What the BEST data actually says

Guest Post by Willis Eschenbach

My theory is that the BEST folks must have eaten at a Hollywood Chinese restaurant. You can tell because when you eat there, an hour later you find you’re hungry for stardom.

Now that the BEST folks have demanded and received their fifteen minutes of fame before their results have gone through peer review, now that they have succeeded in deceiving many people into thinking that Muller is a skeptic and that somehow BEST has ‘proven the skeptics wrong’, now that they’ve returned to the wilds of their natural scientific habitat far from the reach of National Geographic photographers and people asking real questions, I thought I might take a look at the data itself. Media whores are always predictable and boring, but data always contains surprises. It can be downloaded from the bottom of this page, but please note that they do not show the actual results on that page, they show smoothed results. Here’s their actual un-smoothed monthly data:

Figure 1. BEST global surface temperature estimates. Gray bars show what BEST says are the 95% confidence intervals (95%CI) for each datapoint.

I don’t know about you, but Figure 1 immediately made me think of the repeated claim by Michael Mann that the temperatures of the 1990s were the warmest in a thousand years.

WHAT I FIND IN THE BEST DATA

Uncertainty

I agree with William Briggs and Doug Keenan that “the uncertainty bands are too narrow”. Please read the two authors to see why.

I thought of Mann’s claim because, even with BEST’s narrow uncertainty figures, their results show we know very little about relative temperatures over the last two centuries. For example, we certainly cannot say that the current temperatures are greater than anything before about 1945. The uncertainty bands overlap, and so we simply don’t know if e.g. 2010 was warmer than 1910. Seems likely, to be sure … but we do not have the evidence to back that up.

And that, of course, means that Mann’s claims of ‘warmest in a mill-yun years’ or whatever he has ramped it up to by now are not sustainable. We can’t tell, using actual thermometer records, if we’re warmer than a mere century ago. How can a few trees and clamshells tell us more than dozens of thermometers?

Disagreement with satellite observations

The BEST folks say that there is no urban heat island (UHI) effect detectable in their analysis. Their actual claim is that “urban warming does not unduly bias estimates of recent global temperature change”. Here’s a comment from NASA, which indicates that, well, there might be a bias. Emphasis mine.

The compact city of Providence, R.I., for example, has surface temperatures that are about 12.2 °C (21.9 °F) warmer than the surrounding countryside, while similarly-sized but spread-out Buffalo, N.Y., produces a heat island of only about 7.2 °C (12.9 °F), according to satellite data. SOURCE

A 22°F (12°C) UHI warming in Providence, and BEST says no UHI effect … and that’s just a couple cities.

If there were no UHI, then (per the generally accepted theories) the atmosphere should be warming more than the ground. If there is UHI, on the other hand, the ground station records would have an upwards bias and might even indicate more warming than the atmosphere.

After a number of adjustments, the two satellite records, from RSS and UAH, are pretty similar. Figure 2 shows their records for global land-only lower tropospheric temperatures:

Figure 2. UAH and RSS satellite temperature records. Anomaly period 1979-1984 = 0.

Since they are so close, I have averaged them together in Figure 3 to avoid disputes. You can substitute either one if you wish. Figure three shows a three-year centered Gaussian average of the data. The final 1.5 years are truncated to avoid end effects.

Remember what we would expect to find if all of the ground records were correct. They’d all lie on or near the same line, and the satellite temperatures would be rising faster than the ground temperatures. Here are the actual results, showing BEST, satellite, GISS, CRUTEM, and GHCN land temperatures:

Figure 3. BEST, average satellite, and other estimates of the global land temperature over the satellite era. Anomaly period 1979-1984 = 0.

In Figure 3, we find the opposite of what we expected. The land temperatures are rising faster than the atmospheric temperatures, contrary to theory. In addition, the BEST data is the worst of the lot in this regard.

Disagreement with other ground-based records.

The disagreement between the four ground-based results also begs for an explanation. Note that the records diverge at the rate of about 0.2°C in thirty years, which is 0.7° per century. Since this is the approximate amount of the last century’s warming, this is by no means a trivial difference.

My conclusion? We still have not resolved the UHI issue, in any of the land datasets. I’m happy to discuss other alternative explanations for what we find in Figure 3. I just can’t think of too many. With the ground records, nobody has looked at the other guys’ analysis and algorithms harshly, aggressively, and critically. They’ve all taken their own paths, and they haven’t disputed much with each other. The satellite data algorithms, on the other hand, has been examined minutely by two very competitive groups, UAH and RSS, in a strongly adversarial scientific manner. As is common in science, the two groups have each found errors in the other’s work, and when corrected the two records agree quite well. It’s possible they’re both wrong, but that doesn’t seem likely. If the ground-based folks did that, we might get better agreement. But as with the climate models and modelers, they’re all far too well-mannered to critically examine each other’s work in any serious fashion. Because heck, if they did that to the other guy, he might return the favor and point out flaws in their work, don’t want that kind of ugliness to intrude on their genteel, collegiate relationship, can’t we just be friends and not look too deeply? …

w.

PS—I remind folks again that the hype about BEST showing skeptics are wrong is just that. Most folks knew already that the world has been generally warming for hundreds of years, and BEST’s results in that regard were no surprise. BEST showed nothing about whether humans are affecting the climate, nor could it have done so. There are still large unresolved issues in the land temperature record which BEST has not clarified or solved. The jury is out on the BEST results, and it is only in part because they haven’t even gone through peer review.

PPS—

Oh, yeah, one more thing. At the top of the BEST dataset there’s a note that says:

Estimated 1950-1980 absolute temperature: 7.11 +/- 0.50

Seven degrees C? The GISS folks don’t even give an average, they just say it’s globally about 14°C.

The HadCRUT data gives a global temperature about the same, 13.9°C, using a gridded absolute temperature dataset. Finally, the Kiehl/Trenberth global budget gives a black-body radiation value of 390 W/m2, which converts to 14.8°. So I figured that was kind of settled, that the earth’s average temperature (an elusive concept to be sure) was around fourteen or fifteen degrees C.

Now, without a single word of comment that I can find, BEST says it’s only 7.1 degrees … say what? Anyone have an explanation for that? I know that the BEST figure is just the land. But if the globe is at say 14° to make it easy, and the land is at 7°, that means that on average the ocean is at 17°.

And I’m just not buying that on a global average the ocean is ten degrees C, or 18 degrees F, warmer than the land. It sets off my bad number detector.

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191 thoughts on “What the BEST data actually says

  1. And long-duration stations with continuous records show no or negative change over the 20th Century:

    http://wattsupwiththat.com/2011/10/24/unadjusted-data-of-long-period-stations-in-giss-show-a-virtually-flat-century-scale-trend/#comment-776101

    The slight upward temperature trend observed in the average temperature of all stations disappears entirely if the input data is restricted to long-running stations only, that is those stations that have reported monthly averages for at least one month in every year from 1900 to 2000. This discrepancy remains to be explained.

  2. And Mueller and the BEST team (outside of Youknowwhodat) say to their critics ……..

    That’s what I thought.

  3. Willis: very helpful and it highlights how much work still needs to be done on what should be foundational datasets. I know the following is a little off-topic but it flows out of the assessment you offer. Namely, I will be interested to see how, if at all, the BEST papers evolve with “peer review.” I don’t understand why the authors took on the reputational risk (and some possible risk to good relations with the publishers) by issuing press releases and drafts of their papers before peer review and final publisher acceptance. There is a good reason for doing things the other way around: not wasting the public’s time for one thing, not looking like a fool for another. Now to mitigate or manage those risks the authors will be tempted to externalize the cost by suppressing corrections that might be advisable or vital. There will be enormous pressure on the reviewers not to change anything important. If the reviewers insist on such changes, there will be enormous pressure on the publishers to ignore or fudge them. If that doesn’t work, then the authors will be forced to eat very public crow, and so will everyone who ran down the hill with them. What induced them to assume that risk? What was the magic of their being able to issue press releases now?

  4. Willis,

    The only stunning thing about the BEST results is that they don’t help in any way to resolve the issue. They simply add additional uncertainty, as is clearly reproduced in your fig.1, showing that anything might have happened to the mean global average temperature over the past 210 years from 3degC warming to 2degC cooling. 

    In other words the BEST results are useless for making any useful prediction whatsoever over whether the world has warmed or not, alarmingly or otherwise. This is the true conclusion which, of course, the alarmists will be entirely incapable of seeing.

  5. I emailed the BEST team a while ago asking if they could just plot the rural, unadjusted data. I got an email a few days ago saying it’s done.

    My question is, if the rural data unadjusted data agrees with the adjusted and unadjusted data, why bother to adjust the data at all?

  6. They did a pairwise comparison for 500K pairs of series and over 4K miles, I think, they found no correlation between stations. If there is a long term global trend, shouldn’t that correlation show up?

  7. kramer says:
    October 24, 2011 at 5:01 pm

    I emailed the BEST team a while ago asking if they could just plot the rural, unadjusted data. I got an email a few days ago saying it’s done.

    My question is, if the rural data unadjusted data agrees with the adjusted and unadjusted data, why bother to adjust the data at all?

    Dunno, kramer, good question but lacking information … where did they post it up, what did they say they had done, how did they decide if a site is “rural”, what time span are we talking about, what does “agrees with” mean in their and your mind … some links and details would help.

    w.

  8. You must hand it to them on one PR front. Coming up with the ‘BEST’ acronym no doubt fools some people, and will continue to do so even if it turns out to be the worst data set.

    In any case, seems like they have done a fine enough job of confirming the rebound out of the Little Ice Age which, for me, says it all.

  9. Willis, there’s a lot of good work here, but I think it will be obscured by all of the ad hom is your opening paragraphs. If we are going to persuade the persuadable (as opposed to preach to the choir) then I think we need to dial it back a bit.

  10. I’m convinced. I’m changing my position as a skeptic who thinks the world is warmer than it was to a skeptic who thinks the world is warmer than it was. Thanks, BEST!

  11. I always though a 95% CI was the area under a curve which showed 95% of the data when N was large.
    Have a look at figure 3 of the UHI paper; the 95% of the slope is +/- about 1.5 degrees.

  12. Willis,
    Klotzbach et al. 2009 ( here and correction here) suggests several possibilities for bias in the land record other than UHI. I don’t think that any of the other possible factors have been quantified though.

  13. I do not understand why the “land” temperature data set is of relevance at all. The earth’s surface is 70% water and this body of water contains ~ 1000 times the energy of the atmosphere, Indeed the temperature of the atmosphere is totally dictated by the sea temperatures – one only has to notice the effect of the Gulf stream on Western Europe to see that.

    So if we want to see real earth warming or cooling and the magnitude of it, we must just look at ocean temperatures. Why is there this fixation on the land ?

  14. moptop says:
    October 24, 2011 at 5:05 pm

    They did a pairwise comparison for 500K pairs of series and over 4K miles, I think, they found no correlation between stations. If there is a long term global trend, shouldn’t that correlation show up?

    Not necessarily. There is a commonly believed fallacy out there, which is that good correlation of data indicates good correlation of trends. I discussed this in a post called “GISScapades“.

  15. Excellent post, Willis.

    Media whores are always predictable and boring, but data always contains surprises.

    Ironic, isn’t it?

  16. You suspect BEST are not serious when their numerical data are posted only in Text format, to judge from their site at WE’s link above. At least GISS and ESRL-NOAA provide data in formats eaily brought into Excel etc.

  17. The BEST page says

    “The Berkeley Earth Surface Temperature Study has created a preliminary merged data set by combining 1.6 billion temperature reports from 15 preexisting data archives.”

    Yet when I download the alleged data file it is only a mere 57KB zipped and only consists of two uncompressed files of 243KB and 14KB… and certainly do not contain 1.6 billion temperature reports!!!

    “% This file contains a detailed summary of the land-surface average
    % results produced by the Berkeley Averaging method. Temperatures are
    % in Celsius and reported as anomalies relative to the 1950-1980 average.
    % Uncertainties represent the 95% confidence interval for statistical
    % and spatial undersampling effects.
    %
    % The current dataset presented here is described as:
    %
    % The preliminary version of the complete Berkeley Earth dataset
    %
    %
    % This analysis was run on 27-Sep-2011 16:42:54
    %
    % Results are based on 37633 time series
    % with 14502771 data points
    %
    % Estimated 1950-1980 absolute temperature: 7.11 +/- 0.50
    %
    %
    % For each month, we report the estimated land-surface average for that
    % month and its uncertainty. We also report the corresponding values for
    % year, five-year, ten-year, and twenty-year moving averages CENTERED about
    % that month (rounding down if the center is in between months). For example,
    % the annual average from January to December 1950 is reported at June 1950.
    %
    % Monthly Annual Five-year Ten-year Twenty-year
    % Year, Month, Anomaly, Unc., Anomaly, Unc., Anomaly, Unc., Anomaly, Unc., Anomaly, Unc.

