with few, if any, changes in instrumentation, location or observation times. [Jones et al.]
They were chosen based on station histories: selected stations have relatively few, if any, changes in instrumentation, location, or observation times.... [Wang et al.]
Unfortunately, these statements appear to be quite false:
Each paper gives the same reference for its statement: a report resulting from a project done jointly by the U.S. Department of Energy (DOE) and the Chinese Academy of Sciences (CAS). The DOE/CAS report (available via http://cdiac.esd.ornl.gov/ndps/ndp039.html) resulted from concern over “possible CO2-induced climate changes”. Its purpose was to present “the most comprehensive, long-term instrumental Chinese climate data presently available”. It contains, in particular, histories of some Chinese meteorological stations, including the different locations of those stations and the dates on which they moved, if any.
The DOE/CAS report was formally published in full in 1991-Wang et al. and Jones et al. used a pre-publication version of the report. A revised version of the report was published in 1997, but the station histories are the same in the two versions.
Jones et al. and Wang et al. consider the same 84 meteorological stations in China. Regarding 49 of those stations, the DOE/CAS report says, “station histories are not currently available” and “details regarding instrumentation, collection methods, changes in station location or observing times ... are not known” (sect. 5). For those 49 stations, then, the above-quoted statements from the two papers are impossible.
Shocking. But there was more:
Regarding the remaining 35 stations that were analyzed by the two papers, I have prepared a summary of the relevant information from the DOE/CAS report. The summary is available at http://www.informath.org/apprise/a5620/b17.htm. As an example from the summary, one station had five different locations during 1954-1983, with the locations as much as 41 km apart. Two other stations each had four different locations. At least half the stations had substantial moves (two other examples, of 25 km and 15 km, were given above). Moreover, several stations have histories that are inconsistent, making reliable analysis unattainable.
(The station that moved five times during the study period, #54511, is discussed by Yan et al. [Advances in Atmospheric Sciences, 18: 309 (2001)]; the authors conclude that some of the moves affected temperature measurements by 0.4 °C. The authors also discuss another station, #58367, which had a single move of 4 km; the authors conclude that the move affected temperature measurements by 0.3 °C. The authors’ statistical analysis, though, is invalid-e.g. it does not consider significance-so the conclusions are unproven.)
Additionally, the following statement from the DOE/CAS report seems apposite: “Few station records included in the PRC data sets can be considered truly homogeneous [i.e. have no significant changes in location, instrumentation, etc.]. Even the best stations were subject to minor relocations or changes in observing times, and many have undoubtedly experienced large increases in urbanization.”
The essential point here is that the quoted statements from Jones et al. and Wang et al. cannot be true and could not be in error by accident. The statements are fabricated.
A snippet from Steve McIntyre ...
http://www.norcalblogs.com/watts/2007/08/does_hansens_error_matter_gues.html
Steve McIntyre’s Climate Audit blog is offline, he has asked me to post this here - Anthony
...
Schmidt observed that the U.S. accounts for only 2% of the world’s land surface and that the correction of this error in the U.S. has “minimal impact on the world data”, which he illustrated by comparing the U.S. index to the global index. I’ve re-plotted this from original data on a common scale. Even without the recent changes, the U.S. history contrasts with the global history: the U.S. history has a rather minimal trend if any since the 1930s, while the ROW has a very pronounced trend since the 1930s.
These differences are attributed to “regional” differences and it is quite possible that this is a complete explanation. However, this conclusion is complicated by a number of important methodological differences between the U.S. and the ROW. In the U.S., despite the criticisms being rendered at surfacestations.org, there are many rural stations that have been in existence over a relatively long period of time; while one may cavil at how NOAA and/or GISS have carried out adjustments, they have collected metadata for many stations and made a concerted effort to adjust for such metadata. On the other hand, many of the stations in China, Indonesia, Brazil and elsewhere are in urban areas (such as Shanghai or Beijing). In some of the major indexes (CRU,NOAA), there appears to be no attempt whatever to adjust for urbanization. GISS does report an effort to adjust for urbanization in some cases, but their ability to do so depends on the existence of nearby rural stations, which are not always available. Thus, ithere is a real concern that the need for urban adjustment is most severe in the very areas where adjustments are either not made or not accurately made.
In its consideration of possible urbanization and/or microsite effects, IPCC has taken the position that urban effects are negligible, relying on a very few studies (Jones et al 1990, Peterson et al 2003, Parker 2005, 2006), each of which has been discussed at length at this site. In my opinion, none of these studies can be relied on for concluding that urbanization impacts have been avoided in the ROW sites contributing to the overall history.
A paper on this topic of reliability of non-US temperature records, that shows biases in global temperature records, likely due to inadequate controlling for things like heat island effect.
http://www.uoguelph.ca/~rmckitri/research/gdptemp.html
ABSTRACT:
Monthly surface temperature records from 1979 to 2000 were obtained from 218 individual stations in 93 countries and a linear trend coefficient determined for each site. This vector of trends was regressed on measures of local climate, as well as indicators of local economic activity (income, GDP growth rates, coal use) and data quality. The spatial pattern of trends is shown to be significantly correlated with non-climatic factors, including economic activity and sociopolitical characteristics of the region. The analysis is then repeated on the corresponding IPCC gridded data, and very similar correlations appear, despite previous attempts to remove non-climatic effects. The socioeconomic effects in the data are shown to add up to a net warming bias, although more precise estimation of its magnitude will require further research.