    1800 1 -1.447 2.505 -0.890 0.766 -0.461 0.524 -0.424 0.512 -0.477 0.475
    1800 2 -2.132 2.928 -0.898 0.735 -0.463 0.523 -0.425 0.508 -0.481 0.474

    2010 4 -1.035 2.763 NaN NaN NaN NaN NaN NaN NaN NaN
    2010 5 1.098 2.928 NaN NaN NaN NaN NaN NaN NaN NaN”

    This is bogus since it is not the raw data but once more mysteriously processed data.

    BEST where is the raw data please? ALL OF IT!!! Please provide the download link. Thank you.

  18. Recently the BBC started to use the word “skeptic”, even acknowledging that some exist. Maybe this was preparation for Muller’s PR blitzkrieg; and maybe they will continue to use the word “skeptic” for the Mullerite opportunists / GISS imitators; and you-know-what for us. So maybe this was simply an exercise in “improving the communication” of science a la “skepticalscience”; i.e. by claiming a word and redefining it. Wouldn’t surprise me at all; they did it with the words “liberal” and “progressive” before.

    Some fun: Google trends for the words “climate” and “Al Gore”.

    http://www.google.com/trends?q=climate%2C+al+gore&ctab=0&geo=us&geor=all&date=all&sort=0

    Notice
    – the seasonal dependency in the chart for “climate” (looks like people are more worried in Winter)
    – the long term decline of “climate”
    – the non-event that Al Gore’s CRP was
    – the 2010 spike for Al Gore (hint: not climate-related)

  19. BEST’s denial of the UHI effect will get them into trouble.

    The one climate related thing an unscientific person can do is read the thermometers in their cars. They have seen the UHI effect with their own eyes. When BEST tells them they are crazy they will have doubts about BEST’s credibility.

  20. I’d be cautious about drawing UHI conclusions from Buffalo, NY.

    Buffalo and its surrounding area has a very unusual winter micro-climate due to prevailing winds and the proximity of lakes Erie and Ontario.

    Its common to encounter a raging blizzard near Buffalo and have bright sunshine a couple Ks down the road.

  21. mpaul says:
    October 24, 2011 at 5:17 pm

    Willis, there’s a lot of good work here, but I think it will be obscured by all of the ad hom is your opening paragraphs. If we are going to persuade the persuadable (as opposed to preach to the choir) then I think we need to dial it back a bit.

    You’re likely right, mpaul. But the arrogance of Muller and his merry men knows no bounds. He got Anthony to lend him his Surfacestation data, and then broke a confidentiality agreement to traduce Anthony’s work in front of Congress, of all places. He knew it would get maximum media exposure there …

    He also promised the most transparent, ethical, straightforward, purely scientific effort yet … then he goes and engages in shameless self-promotion prior to his work even passing peer review.

    Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media. Sure, I could pretend Muller is an honest and honorable man like you recommend. But his actions have shown him to be a cunning snake. It is not my habit to address snakes as though they were honorable men.

    Note, however, that none of these are “ad hominems”, as I make no claim that Muller being a snake has affected his mathematics or altered his results in the slightest. The data is the data, it says what it says despite Muller’s reptilian ways. I am not arguing against the data, there is no ad-hominem.

    Look, mpaul. Almost no one in the climate establishment will stand up and call a spade a spade. They will never censor, condemn, or even criticize another climate scientist. The Eleventh Commandment for climate scientists is “Thou shalt not speak ill of a fellow climate scientist”, and they follow it religiously. Near as I can tell the AGW establishment scientists have had their gag reflexed surgically removed, it’s the only explanation I can think of that explains their actions. There is a deafening silence out there, just like after Climategate, scientists are acting like Muller is a straightforward, ethical scientist.

    So as usual, I end up being one of the few people willing to be the kid in the story of the Emperor and his new clothes. I’m not going to say he’s well dressed, mpaul, I’m not going to pretend that Muller is “gentleman from sole to crown”. He is a deceptive, sneaky man, an activist who professes neutrality and pretends to be a scientist, a man who thinks nothing of throwing someone to the wolves, a panderer for his latest findings. And as far as I’m concerned, all you guys acting like he is a decent man, and advising me not to mention the Emperor’s nudity, are accomplices in his deception.

    So rather than you advising me to be all calm and peaceful about this, how about I advise you to be less calm and peaceful, and to stand up and denounce bad science wherever you find it? I’m tired of people playing nice when folks are trying to sentence the poor to a lifetime of un-obtainably expensive energy. I’m sick of the silence surrounding egregious scientific malfeasance. I’m upset, yes, and you’re right, it does affect my writing. I’m upset that people are not outraged at this attempt to assuage some liberal guilt by making energy, the lifeblood of the poor, more and more and more expensive with each passing day.

    However, I don’t see my being upset as a bad thing. It’s just what’s so. What would be a bad thing would be if if I were to pretend I wasn’t upset, as you advise me to do, if I were to lay down false honeyed words and omit certain facts in order to “persuade the persuadable”.

    The problem is, mpaul, that that would make me exactly like Muller, putting on a false front simply to attract converts. Sorry, but I hope you can see why that’s not my style. I tell the truth as best I see it, and I trust that people are wise enough to look past my being upset, to look at the reasons why I’m upset, and to see that I am honestly recounting my experience and my ideas and my judgements. To date, I haven’t been disappointed placing my trust in folk’s common sense.

    Thanks for your thoughts,

    w.

  22. I would like to see the satellite graph (Figure 2) after correction for the El Chichon and Pinatubo eruptions, where fairly strong El Ninos took place for both. Anyone? Thanks.

  23. Figure 3. is interesting. BEST looks worst.

    I don’t think the BEST papers can be read as stating that there is no UHI effect. Rather they seem to say that UHI makes no difference in the calculated temperature anomaly. In other words, urban areas, while overall hotter, have the same trend of rising temperature as non-urban areas over the period analyzed. But it’s not clear to me that their analysis was sufficiently rigorous. If they looked at only a few years of data, around large but relatively static urban areas, they might find no effect or little effect on the calculate anomaly. However, looking at many years of data around a growing urban area might (probably would?) show temperatures rising faster than surrounding non-urban areas.

    There’s also the question of micro-climates around sensing stations, which are so clearly shown in Andrew’s Surface Station data. It might be that non-urban areas are affected as much, or even more, by very-localized heat sources (AC units, barbecues, cars, planes, etc.).

    BEST and others show most of the warming occurring since 1980. Isn’t that about the time that electronic sensors began to replace old-fashioned glass thermometers, and didn’t the use of electronic sensors require moving sensors closer to structures (heat sources) because the cables have a limited useful length? The warming stops around 2000, which could be around the time that most sensors had been upgraded and moved closer to artificial heat sources.

    Anthony’s surface Station data is great stuff. But since most of the warming occurred outside the U.S., it could be more revealing to look at the history and metadata for stations that actually show the measured warming.

    Another point that really bothers me; is the raw data lost? Do we no longer have the daily high and low temperatures? A CO2 warming signature should show more warming on cold nights. It sure would be helpful is we could see that data. Is anyone really going to complain if CO2 warming causes -30°C nights in Siberia to be -28°C nights?

    One of the BEST color graphics shows most of the warming over the past hundred years occurred in the Arctic, north-central Russia, and central Asia. If that warming mostly occurred on cold nights, our Russian and Central Asian cousins might be willing to ship us oil at a discount, provided we promise to burn it all quickly.

    dT

  24. Hi Willis

    Any chance of getting your analysis in front of the editors, reviewers and so on at the Journal that is publishing the BEST thing???

    All the best to you…

    Stu

  25. Dear Willis.
    Thanks for your tireless research and hard work, you are a champion and a welcome breath of fresh air in the search for clarity and truth your post always bring enlightnment.
    Keep up the good work.

  26. mpaul might have a point about dialing it back. From a selfish point of view, I hope you do not. You have a delightful way of expressing opinions that makes what you write worth reading. It is far better to be “over the top” and remembered than staid and ignored.

    “hour later be hungry for stardom.” Delicious! And on point. BEST’s conclusion that UHI cannot be quantified in the data, or at least separated from the urban and rural sites will haunt them and IPCC. If you cannot find any UHI signature in your best data, how can you possibly find any human signature at all in the temperature records. It has all the hallmarks of being hurried to meet a deadline for stardom.

    Stay colorful. Stay yourself, Willis.

  27. oMan says:
    October 24, 2011 at 4:53 pm
    “What was the magic of their being able to issue press releases now?”

    Literally, the $64 million question?

  28. @ Willis; In my opinion, your characterization of the beserkeley BEST project as a den of snakes is incorrect.
    This smells of a pack of Rats to me. pg

  29. From pwl on October 24, 2011 at 6:00 pm

    BEST where is the raw data please? ALL OF IT!!! Please provide the download link. Thank you.

    From their Data set page, first line:

    The Berkeley Earth data set is now publicly available here.

    There you find:

    * Preliminary text dataset: download
    * Preliminary Matlab dataset: download

    During an attempted download (I’m on dial-up), the size of the text version was reported as 253Mb. And if I’d let it finish doing nothing else online and nothing went wrong, it’d only take about 11 hours…

    By the note on the download page though, these are the TAVG files. More detail, but not exactly all that raw.

  30. on a hot day in any australian city you’ll find over 250,000 a/c units on full power. each one is providing radiative forcing of over 35 watts sq/m. That’s around 2 degrees over 25 square kilometres.

  31. Willi Eschenbach, per reply to MPaul: Stay brave and true, cherish Honor above all. “Blessed are those that hunger and thirst after righteousness for righteousness’ sake, for they shall be saved.”

  32. Willis Eschenbach says (October 24, 2011 at 6:31 pm): “Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media. Sure, I could pretend Muller is an honest and honorable man like you recommend. But his actions have shown him to be a cunning snake.”

    Hah! That’s nothing! I hear the cad won’t even pick up hitchhikers! :-)

  33. To quote myself from Dr. Curry’s blog:

    I went from profound disappointment in the quality, character, and abuse of the science to being disgusted, angry, and unforgiving of the quality and character of the scientists.

    In the matter of changing one’s mind over time regarding this topic of climate.

  34. Just read an interview with that skeptic Muller from Oct 2008

    http://www.grist.org/article/lets-get-physical

    HTH can the MSM refer to him as a former skeptic. He is a warmist to the core. Check out this opinion about Al:

    “The important thing is not getting Al Gore out of his jet plane; the important thing is solving the world’s problem. What we really need are policies around the world that address the problem, not feel-good measures. If [Al Gore] reaches more people and convinces the world that global warming is real, even if he does it through exaggeration and distortion — which he does, but he’s very effective at it — then let him fly any plane he wants.”

    I agree with you Willis, he is a slimeball.

    h/t ZI in comments on Climateaudit.org

    Hal

  35. The open source raw data of the BEST project are where? All I have seen since the marvelous presser are the monthly and annual averages. Perhaps they are out there and I have missed announcement.

  36. I don’t know about you, but Figure 1 immediately made me think of the repeated claim by Michael Mann that the temperatures of the 1990s were the warmest in a thousand years

    Uhhh, sooo, whats the big deal? Sooo, we had a medieval warm period 1000 years ago, it was warm, people were happy. Then it got cold, people were not happy (those that lived through it). Now it is the same temperature as 1000 years ago (and people are happy again), so I have to ask, what, exactly, is “unprecedented” here? We have been this warm before, we are again now, what, exactly, has changed? What, exactly, is there to be concerned about? Or can it be shown that 1000 years ago was a time of danger and death from all that heat? Did the sea rise and cover all of them then? Did all the animals go extinct? All the forests and crops die off? What, exactly, did happen?

    Now, if you can show me that it is much much warmer than it was 1000 years ago, much warmer than it has ever been, why, that would be something else.

    And the 1990′s huh, what about the 2000′s, what about the 2010′s? What has happened since those 1990′s, and why?

    Mr Mann, call me when you actually have something to say.

  37. Willis,

    Don’t hold back tell us how you really feel :)

    You are just saying what we are all feeling. Thanks for having the balls to do so.

  38. What, the paper does not “support the findings of the models”?
    What is the world coming to? If this keeps up there will never be global unity!
    Lucky for them the press held up their end of the planet by not reading the report and covering for the scientists by announcing that the skeptics had been vanquished yet again!
    /snark

  39. My motto is:

    Say what you mean – Mean what you say!

    Continue doing that Willis, just keep in mind, that it is extremely difficult to do BOTH, when one is angry. Some, of my greatest chagrin, originates from an angry violation of my motto. GK

  40. Doug in Seattle said on October 24, 2011 at 7:32 pm:

    The open source raw data of the BEST project are where? All I have seen since the marvelous presser are the monthly and annual averages. Perhaps they are out there and I have missed announcement.

    Apparently you missed my comment giving the links to the large data set, check it for yourself to see if it is raw enough.
    ===

    Too bad the group couldn’t have been slightly more descriptive in their title. Berkeley Earth Atmospheric Surface Temperature would have been near perfect and more accurate.

  41. ” Hey guys, we’re losing the general public. Let’s go on the offensive!!”
    ” Yeah, maybe we can sucker punch a few good natured skeptics along the way.”
    ” Just in time for our next rendezvous !!”
    ” (All) Kumbaya, …”

  42. Willis,
    you made the mistake of using GISS without having it properly using a land-mask. The met only dataset is not a “land-only” dataset like NOAA’s land only, Best’s land only or Hadleys… When you properly account for this the differences between GISS and BEST are very small. Why didn’t you show NOAA by the way? I don’t understand how someone can include hadley but doesn’t include NOAA considering how vastly superior their method is (empirical orthogonal function and what not compared to CAM). Anyways all i’m saying is that your graph there would look way different if you used the right land masked form of GISS and if you showed NOAA. Please show due diligence next time around. This was discussed at LUCIA’s long ago (re the issue with GISS).

  43. How many times have we been told by the likes of Phil Jones that if it’s not peer reviewed it doesn’t matter. Well, none of these BEST papers have passed peer review yet, so why is everybody fawning over them. They could still have major revisions before the review process is finished. (OK, probably not, but let me have this little fantasy)

    So I think we should all just stop hyperventilating over them and talk about some established science. And for the record, I tend to agree with Willis in this regard: the BEST team is much to preoccupied with attention getting stunts like this one. Real scientists crave not these things, as Yoda would say. (OK, I’m a Star Wars geek too)

  44. Mistake on the last post. Willis did use NOAA he just labelled it GHCN which I just assumed it meant just using the raw GHCN rather than NOAAs method (I only noticed when I saw it linked to NOAA). Point still stands on GISS. The only one that doesn’t fit is Hadley and we know why that is.

  45. Thank you for posting Willis.

    I was not clear how you produced Figure 1 of ” their actual un-smoothed monthly data:”

    Can you post step by step instructions?

  46. The “best” data would be a compilation of stations that have not moved and that are still uncontaminated by changes in land use, structures, or any type of development. There would not be many such sites. The impact on temperature by land use changes would be difficult to see as it would happen slowly. BEST dealt with obvious step changes by starting a new series each time one cropped up, then looking only at the changes that occurred after the step change, which likely dealt pretty will with equipment changes or rapid development. Land use changes would likely not be addressed by this technique. I suspect that one of the largest error drivers in the data are those sites that went through land use changes, such as from forested to intensive farming.

    In the end, all this bother about how much global temperatures have increased is meaningless. The real issue is what is causing it. As long as the warmists can make the public believe that all warming since 1950 or whatever is due to CO2, and that their models are infallible, they will be able to further their green agenda.

    BEST will be peer reviewed by anonymous warmists and found to be perfect.

  47. The BEST press release makes the following claim about UHI:

    “The urban heat island effect is locally large and real, but does not contribute significantly to the average land temperature rise. That’s because the urban regions of the Earth amount to less than 1% of the land area.”

    Aren’t they shooting AGW in the head (or themselves in the foot) with that statement? I mean, if the urban regions of the Earth are not contributing significantly to the average temperature rise of the planet, how can they then turn around and claim that humans are the main cause of global warming? Aren’t the urban regions of the Earth where the people are? Doesn’t most energy use occur in urban regions? Are they saying that people in rural areas are somehow at fault for warming the earth even though they are not warming their local region? What am I missing here?

    • Louis – your point about UHI…

      As I understand the thing about UHI is that it causes distortions to the temperature record by trending them upwards as urban areas overtake rural areas – not that it has an overall effect on climate. I think it is interesting that BEST acknowledges that the effect is ‘large’ and then does not appear to take this into account. Anthony, I believe is the world’s expert on this…

  48. Stuart Huggett says:
    October 24, 2011 at 6:38 pm

    Hi Willis

    Any chance of getting your analysis in front of the editors, reviewers and so on at the Journal that is publishing the BEST thing???

    All the best to you…

    Stu

    Hey, Stu, always a pleasure. Realisticly, chances are slim to none. First, all I’ve looked at is the data, not their pre-publication papers (pre-papers? Pre-pers?). And what I find is that the data doesn’t support the claims made pre-publication … but there’s nothing to examine, consider, or object to yet. Not only have the papers not been published, but they haven’t even been peer-reviewed. So there’s nothing to discuss, really, except their bad habit of doing “science” by press release.

    Oh, and the fact that a land temperature warming 50% faster than the atmosphere seems unlikely. And that there’s still a difference of some 0.7° per century between the high and low land surface temperature trends.

    Second, the fact that they went on their figurative book-signing tour before the paper had been peer-reviewed does not show that the fix was in, that the game was already decided. It certainly does mean that we have to include “the fix was in” in our guesses as to why they took such a hazardous and generally untrodden path. And that makes it less likely that any opposing view would be heard.

    w.

  49. “The disagreement between the four ground-based results also begs for an explanation. Note that the records diverge at the rate of about 0.2°C in thirty years, which is 0.7° per century. Since this is the approximate amount of the last century’s warming, this is by no means a trivial difference.”

    Indeed!!. And why, after 1995 does the divergence widen considerably. It appears that the divergence of land based readings, from each other and the satelite record, is growing faster then any observed warming, which since 1995 is statistically not significant.

  50. Gary Hladik says:
    October 24, 2011 at 7:23 pm

    … Hah! That’s nothing! I hear the cad won’t even pick up hitchhikers! :-)

    I had just put down my coffee cup (yes, I drink coffee at 10:10 PM). Good timing, ’cause I cracked up. Not picking up hitchhikers, that I can forgive … forgiving what he’s actually done, that’s harder.

    Many thanks,

    w.

    PS—if the joke seems obscure, it’s about my report of my hitchhiking

  51. Robert says:
    October 24, 2011 at 8:44 pm

    Willis,
    you made the mistake of using GISS without having it properly using a land-mask. The met only dataset is not a “land-only” dataset like NOAA’s land only, Best’s land only or Hadleys… When you properly account for this the differences between GISS and BEST are very small.

    Quite possibly so. However, the GISS data set says:

    sources: GHCN-v2 1880-09/2011 (meteorological stations only)

    So why would it need a land mask, if it is met stations only, no ships, no ocean data?

    In addition, the URL says:

    monthly.land.90S.90N.df_1901-2000mean.dat

    Kinda sounds like … well … monthly land data to me. I’ll need a citation to your “land-masked” data before changing my mind. You may be right, GISS does some strange stuff, but where’s the info? Also, if this makes GISS look like HadCRUT … how does that change anything?

    Why didn’t you show NOAA by the way? I don’t understand how someone can include hadley but doesn’t include NOAA considering how vastly superior their method is (empirical orthogonal function and what not compared to CAM). Anyways all i’m saying is that your graph there would look way different if you used the right land masked form of GISS and if you showed NOAA.

    As far as I know, GHCN is NOAA … if not, provide the link to the NOAA data.

    Please show due diligence next time around. This was discussed at LUCIA’s long ago (re the issue with GISS).

    Oh, piss off with your nastiness about due diligence. Please show due politeness next time around.

    I do all the due diligence I can do, wacka do. I don’t know everything, I can’t read everything, that’s why I put it out there and ask people to check it. If you were interested in due diligence rather than scoring points with snide comments, you would haveprovided links to the two datasets you would like me to add. I’ll guarantee that I’m not going to try to guess which ones you are referring to.

    When you do so, I’ll be glad to include them. Until then, you’re just trying to score points and make unpleasant allegations without doing your due diligence. You have to show your data and code, just like me.

    Finally, these are minor issues, which do not alter my conclusions in the slightest. My three conclusions had to do with a) uncertainty, b) UHI, and c) the difference between BEST and the other ground stations. Your nitpicking does not change any of those. I fail to see why you assign such importance to your claims, as if I had made some fundamental error that changed my conclusions. My conclusions are unaltered by your claims.

    w.

  52. Robert says:
    October 24, 2011 at 8:46 pm

    Mistake on the last post. Willis did use NOAA he just labelled it GHCN which I just assumed it meant just using the raw GHCN rather than NOAAs method (I only noticed when I saw it linked to NOAA).

    Please show due diligence next time around, as a nasty acquaintance of mine once remarked.

    Point still stands on GISS. The only one that doesn’t fit is Hadley and we know why that is.

    You said above that if we make the changes, GISS looks just like Hadley. How does that help things?

    w.

  53. Actually, is there unadjusted data on the percent of all stations showing a temp rise versus those that show no rise versus those that show a decline? Given the deceitfulness of averaging in the Southern Hemisphere (flat trend) with the Northern (increasing trend) to show an increasing GAT I get the distinct impression that the denial of the UHI effect is merely to cover up the fact that many or most of the non urban stations will show a declining trend and not an increasing trend.

  54. dixonstalbert says:
    October 24, 2011 at 9:07 pm

    Thank you for posting Willis.

    I was not clear how you produced Figure 1 of ” their actual un-smoothed monthly data:”

    Can you post step by step instructions?

    Downloaded the data. Opened it in excel. Made the graph using their “monthly” data. Used their “monthly uncertainty” numbers for the error bars. Not sure exactly what you’re asking for here, Dixon.

    All the best,

    w.

  55. . Interestingly the BEST data show only a very small acceleration in the GMT trend from 1991 to 2000, and an actual deceleration from 2001 to 2009, which belies their claim “the world is warming fast”, which should have read “the world is warming more slowly” (according to BEST) – but then they don’t do calculus at Berkeley anymore do they?

  56. “Now that the BEST folks have… succeeded in deceiving many people into thinking that Muller is a skeptic…”

    Perhaps an overly strong wording of a mistaken impression? As far as I can tell, Muller has long been a skeptical warmist. And an honest one.

    Muller is so skeptical of those involved with “Mike’s trick to hide the decline”, that he won’t read any work by a Team member. So Hadley temps are out. And he doesn’t trust GISS either, hence BEST. He is skeptical of all proposed climate policies, seeing none as credible solutions to warming. Further, he is clear about the uncertainty of water vapor feedback in projected warming; he states (at 4:10) that although increased evaporation is not thought to result in more clouds, “if cloud cover were to increase by 2% over the next 50 years, we wouldn’t have global warming.”

    That’s not to say that BEST’s papers will pass peer review without changes.

  57. Something I dont quite understand. In the early 1970’s the National Academy of Science published a climate reconstruction showing that temperatures fell by 0.7C ( about 1.3F) between 1940 and 1970. This was the basis for many articles in both science and environmental journals suggesting we were heading for dangerous global cooling (anthropogenic of course). The modern reconstructions now show no cooling over this period. Did the historical data change with time and if so, how does long documented historical data change with time? Was the highly accredited NAS incompetent in generating their climate record? Or is the change due to more recent “adjustments” to the historical data. If the latter, maybe the adjustments are valid, maybe not but lets not forget if the 0.7C fall was in fact correct it would wipe out the entire claimed anomolous warming. So the adjustments would be 100% of the effect being claimed. Would such a scenario be acecpted in any other branch of science, and almost without questioning or scrutiny?

  58. From dixonstalbert on October 24, 2011 at 9:07 pm:

    I was not clear how you produced Figure 1 of ” their actual un-smoothed monthly data:”

    Can you post step by step instructions?

    1. Download and unzip the analysis chart data.

    2. Prep the data for the spreadsheet with a word processor. Open Full_Database_Average_complete.txt, which has the monthly results. Copy just the numbers to a new text document. Using the Replace command, replace all double spaces with single spaces until only single spaces are left. That is a trick I taught myself, simplifies things tremendously.

    3. In a new spreadsheet, do a “Paste Special” of the prepped data, Ctrl-Shift-V. (I use OpenOffice, YMMV.) When prompted, mark “space” as the delimiter. Voila, data fills in the correct rows and columns. If I do a “raw” copy without reducing the spaces then normally the data doesn’t stay in the correct columns, I get too many columns, etc.