From a guy that doesn’t know degrees from radians. Next.
For future reference, can I have a couple names and quotes?
If you want to believe that stations in Yemen and Sri Lanka are as well-maintained as US stations, go ahead, but unless a thorough review of station quality and temperature adjustment metrics is done, we cannot infer that global temp measurements are reliable to the precision required to say much about global warming. The potential signal to noise is too small.
You haven't read Peterson et al. on QA/QC of GHCN data, apparently.
I may reply more later. But the blogs are hashing this out pretty well, better than you or I could.
The process itself has been shown flawed and should be fixed.
Perhaps true. That does not, however, in any fashion, invalidate the current scientific understanding of anthropogenic global warming.
It cannot be fully self-checking if data and data adjustment methodology is not made transparent. Yes, they publish papers, but they don’t publish the underlying data that enable true reproducibility. This was part of the ‘hockey stick’ controversy as well. The climate science community has been overly lax in not making sure results are truly reproducible.
Perhaps true. That does not, however, in any fashion, invalidate the current scientific understanding of anthropogenic global warming.
Meteorological stations sometimes move, and this can affect the temperature measurements of the stations. For example, one of the stations relied upon by the above two papers was originally located on the upwind side of a city and later moved, 25 km, to be on the downwind side of the city. Such a move would be expected to increase the measured temperatures, because a city generates heat. Another station relied upon by the papers was originally located in the center of a city and then moved, 15 km, to be by the shore of a sea. Such a move would be expected to decrease the measured temperatures.
Apparently he didn't read Peterson et al. either.
And finally:
“Models indicate ...” models are not data.
The output from models IS data. If it wasn't, you couldn't check the validity of models against observations.
The bottom line is that this may cause the USHCN principals to examine their methods and data; and the ultimate bottom line will turn out to be the current scientific understanding of the issue -- the world is warming and the scientists know why.
Please try to re-read what you wrote as an impartial scientist.
1) It is the responsibility of the scientists to defend their data, not for the critics to defend their findings of incorrectly collected data. If data was collected from a stations that did not meet a simple set of standards, then, if these scientists wish to maintain their credibility, it is THEIR responsibility to demonstrate how the bad data affects their previous conclusions. Apparently they have refused to show how they have corrected their predictions for the bad data, and there is evidence that suggests that they are correcting good data to offset the bad data. This is bad science. In my line of work (nuclear power), it would get me thrown in jail.
2) Your second paragraph indicates that you "know" the conclusion without any knowledge of the depth of the problems with the methods and data collection errors. This too is bad science. Some would even call your position "faith"
The usual case is that the QA/QC procedure results in a new, improved dataset -- exactly what happened with the GHCN v2. This is how the scientists maintain their credibility. If others think that there is still bad data in the dataset, then they have to demonstrate that the effect of the bad data is significant.
Your second paragraph indicates that you "know" the conclusion without any knowledge of the depth of the problems with the methods and data collection errors. This too is bad science. Some would even call your position "faith"
Anybody who thought that would be an idiot. My statement is an evaluation of the entire body of the science. I may write more on this later -- I have several ideas floating around in my head. I have a question for you: do you think that problems with surface station data may be significant enough to eliminate the 0.6 C warming of the 20th century and the 0.4 C warming since the 1980s?
No. It isn't. You place a lot of emphasis on peer review. Why aren't the methods of data correction released for peer review? Scientists maintain credibility by working with a high degree of tranparency. Bad data happens, QA errors happen...but when they do, it is the obligation of the scientist to be open to scrutiny rather than the secrecy here.
I have a question for you: do you think that problems with surface station data may be significant enough to eliminate the 0.6 C warming of the 20th century and the 0.4 C warming since the 1980s?
I haven't the slightest idea. However, I looked at the station audit site and found that a significant number of the stations had BLATENT temperature collection problems. I suspect the problem is worse in other countries where QA is even looser.
Bad data happens. When it does happen, a proper scientist would either provide his justification for using the data, and openly provide his methodology and basis for a correction, or reject the data outright. Frankly, I'm more alarmed at the secrecy in which data correction is performed than I am with the QA slip-ups. I'm at a loss as to why there is even any secrecy about temperature corrections if this is all being done in a heavily peer-reviewed environment.
“The process itself has been shown flawed and should be fixed.”
“Perhaps true. That does not, however, in any fashion, invalidate the current scientific understanding of anthropogenic global warming.”
I’m not one to argue the basic mechanisms. But clearly the science on actual magnitudes and matching of data to models is still under development, and these issues relate directly to the levels of certainty and confidence in those.
IMHO, the IPCC treatment of AGW has numerous sources of over-estimation, and the popular media and alarmists like AlGore have unscientifically extrapolated further into claims of certainty and presenting near-impossible scenarios as bound-to-happen.