    4. For the X-axis, make a column that is the year + (month-1)/12. Close enough decimal value for this.

    5. Add two columns. One is Monthly:Anomaly + Uncertainty (Unc.), one is -Unc.

    6. Apply standard chart-fu, make a XY (scatter) graph, lines only. Graph Anomaly, +Unc., and -Unc. Make +/-Unc. the same shade of grey, give them enough width to blend into a grey mass.

    7. After that it’s just Titles, Labels, labeling the spreadsheet columns, the usual nice touches for making it look pretty and legible.

    Note: the last two months in the file, Months 4 and 5 of 2010, have something really screwed up, at least the copy I downloaded, might have changed. Uncertainty goes from around 0.1°C for previous months to around 2.8. Consider dropping off those months or perhaps all of 2010 to make your chart extra pretty.

  59. Willis

    Are you sure about BEST’s motivation? I took Mann’s Hockey Stick, cropped everything but 1800-2000, re-scaled it to fit the BEST reconstruction graphic and constructed a blink gif. The first 50 years leaves one either doubting BEST or Mann, given their relative statistical clout, if I were Mann I would not want this graphic shown in the Ball case courtroom!

    1800-2010 comparison, BEST-Hockey Stick

  60. Willis I liked your reply to MPaul. You and Lubos Motl way into the scientists playing politicians with exactly the scorn they deserve. Please keep it coming they need to be made to see their stupidity like Peter Gleick.

  61. On checking through their monthly station data, I was surprised to find that BEST really don’t have anything but GHCN data pre-1850. So when they take the analysis back to 1800 when others don’t, they are presumably hoping that their statistical methods will reduce errors. I doubt hat they can make so much difference. I’ve listed the BEST and GHCN station records here

  62. pwl says:

    1800 1 -1.447 2.505 -0.890 0.766 -0.461 0.524 -0.424 0.512 -0.477 0.475
    1800 2 -2.132 2.928 -0.898 0.735 -0.463 0.523 -0.425 0.508 -0.481 0.474

    2010 4 -1.035 2.763 NaN NaN NaN NaN NaN NaN NaN NaN
    2010 5 1.098 2.928 NaN NaN NaN NaN NaN NaN NaN NaN”

    This is bogus since it is not the raw data but once more mysteriously processed data.

    Is the data actually accurate to 3 decimal places in the first place. That would imply something capable of reading to a thousanth of a degree. Not sure such things existed in 2010, let alone 1800!

  63. When it gets too hot in the city, people get into their cars and drive out to the country or the beach. Why?

    How big was Los Angeles in 1811? How big is Los Angeles now?

    UHI proven. Q.E.D.

  64. Willis, I know you will think me a pedant (and probly I am) but I think it adds clarity to the UHI discussion to refer to Delta UHI over time, coz that is what affects the temperature records. Not the fact that urban environments can have a UHI effect.

  65. Willis:

    At October 24, 2011 at 5:54 pm you say:
    “… There is a commonly believed fallacy out there, which is that good correlation of data indicates good correlation of trends. I discussed this in a post called “GISScapades“.”

    Yes!
    I and a large group of others wrote a critique of the various surface global temperature reconstructions. Their data show good correlation but
    (a) data for individual years differ by more than their stated accuracy
    and
    (b) the trends differ significantly between the data sets.
    We then showed that the data sets are not valid indicators of mean global temperature (MGT) according to either of the possible understandings of what MGT is.

    We failed to obtain publication of our paper because the data sets kept being altered by their compilers between submission of our paper and its acceptance for publication. I reported this to a UK Parliamentary Select Committee that was conducting an investigation (that became a ‘whitewash’) of the ‘climategate’ affair.

    Although it seems very likely that MGT has risen over the last century, it is not possible to determine by how much MGT has changed over the last century. And the BEST data do not change this.

    Richard

  66. mondo, if it’s any help I don’t think you’re a pedant as most pedants obsess about spelling ;-). On a broader cultural note I detect that Michael Mann might be from a poorer hick background from the use of the ‘Mill-yhun’ by Willis. Is he a rural type person regarded as lower class by the oligarchy?
    I’m outside US and sometimes have trouble understanding the social mores of your culture

  67. One more time, the money quote to me…
    “The disagreement between the four ground-based results also begs for an explanation. Note that the records diverge at the rate of about 0.2°C in thirty years, which is 0.7° per century. Since this is the approximate amount of the last century’s warming, this is by no means a trivial difference.”

    Indeed!!. And why, after 1998 does the divergence widen considerably. It appears that the divergence of land based readings, from each other and the satelite record, is growing faster then any observed warming, which since 1995 is statistically not significant. Take a look, via eye ball, the divergence swings between .1 amd .2 degrees untill about 1998 to 2000, then the divergence rapidly changes to .3 then .4 degreees. An divergent increase of about .2 degrees in 10 years during a period when three of the five data sets show a cooling from the 98 high!! Additionally the data sets no longer move in harmony in the last decade. So how do they claim that all the data sets agree when in one nine year period (98 to 07) some show cooling of about .15 degrees, and others show a warming of about .25 degrees?. Any thoughts anyone?

    Also michael hammer says: October 24, 2011 at 11:11 pm, raises some serious questions over how the sets have changed over time.

  68. From Willis Eschenbach on October 24, 2011 at 10:18 pm

    (…) However, the GISS data set says:

    sources: GHCN-v2 1880-09/2011 (meteorological stations only)
    (…)
    In addition, the URL says:

    monthly.land.90S.90N.df_1901-2000mean.dat
    (…)

    Willis, that is an inaccurate sourcing note. NOAA-NCDC says here they moved on to GHCN-M version 3. They were updating v2 a while longer, according to the note at the section near the bottom where the summary sets are available. URL for that v3 set matches what you posted:
    ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land.90S.90N.df_1901-2000mean.dat

    At that note is a link to the ftp directory for v2, current “last modified” is July 20, last value in the indicated monthly file is June 2011.

    GISS could not be using v2 for the most recent months, they should change the attribution. Someone better notify Hansen about the v2 set: It’s dead, Jim.

  69. Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media. Sure, I could pretend Muller is an honest and honorable man like you recommend. But his actions have shown him to be a cunning snake. It is not my habit to address snakes as though they were honorable men.

    You lost me.

  70. When did Dr Muller become a Skeptic? I seem to recall watching a lecture by Dr Muller in which he provides evidence that increasing CO2 in the atmosphere, because it is a greenhouse gas, will cause increased warming.

    UHI and changes to land use/landscape cannot be ignored, e.g. soil, bitumen and concrete absorb more radiation than grass and trees.

  71. From aaron on October 25, 2011 at 4:15 am:

    In the first graph, are the data points connected by lines, or are the points that dense?

    Just lines.

    I’d like to see it without lines.

    I replicated that graph for this comment. Without lines, with the spreadsheet using little symbols for the points, it looks like a large air nozzle spewing confetti. There are more than 2500 points.

  72. I also would love to see an oceans only graph layered into the five data sets chart to see which data set follows the ocean air temp chart the most accurately.

  73. Ladies and Gentlemen, the International Panel on Climate Shenanigans is proud to announce the nominations for the golden Pacharan International Shenanigans Statues for 2011.

    There are six nominations for the Creative Research And Publicity award.

    From California: BEST Birks Earth Surface Tragedy

    From East Anglia: CRUD Climate Research Universal Disambiguation

    From Exeter: HASH Hardly Atmospheric Surface History

    From Yorkshire: LUST Leeds Ultimate Surface Temperature

    From Pennsylvania: MESS Mans Earth Surface Study

    From Exeter again: MOST Metro Official Surface Temperature

    Please submit your vote in the next 14 days using the Pal Approval Streamlined System.

    The winner will be announced in Durban in early December.

  74. Addendum to last post:
    That’s more than 2500 anomaly points. Each has two uncertainty points with them (+ and – unc.). Thus over 7500 points total to graph.

    It looks much better as only lines.

  75. Louis October 24, 2011 at 9:45 pm
    The BEST press release makes the following claim about UHI:
    “The urban heat island effect is locally large and real, but does not contribute significantly to the average land temperature rise. That’s because the urban regions of the Earth amount to less than 1% of the land area.”
    Aren’t they shooting AGW in the head (or themselves in the foot) with that statement? I mean, if the urban regions of the Earth are not contributing significantly to the average temperature rise of the planet, how can they then turn around and claim that humans are the main cause of global warming? Aren’t the urban regions of the Earth where the people are? Doesn’t most energy use occur in urban regions? Are they saying that people in rural areas are somehow at fault for warming the earth even though they are not warming their local region? What am I missing here?

    You’re missing the fact that AGW is supposed to be due to the global average atmospheric concentration of greenhouse gases, esp. CO2. The UHI effect is primarily due to heat retention by construction materials in buildings, roads, etc., and waste heat from energy use.

  76. Septic Matthew says:
    October 25, 2011 at 4:07 am
    Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media. Sure, I could pretend Muller is an honest and honorable man like you recommend. But his actions have shown him to be a cunning snake. It is not my habit to address snakes as though they were honorable men.

    You lost me.

    Some education ………………….

    Splendid hunting ground
    Rikki Tikki Tavi, Rudyard Kipling (1894) Can skip to Part 3.

  77. Where is the missing data used for the smoothing?

    From Full_Database_Average_complete.txt, I can see the 20-yr running average ends 10 years before the end of the records. That makes sense, it’d use 10 yrs before and after. They’ve run out of data, the 20 yr smoothing stops.

    But the records start at 1800, including the smoothed values. So they would need 10 yrs of data from before 1800 to start the 20 yr smoothing. Where is it? Same issue with the other shorter-length smoothed values. This is supposed to be the data, but 10 yrs are missing. Did they, identifying it with the appropriate scientific/mathematical/statistical terminology, just “make up” the starting data or initial smoothing results?

  78. What exactly is the BEST temperature dataset? I had assumed it was some kind of average of GISS, HADCRUT and NOAA, but the graph labeled fig 3 has confused me. Here the BEST temperatures are higher than any of the others – not an average like I expected. How do they do it?

  79. The first thing I thought of when I saw Fig 1 was a funnel.

    So they’ve gone from beating us over the head with a hockey stick, to using a funnel to…

    Never mind. Any further comment would just result in a ban.

  80. I would suggest moving the ‘normal’ for the satellite data down, thereby moving the anomoly for that record upwards. That would place it more in line with what you expect to see.

  81. Willis Eschenbach says:
    October 24, 2011 at 6:31 pm
    …Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media.

    Willis, I understand that you and Anthony have been subjected to some pretty shoddy treatment by the BEST team. And I am not suggesting that people should not be angry. But I think that our side (the skeptics) is winning the battle of ideas. Our mission now is to convert the independent thinkers. And we do this by being on the side of reason. I think we can expose all of their dirty tricks and duplicitousness without calling them “media whores” — let the reader come to that conclusion for themselves. A little bit of mockery and ridicule is ok (“once again Muller has demonstrated that the most dangerous place to stand is between him and a microphone”) but I think if it goes too far it alienates new readers. Anyway, I’m not here to lecture. Its just my opinion — take it for what its worth.

    I’m a big fan of your work.

  82. BlueIce2HotSea says:
    October 24, 2011 at 10:56 pm

    “Now that the BEST folks have… succeeded in deceiving many people into thinking that Muller is a skeptic…”

    Perhaps an overly strong wording of a mistaken impression? As far as I can tell, Muller has long been a skeptical warmist. And an honest one.

    Muller is so skeptical of those involved with “Mike’s trick to hide the decline”, that he won’t read any work by a Team member. So Hadley temps are out. And he doesn’t trust GISS either, hence BEST. …

    Here’s Muller on the subject:

    “A quote came out of the emails, these leaked emails, that said “let’s use Mike’s trick to hide the decline”. That’s the words, “let’s use Mike’s trick to hide the decline”. Mike is Michael Mann, said “hey, trick just means mathematical trick. That’s all.” My response is I’m not worried about the word trick. I’m worried about the decline.”

    Me, I’m not worried about the decline. I’m worried about the “Nature trick”, as this refers to egregious scientific malfeasance. Here’s more about Muller (emphasis mine):

    UC Berkeley physicist, and longtime climate skeptic, Richard Muller has finally gone on the offensive, publicly admitting he was wrong to doubt global-warming data in a piece for The Wall Street Journal.

    The outspoken professor, who gained notoriety in the climate-denial community for his rants against Al Gore and criticism of Climategate, decided to take matters into his own hands earlier this year by creating an independent study to assess specific objections raised by climate skeptics.

    Muller and a team of researchers working under the Berkley Earth Surface Temperature Project, analyzed more than 1.6 billion data points collected from more than 39,000 temperature stations around the world to find that their results were “close to those published by prior groups,” including estimates from the Intergovernmental Panel on Climate Change.
    The evidence proved convincing, even to a habitual climate disbeliever.