The K*ln(C/C0) factor that CO2 increase plays in AGW both support AGW concept and the skeptics claim (hey, 290->390ppm is same as 390ppm->550ppm), but the actual impacts depends on that constant K factor, and you have to extrapolate both larger estimates of warming than we’ve actually observed, you’d have to magnify water vapor feedback effects, you’d have to pull other tricks to get to the feared magnitudes (K=5.35)the IPCC claims. most of this knowledge is based on models that are neither verified nor supported by the actual records of temperatures, which themselves are subject to error.
Thus, the side of a real scientist would be to be cautious and skeptical of a conclusion and to reject outright the lie that ‘the science is settled’. It is not, and it is unscientific gibberish to say it is. Especially from a divinity school dropout like Al Gore.
PS. “Models indicate ...” me:”models are not data.”
you: “The output from models IS data. “ - I’d call that model outputs/estimates. output from models could be GIGO unless it correlates to reality. The only data worthy of that name are the actual measurements (ie temperature) of physical reality. Everything else is AGM - anthropromophic gaseous modeling.
“From a guy that doesn’t know degrees from radians. Next.”
Eyes Wide Shut. This close-minded dismissiveness even of peer-reviewed work that is not part of the ‘consensus’ is common from the ‘community’ of AGW alarmists, I’ve noticed this attitude on e.g., climatescience.org.
maybe it’s par for the course on FR to reach for ad hominem without addressing the point, but it’s irksome, unwarranted, and unscientific.
If warming trends correlate to sociological non-climate factors, it puts into question whether adjustments are being properly done.
” The GISS problem is merely a clear example of how long very basic errors sit around because despite claims of widespread peer-review, they’ve never really been examined...and hundreds of papers cite them, and other networks gain credibility by matching them...just as with the Mann MHB98/99 papers.
Mann claimed his papers were not just read, but actively peer-reviewed by THOUSANDS of scientists; the TAR heavily relied on his work (in part because the IPCC made him a chapter author, which he took full advantage of)...and yet it took 8 years and congressional pressure before the math was thoroughly checked and found “not skillful”.
The GISS calculations are widely cited, and a great deal of faith is placed upon Hansen’s team performing adjustments for which they are not required to really explain what they are doing in any examinable detail.
Mr. McIntyre, did not find the error by himself - he lacks the resources to set up an alternate climate reference network - but the adverserial process narrowed down the error which had been overlooked for 7-1/2 years. “
Meanwhile, from the AGW hypers we are told, ‘pay no attention to the man behind the curtain’.
McKitrick
Scroll down to "McKitrick Screws Up Yet Again"
"As I noted in my post, correcting the error halves the size of the economic signal in the warming trend, reducing it from 0.16 (out of 0.27) to 0.09. ... Well, all the conclusion says is that there were socioeconomic effects, without mentioning their size. The size of the effects, which change substantially, are only mentioned in the body. And the “bombshell” nature of the paper touted by Michaels et al in their TCS article depends on socioeconomic effects being the primary cause of the warming trend, something that McKitrick has now retracted."
Moving on... I'll ask you the same question that I asked kidd above (he replied that he had no idea). Do you think that the problems with surface station data are significant enough to eliminate the (stated) observed warming of 0.6 C in the 20th century and 0.4 C since the 1980s? I have some ideas I want to put down, but it will take longer than a day; your response to this question will guide my thoughts.
“I’ve noticed this attitude on e.g., climatescience.org”
Sorry I meant to say RealClimate blog, which has a hostile, politicized and patronizing attitude towards anyone/anything that doesn’t align with the PC ‘consensus’.
Climate science blog, i.e.,
http://climatesci.colorado.edu/ is its own interesting site.
Their latest article is on cloud cover feedback.
Oh puleeze, quoting Tim Lambert again? If you dont trust McKitrick why should I trust a biased leftist advocate like Tim Lambert who I’ve alredy pointed out has issues of his own? His obligatory slanderous “right wing attack on science,” is right in the first sentence.
He starts off with “Chris Mooney has great article in the The American Prospect ...” Yeah. I’m going to give credence to a left-winger quoting a left-wing *political* magazine on science issues. Pointless gainsaying awaits. Why are you linking to leftwingers on *FR* fer crying out loud?
If you want this to be a debate about the science, stick at least to citing non-leftists.
On the substance, I am not drawing any conclusion from McKitrick except the most narrow one, which is that further adjustment/review of international data is warranted based on possible spurious correlations. So even cutting his signal in half doesn’t change that point. Like the GISS issue, the magnitude is only one factor here; it’s the process of how we make sure the spurious signal is zero that is the point. Same point here as in the GISS recalibration issue. You cite Peterson, but Keenan is poking holes in it. see also:
http://www.norcalblogs.com/watts/2007/08/surface_temperature_records_in.html
The numbers that fall out await such a review and scrubbing of data and adjustments for accuracy. We shouldn’t trust statements about international numbers/trends with high precision until that has been really done.
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