    Global warming is real. Perhaps our results will help cool this portion of the climate debate,” Muller concluded.

    Parse it the way you want it, I call BS on a physicist who makes a statement like “Global warming is real”. There’s too many twists, too much deniability, too many bogus assumptions in that. From a physicist of Muller’s stature, that statement is as designedly deceptive as Mikes “Nature trick”.

    In addition, his results are not “close to those published by prior groups”. They are diverging at 0.7°C per century, which is larger than last century’s purported warming … how is that “close” in any but the “Nature trick” sense of the word?

    w.

  83. Gras Albert says:
    October 25, 2011 at 1:03 am

    Willis

    Are you sure about BEST’s motivation? I took Mann’s Hockey Stick, cropped everything but 1800-2000, re-scaled it to fit the BEST reconstruction graphic and constructed a blink gif. The first 50 years leaves one either doubting BEST or Mann, given their relative statistical clout, if I were Mann I would not want this graphic shown in the Ball case courtroom!

    1800-2010 comparison, BEST-Hockey Stick

    Their scientific motivation seems to be to get the best dataset and analyze it as best they can.

    Their political motivation seems to be to use that dataset to prove that “global warming”, as Muller deceptively calls it, is real. He means Anthropogenic Global Warming by that term … or not, as the moment requires. He is quite willing (see my last post) to use “global warming” to mean just that the earth is warming, at times when he is being interviewed.

    Of course, he must know that the media will take that to mean AGW is real, and yet he makes no attempt to stop them from that error. Then he can deny ever having said AGW is real, and at the same time the media are trumpeting “Skeptic Scientist Declares Global Warming is Real”. It’s what you call a “win-win situation”.

    I don’t think Muller cares for Mann, he knows his science is way wonky. So I don’t think he cares if his work contradicts Mann’s work.

    w.

  84. Mark says:
    October 25, 2011 at 1:55 am

    pwl says:

    1800 1 -1.447 2.505 -0.890 0.766 -0.461 0.524 -0.424 0.512 -0.477 0.475
    1800 2 -2.132 2.928 -0.898 0.735 -0.463 0.523 -0.425 0.508 -0.481 0.474

    2010 4 -1.035 2.763 NaN NaN NaN NaN NaN NaN NaN NaN
    2010 5 1.098 2.928 NaN NaN NaN NaN NaN NaN NaN NaN”

    This is bogus since it is not the raw data but once more mysteriously processed data.

    Is the data actually accurate to 3 decimal places in the first place. That would imply something capable of reading to a thousanth of a degree. Not sure such things existed in 2010, let alone 1800!

    That is the raw data. Column 1, year. Column 2, month. Column 3, monthly data. Column 4, uncertainty of monthly data. Column 5, annual average data. Column 6, uncertainty of annual data. Column 7, 5-year average data. … etc.

    The averages are centered averages. As a result, at the end of the dataset, the averages are omitted, since there is not enough data to make the average. That’s why they say NaN, nothing underhanded at all.

    The averages are to a thousandth of a degree, which seems like false accuracy to me, but doesn’t bother me, it’s just data.

    w.

  85. mondo says:
    October 25, 2011 at 2:35 am

    Willis, I know you will think me a pedant (and probly I am) but I think it adds clarity to the UHI discussion to refer to Delta UHI over time, coz that is what affects the temperature records. Not the fact that urban environments can have a UHI effect.

    Yeah, probably you are, but that’s OK. You are right that it is a change in UHI (∆UHI) that affects the trends, not the UHI itself.

    However, (presumably) the UHI is always changing, because in general the cities are always growing, new areas paved, more buildings built, more UHI. So in practice the difference doesn’t really make a difference.

    w.

  86. Richard S Courtney says:
    October 25, 2011 at 2:42 am

    Willis:

    At October 24, 2011 at 5:54 pm you say:
    “… There is a commonly believed fallacy out there, which is that good correlation of data indicates good correlation of trends. I discussed this in a post called “GISScapades“.”

    Yes!
    I and a large group of others wrote a critique of the various surface global temperature reconstructions. Their data show good correlation but
    (a) data for individual years differ by more than their stated accuracy
    and
    (b) the trends differ significantly between the data sets.
    We then showed that the data sets are not valid indicators of mean global temperature (MGT) according to either of the possible understandings of what MGT is.

    We failed to obtain publication of our paper because the data sets kept being altered by their compilers between submission of our paper and its acceptance for publication. I reported this to a UK Parliamentary Select Committee that was conducting an investigation (that became a ‘whitewash’) of the ‘climategate’ affair.

    Another way to hide the decline … just alter your data sets on a regular basis …

    Thanks, Richard, keep pounding at the gates,

    w.

  87. David says:
    October 25, 2011 at 4:47 am

    I also would love to see an oceans only graph layered into the five data sets chart to see which data set follows the ocean air temp chart the most accurately.

    The Berkeley dataset doesn’t cover the oceans, just the land.

    w.

  88. mpaul says:
    October 25, 2011 at 8:06 am

    Willis Eschenbach says:
    October 24, 2011 at 6:31 pm

    …Me, I’ve had it up to here with being lied to by Muller, I’m fed up to my eye-teeth with his tricks and his whoring for the media.

    Willis, I understand that you and Anthony have been subjected to some pretty shoddy treatment by the BEST team. And I am not suggesting that people should not be angry. But I think that our side (the skeptics) is winning the battle of ideas. Our mission now is to convert the independent thinkers. And we do this by being on the side of reason. I think we can expose all of their dirty tricks and duplicitousness without calling them “media whores” — let the reader come to that conclusion for themselves. A little bit of mockery and ridicule is ok (“once again Muller has demonstrated that the most dangerous place to stand is between him and a microphone”) but I think if it goes too far it alienates new readers. Anyway, I’m not here to lecture. Its just my opinion — take it for what its worth.

    I’m a big fan of your work.

    mpaul, as I said before, you are likely right. And certainly, tactically you are right. As the old saw goes, “You catch more flies with honey than with vinegar”. And certainly humor is the best, as you say, “once again Muller has demonstrated that the most dangerous place to stand is between him and a microphone”.

    However, I’m not really here to catch flies, or certainly not entirely here to catch flies. I’m here to tell the truth about what I see and what I think and feel about what I see, particularly regarding scientific malfeasance.

    I’m one of the few scientists to do so. Most of them say nothing about anything bad or even slightly negative. Some of them use carefully parsed and chosen words to express their displeasure without ruffling a hair on their heads, and without mentioning a single name. See, e.g., the general response of the climate science community, skeptics and AGW supporters alike, to the Climategate revelations—a haunting silence, with occasional murmurings about the actions, and not one scientist’s name ever spoken.

    So while it is tempting to take up the “mention your concerns gently and never name names” kind of approach, I just don’t like the feeling it leaves in my mouth. These guys are not agitating for something good, or even for something neutral. They are making a concerted effort to raise the price of energy for everyone, including the poorest of the poor. If they are successful they will keep the poor impoverished for generations.

    And getting all “honey-words” about that, well, that is a very difficult thing for me to do. However, your advice is good, and I will strive to do that wherever I can do so without abating my desire to actually tell the truth. Humor is the best, as you point out … but somehow smart-but-brainless wealthy scientists working overtime to raise energy costs for people living on a dollar a day is not all that funny … odd how that works.

    My thanks for returning with your thoughts, much appreciated, mpaul.

    w.

  89. william says:
    October 25, 2011 at 8:20 am

    ‘then broke a confidentiality agreement’

    surely a court case.

    It was a handshake deal between ostensibly honorable men. When one man turns out to be … let me take mpaul’s suggestion and describe Muller as “less than honorable” in that situation, court is often an expensive and ultimately futile exercise.

    Plus the optics are bad, it would make Anthony look like a sore loser when in fact he is the injured party.

    w.

  90. Willis Eschenbach says:

    I’m tired of people playing nice when folks are trying to sentence the poor to a lifetime of un-obtainably expensive energy. I’m sick of the silence surrounding egregious scientific malfeasance. I’m upset, yes, and you’re right, it does affect my writing. I’m upset that people are not outraged at this attempt to assuage some liberal guilt by making energy, the lifeblood of the poor, more and more and more expensive with each passing day.

    I don’t think they are going to sentence the poor to more expensive energy. What they want to do is redistribute some of the higher energy taxes to the poor to help pay for the higher energy costs as well as help their collective net worth move closer to the rich (as the collective net worth of the rich decreases).

    They also want to do this on a global level so that at some point in the future, all nations have roughly the same per-capita wealth and standard of living.

    What I see are technocrats using science to achieve socialistic goals.

  91. With regard to UHI, I thought BEST compared rural stations to all stations and deduced that the difference was the UHI. As this difference showed no trend, this meant UHI did not skew the overall figures.

    In fact, this approach simply implies that the UHI trend for all stations is similar to the UHI trend for rural stations. Any habitation has a UHI effect and, as the effect is logarithmic in relation to population, a one horse town which becomes 2 horses and a goat might show a similar UHI increase as an expanding city.

    The UHI effect is a serious source of bias and, for me, the BEST methodology does not trump previous work in this field.

  92. Willis,

    In line with your goal of using more humor, I think we are missing information buried in the acronym for the the Berkeley project. Like you, I grew up in the mountains of northern California and so take an earthier analysis of what the output from BEST is. It is, afterall, the BEST P. And so my mind wandered back to long treks along Interstate 80 in an open air Volkswagen consuming copious quantities of coffee and caffeinated beverages and having to wait for 50 or 60 miles for the next rest stop. The output was similar to what you had to analyze, but more satisfying. BEST P indeed.

    Paul

  93. kramer says:
    October 25, 2011 at 9:47 am

    Willis Eschenbach says:

    I’m tired of people playing nice when folks are trying to sentence the poor to a lifetime of un-obtainably expensive energy. I’m sick of the silence surrounding egregious scientific malfeasance. I’m upset, yes, and you’re right, it does affect my writing. I’m upset that people are not outraged at this attempt to assuage some liberal guilt by making energy, the lifeblood of the poor, more and more and more expensive with each passing day.

    I don’t think they are going to sentence the poor to more expensive energy. What they want to do is redistribute some of the higher energy taxes to the poor to help pay for the higher energy costs as well as help their collective net worth move closer to the rich (as the collective net worth of the rich decreases).

    They also want to do this on a global level so that at some point in the future, all nations have roughly the same per-capita wealth and standard of living.

    What I see are technocrats using science to achieve socialistic goals.

    Seriously? Your claim is that some poor shlub living on a dollar a day and sleeping on a back street in Bombay, whose energy costs have been jacked by the first-world scientists insisting that the World Bank not fund inexpensive coal fired power plants in India, is going to get a “tax redistribution” to “help pay for the higher energy costs”???

    I run out of question marks to question that astounding claim … kramer, you truly haven’t thought this one through any further than the first-world scientists have.

    w.

  94. @Willis
    You write: “So rather than you advising me to be all calm and peaceful about this, how about I advise you to be less calm and peaceful, and to stand up and denounce bad science wherever you find it?”

    YES!! YES!!!

    There is a growing portion of sceptics or at most “semi-sceptics” I would call it, that are so focussed on appearing “correct” that they dont really ever make a difference at all.
    It IS “dangerous” to point out anything significant, but if we play to safe, we dont play at all.
    BRAVO Willis.

    How much champagne would it take to make you look at this article, and leave a comment?
    “http://hidethedecline.eu/pages/posts/ruti-global-land-temperatures-1880-2010-part-1-244.php”
    This is the kind of article I have asked no one to publish, because I cant PROOVE that all I do is correct. But truth is, its the best real alternative to landtemperatures there is, SADLY SADLY, and this does mean that im even near perfect. it just means that the rest appears not honest.

    K.R. Frank

  95. @Willis
    “So rather than you advising me to be all calm and peaceful about this, how about I advise you to be less calm and peaceful, and to stand up and denounce bad science wherever you find it?”

    I like that spirit!
    ((Sorry if some of this is already in a comment, I had some internet problems))

    K.R.Frank

  96. Frank Lansner says:
    October 25, 2011 at 10:46 am

    … How much champagne would it take to make you look at this article, and leave a comment?
    “http://hidethedecline.eu/pages/posts/ruti-global-land-temperatures-1880-2010-part-1-244.php”

    I’m a cheap date …

    I looked at the site. I see a couple of issues. You are putting together what you call the RUTI, the “Rural Unadjusted Temperature Index”. The implications are:

    1. You can unambiguously divide the world’s temperature stations into two groups, “Rural” and “Not-rural”.

    2. Adjustments are bad.

    I’m not sure I’d agree (in general) with either of those. First, what criteria are you using for “Rural”? BEST uses MODIS data, GISS uses night-lights, GHCN uses a similarity algorithm to adjust anomalous sites, Roy Spencer uses log(population), and Ross McKitrick uses economic development … which one are you using, why are you using it, and where is the dividing line?

    Second, adjustments, while they are to be decried, may be important or even necessary. For example, the MMTS electronic temperature sensors tend to read a bit higher (from memory) than the Stephenson Screen thermometers. When the changeover is made at a particular station, an erroneous trend is introduced, where it looks like it’s warming but it isn’t. It seems to be your contention that such an erroneous trend should not be corrected for.

    HTH,

    w.

  97. Lets look at the bright side here. We have an accurate temperature reading with error bars, something that I have never seen before. There are valid arguments that these bounds are too narrow, but any small child can see the shape (to quote my two year old, “Twiangle”). The uncertainty growth also makes perfect intuitive sense and can be easily understood by laymen. This then raises the obvious question: If this is the temperature record 200 years ago, how can we be certain about what it will be 200 years from now? Is that flat line in the hockey stick just a giant “we don’t know” (answer= yes)?

    That gets people asking questions. When people ask questions, they typically drift at least to center if not to the skeptical camp.

  98. Hi Willis, that was a fast responce time!!

    You write. “1. You can unambiguously divide the world’s temperature stations into two groups, “Rural” and “Not-rural”.

    This is true.
    In the general RUTI introduction

    http://hidethedecline.eu/pages/posts/ruti-global-land-temperatures-1880-2010-part-1-244.php

    I write:
    “RUTI is not all rural nor all unadjusted. However, RUTI is a temperature index aiming to use still more rural data (less use of city and airport data), still more unadjusted data when available and reasonable.”
    The method I mostly use to determine rural status, is google maps. I have checked a thousand stations this way. The relative growth of population around a station that has large UHI effect, and therefore stations outside urban areas on google maps are preferred. This means that stations named after a large sity may be used if stations is well outside city, allthough declared “Urban” by GHCN.

    Adjustments: There are situations where I accpet adjustments done (Albany, Beyrouth etcetc.).
    What I do is the HARD WORK. I track areas of similar trend, and it takes forever. But this way it has been possible to get a rather good idea if a station is indeed outlier or not. That is, if it looks correct to adjust a station.

    Example DE BILT.
    I CLAIM BOLDLY that i show very very solidly that the area NW Europe DOES support the DE BILT station and therefore adjustment is NOT acceptable nor included in RUTI:

    http://hidethedecline.eu/pages/ruti/europe/nw-europe-and-de-bilt.php

    Example DARWIN
    No adjustment justified either:

    http://hidethedecline.eu/pages/ruti/australia.php

    Example of very limited public availability of East Chinese rural data… But when held together for the whole region, suddenly you see clearly what was hidden. “Grafitty data” from China:

    Etc etc.
    What I have done is hard work, and to get the overall result has taken all evenings weekend of 6 months… :-) And I show openly what I do and am ready to change what is concluded wrongly.

    Thankyou Willis for commenting ;-)

    K.R: Frank

  99. Wops, Willis, I forgot to mention: I use GHCN Unadjusted as primary data source, although rather limited in years publicly available, these data are often i complance with original data i have found.

    I also use NORDKLIM, and more where I have reason to believe we have mostly origina data.

    K.R. Frank

  100. Willis,
    You should have looked to see whether your chart looks like BEST’s comparing the different records. It doesn’t.

    http://berkeleyearth.org/analysis.php

    The issue with GISS is shown here:

    http://rankexploits.com/musings/2010/the-great-gistemp-mystery/

    I do think that a little critical thought would have told you that the GISS graph was wrong. We all know that Hadley is the outlier not GISS.

    So lets consider it this way: BEST, GISS and NOAA are all very similar when properly compared using land-only and Hadley is noticeably lower in recent years. Why? Well simply because CAM is too restrictive for many sites particularly in the Arctic (etc).

    Anyways the only disagreement is between Hadley and BEST and “supposedly” the satellites with BEST but if you look on the STAR analysis publication website you will see that their satellite record is coming, with more accurate satellite combining and what looks to be a significantly higher TLT trend when they actually do the product based on the relationship between TMT and TLT. I wouldn’t hold my breath that RSS and UAH are the end all product of the sat work.

  101. kramer says:
    October 25, 2011 at 9:47 am

    They also want to do this [redistribute wealth] on a global level so that at some point in the future, all nations have roughly the same per-capita wealth and standard of living.

    What I see are technocrats using science to achieve socialistic goals.

    Therefore, kramer, the obvious and proven Communistic outcome once again is going to be a trend among all nations and people toward the holy “equality” of equal impoverishment and slavery, except of course in the case of the Socialist technocrats themselves, who will necessariy thereby own all the wealth themselves since they have the power to redistrubute it.

    And, as usual, the totality of wealth will progressively decrease, because once redistribution of “wealth” starts and then continues toward “equalizing” it, eventually no one has any incentive to produce it – congenital mental and physical slaves, and Saints, excepted.

    So that, finally, the “poor” = the rest of us, will in fact be lucky if the noble Communist Party technocrats can manage “to sentence the poor to more expensive energy” even if they wanted to, because there simply won’t be very much of it to go around, and lucky if we poor have any means at all left to pay for it, as the “wealth” keeps getting progressively redistributed, and thus lucky to even keep on existing.

    kramer, that’s the “science” your technocrats are really enacting, and which you apparently support. So is it any wonder that their CO2 = CAGW “science” is as equally bad, especially in the sense of being no more than an evil unscientific propagandistic subterfuge used to subserve evil ends?

    kramer, when the noble socialist technocrats come to own “the means of production”, they own you, and you finally become disposable!

  102. Willis

    I’m not sure I agree with you calling ‘em “media whores”.

    I have been told some whores are quite nice, if misunderstood folk. Couldn’t vouch for it myself, though.

    And a lot of snakes are quite harmless, if slithery.

    But, with these little quibbles, I think this is another one of your stonking, unmissable pieces. When you’ve finished the autobiography, please can you put together an anthology of your climate writings?

    Pretty please?

  103. This entire CON is MORE of the same, PRETENSE that MYSTERIOUSLY ADJUSTED DATA are REAL DATA.

    MYSTERIOUSLY ADJUSTED DATA are DATA YOU CAN’T GET EVERY FACT ABOUT.

    This is as OLD as the 5-LEG COW joke.

    “So: we have a cow: it has 4 legs, and a tail. But we need to have another leg for this joke to work, so let’s say, the cow’s tail, is a leg.”

    “So: NOW we have a 5 legged cow – RIGHT?”

    W.R.O.N.G.
    You have a 4 legged cow.
    You just CALLED it a 5 legged cow.

    GISS, NOAA, CRU, etc data are A.D.J.U.S.T.E.D. to MAKE INSTRUMENTAL RECORDS look WARMER than they TELL.

    This UNALTERABLE REALITY is why Phil Jones’ statement in 2005, “the scientific world would come down on me in no uncertain terms ***IF I SAID the WORLD had COOLED since 1998.***

    *** OK IT HAS *** but it’s (and here’s the truly telling part of this for those of you wondering just what the ultimate question about all this, is: watch carefully) Only seven years of data (every year FROM ’98 to ’05)
    *** AND it I.S.N’T. S.T.A.T.I.S.T.I.C.A.L.L.Y. S.I.G.N.I.F.I.C.A.N.T. ***

    THAT STATEMENT of non statistical significance to the COOLING since ’98 is what is TRULY TELLING here: Note, that in the email he said it and no one else said a word about “Hey Phil, bud, you’re wrong: the world is still warming.”

    And the reason Phil stated no statistically significant cooling is because: WATCH CAREFULLY KIDS who are just learning of this: HE was REFERRING to the RAW DATA being COLLECTED WORLDWIDE, which SHOWED PRECISELY THAT: A little COOLING, but APPARENT STASIS: not EVEN COOLING to the STATISTICALLY SIGNIFICANT LEVEL.

    The DATA have been SYSTEMATICALLY WASHED to MAKE it APPEAR WARM. The EARTH has not warmed for MANY YEARS. The CLAIM is a FALSE ONE.

    Look up BBC PHIL JONES INTERVIEW 2010. Jones was not discharged from his job on agreement he ADMIT he was WRONG about SOMETHING to the B.B.C. that he had CLAIMED, the BBC had MIS-REPORTED.
    He was CAUGHT in CLIMATE GATE preparing to RUIN the CAREER of a BBC REPORTER.

    Look at the qustion PUT to HIM by the BBC:” DO you AGREE the WORLD has NOT WARMED since 1998?”
    HIS ANSWER: Y.E.S.
    He then dessiminated on various probabilities saying there isn’t a 99 or 98 percent chance but rather a lesser one but that it is indeed warming. But HE was FORCED to ADMIT what HE had ALREADY SAID, IN 2005, WHILE NOT UNDER DURESS, and that NOT ONE SOUL CORRECTED HIM ABOUT: The WORLD stopped WARMING in the MID ’90s.

  104. Actually I mis-stated the question by the BBC: the question was “Do you agree the world has not warmed since 1995.”

    This ENTIRE SCAM has been NOTHING: from the VERY BEGINNING: but a DATA WASHING scam.

    The fact it’s based on physics a child can debunk is beside the point. This has been a LEGAL issue from the beginning. The fact
    THERE IS NO TROPOSPHERIC HOT SPOT shows you how ACCURATE claims are, of a class of gases HEATING the earth to a measurable degree, when the VASTLY OVERWHELMING one: water – is a phase change REFRIGERANT that covers 70 percent of the earth.

    Why is it that MANDATORY INSTRUMENTAL DETECTION of this voodoo, fails to detect ANY greenhouse gas correlation, over and over? HuH?

    LoL. Why doesn’t the INFRA RED ASTRONOMY FIELD even show everyone the RISING INFRA RED visible through the proper filters, that correlates to manmade gas ratios in the atmosphere rising?
    Because it HAS not been WARMING for YEARS.

    What turned off the Atlantic storm system? MORE HEAT?
    Or LESS than when there are MORE, and more VIOLENT storms?

    The entire laughable charade that ANY of this voodoo is based in reality is shocking to anyone with a background in instrumentation etc.

    Claims of “Wayul, WE ALL AGREE it’s WARMER” go hand in hand with “We all agree there’s a greenhouse gas effect. All our instruments must be broke.”

    Pfft.

  105. Rob Honeycutt says:
    October 25, 2011 at 11:49 am

    Willis… May I ask what baseline adjustments you used for your Fig 3?

    As noted below the graph, they are all baselined to their 1979-1984 average, This makes it easy to see the divergence.

    w.

  106. I’ve just taken a look at the data in the BEST data.txt file for my local site (leb2w – 136146). I am a bit disappointed at what I found. I was expecting both the raw data and their adjusted data. What I found was neither. The temperature data supplied appears to be seasonal normalized. That is that temperatures supplied for each month are not the actual monthly average temperature. What it appears to be is the annual average temperature plus the monthly anomaly from the average of that month throughout the data set. When comparing it with the raw data available from the USHCN, it has some strange hiccups added. The BEST monthly data differs from a simple arithmetic monthly normalization in a very regular manner:

    (in degrees Fahrenheit) January -2.9, February -3.3, March +1.5, April +2.8, May -1.2, June -1.4, July +0.8, August +1.4, September -1.4, October +0.3, November +2.5, and December +0.7.

    Those values are consistent across the entire leb2w data set plus or minus less than 0.5 degrees Fahrenheit.

    While that is interesting, I as surprised that this was the output from all their effort. I am wondering now if what this indicates is that after seasonal normalization, my local leb2w site does not need any adjustments. If so, why do you suppose USHCN shows quite significant adjustments for Time of Observation and homogenization? And why seasonal normalized? Oh well, I guess this is suppose to be the preliminary data.

  107. Question Willis,

    first I’m not sure that the measurement from satellites of the troposphere over land is directly comparable with the land surface temps. horizontal advection comes to mind.

    But lets say it is.

    what you show is a .3C difference between the temperature anomaly of the troposphere over land and the land surface measurement.

    So it would see to a first order that this makes sense. The UHI effect in the land record doesn’t
    exceed .3C.

    In fact, since we know SST pretty well in the modern era and we know that the land warms faster than the water.. we can also bound the UHI effect by looking at the difference between SST and the land.. again.. just a first order.. rough estimate of the magnitude of the effect.

    In fact .3C comes pretty close to what Ross argues..

    So, perhaps we can start by getting folks to agree to this.

    1. There was a LIA
    2. Global temperature makes “sense”, that is we say it was cooler in the LIA
    3. Its warmer now then it was then.
    4. UHI? a rough order guess is that it is less than .3C

    Any takers

  108. Willis, is there any reason you used a 5 year baseline rather than the standard 30 year baseline that all these datasets normally use (and that UAH just switched over to)?

  109. The quote of the week that bears repeating, from the thread on unadjusted data: (warning protect keyboard from airborne liquids)
    George Turner says:
    October 24, 2011 at 1:29 pm
    “If you follow some of the adjustments they make to the temperature record, we should worry less about the present getting warmer than the alarming rate at which the past keeps getting cooler. If present trends continue, millions of extra people in the 1940′s are going to freeze to death.”

  110. steven mosher,

    You were doing fine until #4:

    1. There was a LIA
    2. Global temperature makes “sense”, that is we say it was cooler in the LIA
    3. Its warmer now then it was then.
    4. UHI? a rough order guess is that it is less than .3C

    Since the planet has warmed up ≈0.7°C over the past century and a half, and since the LIA was considerably cooler by all accounts, and also according to ice core evidence from both hemispheres, what I suspect happened is that somehow a decimal point got inserted in the wrong place.

    Of course, that would make the LIA 3° colder than now, which may be a little bit too much. But it’s certainly closer to reality than 0.3°C, which looks like a Michael Mannian guesstimate.

  111. @Willis

    “In Figure 3, we find the opposite of what we expected. The land temperatures are rising faster than the atmospheric temperatures, contrary to theory.”

    WTF is up with “we find”? Do you have a mouse in your pocket?

    I expected no such thing. This is exactly what I’ve been harping about, dopey. GHG effect is primarily a land-based phenomenon. Got it? Write that down!

    Perhaps if you hadn’t petulantly dismissed me when I explained the physics to you about why and how the ocean rejects downwelling FIR you wouldn’t be surprised by this finding.

    Get a clue, Eschenbach. Buy one if you must.

    [COMMENT: Drop the attitude, it makes you look like a rabid beaver on crack. I disagreed with your claims. That's science, doesn't make you right. Also, take your never-ending obsession with how DLR can't heat the ocean elsewhere. This blog is for science, not science fiction. I'll snip it next time, along with any wingeing about my policy. There's lot's of places to discuss your fantasy about DLR, but here is not one of them. -w.

    PS—no, that's not a mouse in my pocket, I'm just glad to see you ...]

  112. Robert says:
    October 25, 2011 at 12:04 pm

    Willis,
    You should have looked to see whether your chart looks like BEST’s comparing the different records. It doesn’t.

    http://berkeleyearth.org/analysis.php

    This is supposed to be a surprise? You can’t see anything on their chart at all, it’s totally jumbled together. And yes … mine doesn’t look like that. Are we surprised?

    The issue with GISS is shown here:

    http://rankexploits.com/musings/2010/the-great-gistemp-mystery/

    I do think that a little critical thought would have told you that the GISS graph was wrong. We all know that Hadley is the outlier not GISS.

    Oh, can the attitude, for goodness sake. You are the jerk who proved above that you didn’t do your due diligence, you couldn’t tell GHCN from NOAA. You have no standing for your snark.

    In addition, you offer up the explanation of Reto Ruedy (of NASA GISS) for why GISS differs from GHCN/NOAA, from Lucia’s site, emphasis mine:

    Most of the differences arise from the diversity of spatial averaging techniques. The global average for CRUTEM3 is a land-area weighted sum (0.68 × NH + 0.32 × SH). For NCDC it is an area-weighted average of the grid-box anomalies where available worldwide. For GISS it is the average of the anomalies for the zones 90°N to 23.6°N, 23.6°N to 23.6°S and 23.6°S to 90°S with weightings 0.3, 0.4 and 0.3, respectively, proportional to their total areas. For Lugina et al. (2005) it is (NH + 0.866 × SH) / 1.866 because they excluded latitudes south of 60°S. As a result, the recent global trends are largest in CRUTEM3 and NCDC, which give more weight to the NH where recent trends have been greatest

    Seems clear. If you give more weight in the average to the northern hemisphere, you will show more warming, just as he says. I’m not clear why you’d want to do that, but yes, Robert, you can change the averaging method and get a different result … but you are arguing that that is the only correct result, when clearly it is only a result of the choice of averaging method.

    However, it gets worse. Ruedy’s claim is in total contradiction to another explanation for the exact same phenomenon, viz:

    Figure 4 shows time series of global temperature for the GISS and HadCRUT analyses, as well as for the GISS analysis masked to the HadCRUT data region. This figure reveals thatthe differences that have developed between the GISS and HadCRUT global temperatures during the past few decadesare due primarily to the extension of the GISS analysis into regions that are excluded from the HadCRUT analysis. The GISS and HadCRUT results are similar during this period, when the analyses are limited to exactly the same area.

    Two explanations for the same phenomenon. First one is from Reto Ruedy, of NASA/GISS, so it’s likely the right one, it’s likely the zonal averaging method that is the reason. Oh, except that the second explanation is from James Hansen of NASA/GISS, and he says the land mask is the reason … and you proudly announce that you know the real reason for the disparity, when even the GISS guys can’t agree on it? Hubris, anyone?

    So lets consider it this way: BEST, GISS and NOAA are all very similar when properly compared using land-only and Hadley is noticeably lower in recent years. Why? Well simply because CAM is too restrictive for many sites particularly in the Arctic (etc).

    Anyways the only disagreement is between Hadley and BEST and “supposedly” the satellites with BEST but if you look on the STAR analysis publication website you will see that their satellite record is coming, with more accurate satellite combining and what looks to be a significantly higher TLT trend when they actually do the product based on the relationship between TMT and TLT. I wouldn’t hold my breath that RSS and UAH are the end all product of the sat work.

    You may be right about the satellites. You may be right about GISS, and James Hansen may be wrong. You may be right about the STAR satellite analysis.

    But since we don’t know if you are right, for today, for this discussion, I have used the databases as they are. Not the latitude-band averaged version described (but not archived) by Ruedy. Not the land area masked version described (but not archived) by Hansen. Not the “STAR analysis” you are on about, which doesn’t even exist yet. I used the records that I had as they are.

    I used the existing ground-station based datasets. If you don’t like it, sorry, it’s what I have. I said if you sent me a citation to a land-masked version of the GISS dataset, I’d toss it in the mix. You have not yet done so.

    Finally, note that according to Hansen, when the GISS dataset uses the Hadley missing data mask, GISS agrees with Hadley. If that is true, then why are you claiming that Hadley the outlier? If I apply the Hadley mask to the GISS data and post it up there, GISS doesn’t move towards BEST and NCDC. It becomes more like Hadley … which means they’re both outliers. Or that the BEST/GHCN data are outliers. The jury is still out, my friend, despite your attempt to claim that the science is settled.

    And in either case, we still have about 0.7°C per century between either the high and low ground stations, or between the high ground stations and the satellites. That’s true even if you take GISS out of the equation entirely.

    w.

  113. Oh, I see now. #4 changed direction and was about UHI. Sorry, I got hung up on the LIA references. My bad [but actually my SWAG would be a higher UHI, based on personal experience and common sense].

    Too busy to search at the moment, but didn’t Anthony do an experiment with a datalogger showing several degrees warming driving from the country into the city?

  114. Oh, yeah, one more thing. At the top of the BEST dataset there’s a note that says:

    Estimated 1950-1980 absolute temperature: 7.11 +/- 0.50

    Seven degrees C? The GISS folks don’t even give an average, they just say it’s globally about 14°C.

    The HadCRUT data gives a global temperature about the same, 13.9°C, using a gridded absolute temperature dataset. Finally, the Kiehl/Trenberth global budget gives a black-body radiation value of 390 W/m2, which converts to 14.8°. So I figured that was kind of settled, that the earth’s average temperature (an elusive concept to be sure) was around fourteen or fifteen degrees C.

    Now, without a single word of comment that I can find, BEST says it’s only 7.1 degrees … say what? Anyone have an explanation for that?

    w.

  115. yes smokey your math does not make sense.

    1. you believe in a LIA
    2. according to best the last 50 or so years of the LIA were 1.5c colder than today

    3. You believe that some of this 1.5C is due to UHI.

    4. How much
    ############

    or look at willis shows. willis shows that the troposphere above the land is .3C warmer
    ( anomaly) than the land below it. And, the suggestion is that this difference perhaps is due to UHI
    That is, if there was no UHI the curves would match better.. So, if you believe Willis, you have an upper bound on the UHI bias.. .3C

    think carefully now..

    ####

    if SST warms by .5C over decades and we know that land warms faster than water.. would
    you expect the land to warm.. the same as SST? more than SST.. less than SST?

  116. steven mosher says:
    October 25, 2011 at 2:52 pm

    Question Willis,

    first I’m not sure that the measurement from satellites of the troposphere over land is directly comparable with the land surface temps. horizontal advection comes to mind.

    While that’s true, advection also affects the ground level measurements … when the wind off the Canadian Plains hits the US, ground surface temperature measurements plummet …

    But lets say it is.

    what you show is a .3C difference between the temperature anomaly of the troposphere over land and the land surface measurement.

    So it would see to a first order that this makes sense. The UHI effect in the land record doesn’t
    exceed .3C.

    In fact, since we know SST pretty well in the modern era and we know that the land warms faster than the water.. we can also bound the UHI effect by looking at the difference between SST and the land.. again.. just a first order.. rough estimate of the magnitude of the effect.

    In fact .3C comes pretty close to what Ross argues..

    That’s certainly valid as a first order cut.

    So, perhaps we can start by getting folks to agree to this.
    1. There was a LIA
    2. Global temperature makes “sense”, that is we say it was cooler in the LIA
    3. Its warmer now then it was then.
    4. UHI? a rough order guess is that it is less than .3C

    Any takers

    I would agree with those four statements. I’m still curious why BEST finds a global average temperature of 7°·C, though.

    w.

  117. Rob Honeycutt says:
    October 25, 2011 at 2:59 pm

    Willis, is there any reason you used a 5 year baseline rather than the standard 30 year baseline that all these datasets normally use (and that UAH just switched over to)?

    Yes, it makes it easy to see how far the records have diverged over that time. You can mash them all together as you suggest, but that hides the decline, metaphorically …

    w.

  118. @Willis

    “In Figure 3, we find the opposite of what we expected. The land temperatures are rising faster than the atmospheric temperatures, contrary to theory.”

    Actually you screwed up that graph in Figure 3. The satellite temperature track is global, land + sea. BEST & GHCN are land-only. GISS & CRUTEM are land-ocean but stitch in satellite data for ocean where they can get it and use whatever data they can find or manufacture for ocean surface temp in pre-satellite period.

    The caption and text indicate you believe those are all land-only records.

    What it shows is that surface temperature is rising a lot more over land than it is over water.

  119. “Too busy to search at the moment, but didn’t Anthony do an experiment with a datalogger showing several degrees warming driving from the country into the city?”

    Yes smokey, but thats ONE CITY.. when you average all cities and rural together…
    you get a curve, like the BEST curve.

    Willis shows the temperature at the troposphere where there is no UHI.
    That anomaly is at MOST .3C lower than the average of all the sites, both good and bad.

    So, since the land from BEST is at MOST .3C higher ( anomaly) versus the troposphere..
    right there you have a boundary for the maximum bias that UHI could have in the record.

    Now, one city could be 1C.. another could be 0C..

    one DAY could be 8C.. bt you dont get UHI every day. not when it rains or when the wind blows, or when its cloudy.. we are talking about the average bias.. BEST says its 1.5C warmer now than in the LIA.. and you think there is UHI bias in that 1.5C number.. how much? willis chart hints that the UPPER boundary is .3C bias.

  120. Willis Eschenbach says:
    October 25, 2011 at 9:17 am
    David says:
    October 25, 2011 at 4:47 am

    I also would love to see an oceans only graph layered into the five data sets chart to see which data set follows the ocean air temp chart the most accurately.

    The Berkeley dataset doesn’t cover the oceans, just the land.

    w.

    Thanks Willis, and yes I know, but it would still give a comparison and perhaps some insight into the proper UHI adjustment, and perhaps some insight into the unexplained increasing divergence here; David says: October 25, 2011 at 4:02 am, which no one else has commented on.

  121. From Willis Eschenbach on October 25, 2011 at 3:32 pm:

    Oh, yeah, one more thing. At the top of the BEST dataset there’s a note that says:

    Estimated 1950-1980 absolute temperature: 7.11 +/- 0.50

    (…)

    I noticed that here. BEST is giving the land figure, their baseline for the anomalies. NCDC here says they use 8.5°C for their land baseline, 1901-2000 period. For the period the annual databases overlap (1880 to 2009 inclusive) the average absolute difference is 1.339 lower for BEST, NCDC is always higher.

    Not much of an absolute difference, as long as you’re not worried about permafrost thawing or ice melting if the temp goes up even just another degree or two. If you are, BEST has yielded more breathing room before the “catastrophic” of CAGW kicks in. Surprising that doesn’t receive more press, no?

  122. Thanks Willis. I would trust that smokey and others will see the implications of your chart.
    UHI is bounded from above. we know that its not zero and your chart suggests .3C as an upper bound.

    Next I direct people to look at BEST error bars.. 2 sigma is .19C

    Then do some thinking

    Next. Look at SST.. The land is.. what? maybe .2C warmer.. Does that help you bound the
    BIAS..

    remember. if we had 1000000 rural stations and only 1 urban with a huge 12C bias.. that one
    cities effect would be smothered. When we look at all stations good and bad, rural and not..
    the effect, the overall bias, is somewhere between 0 and .3C, lower if we consider SST and how close it is to the land.

    Then look at the 2 sigma width..

    and think about “power” in a statistical sense

  123. steven “one trick pony” mosher says:
    October 25, 2011 at 3:43 pm

    “if SST warms by .5C over decades and we know that land warms faster than water.. would
    you expect the land to warm.. the same as SST? more than SST.. less than SST?”

    Land warms faster and also cools faster so average temperature no different. The big difference is that the ocean has an albedo close to zero and land has an albedo of about 15% so the SST should go up more because it absorbs more energy. In point of fact land surface temp is warming faster than ocean surface temp and the numbers do not add up indicating that someone’s got some mistakes in their physics. Unable to admit that but able to calculate what the ocean temperature should hypothetically be they’re scrambling around looking for the rise in temperature below the thermocline. They’re not finding it there either for the simple reason that GHGs have little effect over the ocean. That’s because GHGs operate by slowing down radiative cooling and while land surfaces cool primarily by radiation the ocean cools primarily by evaporation and GHG’s don’t do jack diddly squat to slow down evaporate cooling. Got it? Write the down.

  124. Steve Mosher states, “So, since the land from BEST is at MOST .3C higher ( anomaly) versus the troposphere..right there you have a boundary for the maximum bias that UHI could have in the record.”

    Your logic is logical, except I see close to .4 divergence in the chart Willis provided.

    Willis, the previous post was made before I saw the discussion on the diverging data sets. I see the reasons are somewhat contradictory and do not really explain clearly why it is increasing through 2007.

  125. Dave Springer says:
    October 25, 2011 at 3:47 pm
    @Willis

    “In Figure 3, we find the opposite of what we expected. The land temperatures are rising faster than the atmospheric temperatures, contrary to theory.”

    Actually you screwed up that graph in Figure 3. The satellite temperature track is global, land + sea. BEST & GHCN are land-only. GISS & CRUTEM are land-ocean but stitch in satellite data for ocean where they can get it and use whatever data they can find or manufacture for ocean surface temp in pre-satellite period.

    The caption and text indicate you believe those are all land-only records.

    What it shows is that surface temperature is rising a lot more over land than it is over water.

    Thanks, Dave. Citations to both your claims and to the land-only you believe were used would be greatly appreciated. In the meantime, I find this:

    Doesn’t look like a lot ocean in CRUTEM, certainly not enough to affect a global average much. Let me see what the CRUTEM site says:

    CRUTEM3 land air temperature anomalies on a 5° by 5° grid-box basis

    SOURCE

    I also find here:

    … Also previous versions of the dataset did some infilling of missing grid-box values using data from surrounding grid boxes [Jones et al., 2001]. This is no longer done, allowing the attribution of an uncertainty to each grid-box value. The resulting gridded land-only dataset has been given the name CRUTEM3.

    I find nothing about satellite. The grid-boxes containing islands are used, but they are given the values from the “land air temperature anomalies”.

    GISS, as I’ve been discussing with someone else, extends out land temps into the ocean, a crazy procedure in my book. But if you remove that, according to both Ruedy and Hansen, it moves it closer to CRUTEM. In any case, the dataset I’m using is identified as:

    Means Based on Land-Surface Air Temperature Anomalies Only

    SOURCE: GISS
    The word “only” in there should give you a clue that your claims about GISS using satellite data are simply not true.

    SUMMARY: No indication that they “stitch in satellite data” in either one. No indication that they “use whatever data they can find or manufacture for ocean surface temp in pre-satellite period.” Neither one uses either satellite data or ocean data in any form.

    You seem to be confusing HadCRUT for CRUTEM, and mistaking the GISS LOTI (land-ocean temperature index) dataset for the GISS land-only dataset that I actually used.

    Thanks for playing, though, and next time, save the snark. In Spanish there’s a lovely line from a traditional song. It goes, “Dí les que no batan al aqua, que al cabo lo han de beber”. Loosely translated, that means “Tell them not to muddy the water … they might end up having to drink it.”

    Regards,

    w.

  126. kadaka (KD Knoebel) says:
    October 25, 2011 at 4:06 pm

    From Willis Eschenbach on October 25, 2011 at 3:32 pm:

    Oh, yeah, one more thing. At the top of the BEST dataset there’s a note that says:

    Estimated 1950-1980 absolute temperature: 7.11 +/- 0.50

    (…)

    I noticed that here. BEST is giving the land figure, their baseline for the anomalies. NCDC here says they use 8.5°C for their land baseline, 1901-2000 period. For the period the annual databases overlap (1880 to 2009 inclusive) the average absolute difference is 1.339 lower for BEST, NCDC is always higher.

    Not much of an absolute difference, as long as you’re not worried about permafrost thawing or ice melting if the temp goes up even just another degree or two. If you are, BEST has yielded more breathing room before the “catastrophic” of CAGW kicks in. Surprising that doesn’t receive more press, no?

    Thanks, KD. I know that the BEST figure is just the land. But if the globe is at say 14° to make it easy, and the land is at 7°, that means that on average the ocean is at 17°.

    And I’m just not buying that on a global average the ocean is ten degrees C, or 18 degrees F, warmer than the land. It sets off my bad number detector.

    I need a land mask. Someone suggested the HADISST, which has N/A values where there’s land. I need to think some about this.

    w.

  127. From Willis Eschenbach on October 25, 2011 at 5:15 pm:

    Thanks, KD. I know that the BEST figure is just the land. (…)

    Well I’m not just writing for you and me. ;-)

    (…) But if the globe is at say 14° to make it easy, and the land is at 7°, that means that on average the ocean is at 17°.

    NCDC says 8.5°C land, sea surface 16.1°, combined 13.9° for baseline.

    I find that believable. The sea retains the heat gained from the sun when the sun goes away, the land retains little heat and cools quickly (cloud heat retention effect at night being ignored) which leads to plummeting night temps. Using the commonly-accepted 70% sea figure, the combined NCDC figure with simple math is 13.8, close enough.

    A mere 7.6°C land to sea difference, roughly corresponding to twice that as a day/night temperature swing on land of 15.2°C (27.4°F), daily max to min, doesn’t appear that bad. Arid tropical and extra-tropical areas see far more, islands surrounded by moderating sea and the polar regions will see far less but they make up a smaller bit of the total area. Here in Pennsylvania I expect 10 to 20°F swings, at the same latitude in the Midwest they can see far more.

    Hard number crunching may reveal that difference as unrealistic, but for now at a glance I can accept it.

  128. kadaka (KD Knoebel) says:
    October 25, 2011 at 6:38 pm

    … NCDC says 8.5°C land, sea surface 16.1°, combined 13.9° for baseline.

    I find that believable. The sea retains the heat gained from the sun when the sun goes away, the land retains little heat and cools quickly (cloud heat retention effect at night being ignored) which leads to plummeting night temps. Using the commonly-accepted 70% sea figure, the combined NCDC figure with simple math is 13.8, close enough.

    A mere 7.6°C land to sea difference, roughly corresponding to twice that as a day/night temperature swing on land of 15.2°C (27.4°F), daily max to min, doesn’t appear that bad. Arid tropical and extra-tropical areas see far more, islands surrounded by moderating sea and the polar regions will see far less but they make up a smaller bit of the total area. Here in Pennsylvania I expect 10 to 20°F swings, at the same latitude in the Midwest they can see far more.

    Hard number crunching may reveal that difference as unrealistic, but for now at a glance I can accept it.

    Appreciated, KD. Here’s my problem. I’ve gone swimming in the sea in a lot of places around the planet, both at dawn and at dusk. At that time, the air temperature will be somewhere around average. But the sea temperature is never 18°F (10°C) above that.

    That means the difference must be due to the cooler elevated land in the interior. Hmm. Could be, 10°C is about a kilometer in elevation … whoa, cool, here’s a scientific paper about that. Or wait, there a better way … OK, the median elevation of the stations in the BEST database is just over 200 metres. So the station elevation only explains about 2 degrees of the difference … where’s the other 8°??

    Still unclear to me, I need funding for a major inquiry here …

    w.

  129. Willis, why use a Gaussian mean. Makes no sense to me. I would prefer an exponential mean where the previous data affects the current readings.

  130. Willis, you (and others) use plots with ranges that are all different. It would make sense to use the same upper and lower bounds on plots so they can be compared visually. I suggest +- 2 degrees typically for anomalies. Also the graphs should be centered on zero. I know the software does it, but you shouldn’t.

    Keep up the good work. I, for one, read all the stuff you post.

  131. David.

    “Your logic is logical, except I see close to .4 divergence in the chart Willis provided.”

    That’s fine. Any number will do if you are willing to follow along and be logical.

    So, here is what you have. You believe you have evidence that the 1.5C increase from the LIA
    has UHI bias. and you believe its on the order of .4C

    Which means that we are actually closer to LIA temps than we think. I don’t know what effect you think the Sun has on the climate, but your argument effectively diminishes it. However, Lets leave that aside.

    You have evidence that .4C of the warming in the land record is due to UHI bias. Lets use that as your starting premise and do some math and more logic. ok? Lets’ ignore that this would make the
    land cooler than SST, you could always adopt a different argument to handle that issue. Again,
    Lets accept your .4C premise.

    Now, BEST categorizes stations into rural and non rural. 16K rural and 23K not rural. do you think that percentage of rural is high? or is it low? Lets suppose you thought there were NO rural stations. none at all. what does .4C now represent? It represents the total UHI effect. Let me know if you get that. And lets swing it the other way, suppose you thought ALL the stations or lets say
    99% are Rural.. What’s that mean? That means a few urban stations have Huge UHI.
    so, understanding that.. what fraction of stations do you think are actually rural… remember if you pick a low number… then the UHI bias after averaging urban with rural approaches the entire
    UHI effect.. and if you pick a high number of rural, then you are arguing that a few urban stations do all the biasing.

    Lets say that BEST argues that 33% of the sites are rural.. is that low? or high? or just about right?

  132. Springer.

    I think I’ll pass on writing down anything you say. especially the part about GHGs over the ocean.
    that was funny.

  133. Dear Mr Willis Eschenbach

    This is just to say Thank You !
    You see, for people like myself, being able to understand al the statistic measurements in the reviews of BEST statement, is really difficult. But you make a hard job easy. What you say, even a “brutita” like me can read through, and understand.

    “Gracias de nuevo, de su rendida admiradora española ”
    María Maestre

  134. Someone up above asked why BEST is rushing this to the media before it’s been reviewed…there’s an answer.

    Someone else asked why they’re ignoring the (very real, you can see it yourself this winter) impact of Urban Heat Islands. There is an answer there, too.

    The answer is, they’re not doing science, they’re doing POLITICS, and they’re counting on having their results measured with a thumb on the scales marked “good intentions”, because, as we all OUGHT to know, polluting is bad, so is inefficient use of power and resources. The whole Global Warming scare is really about scaring people into doing what the experts think they OUGHT to do, whether it’s Kyoto (giving the 3rd world a leg up by ‘sharing the wealth’), or funding otherwise economically nonviable work (Solyndra), the whole thing is like the preacher telling the people they need to be nicer to their neighbours and give a little to charity because god-is-coming-and-he-is-pissed.

    In a way, a lot of the ‘solutions’ resemble the old Church’s sales of ‘indulgences’, there’s a reason for that-in the modern world, a PhD has replaced the Clerical Collar-so few people know, or understand even the actual SCIENTIFIC METHOD, that they will simply roll over on the word of an “expert’ with a doctorate.

    ‘taint science, ’tis Theology and Politics.

  135. Dave Springer says:
    October 25, 2011 at 4:24 pm

    The big difference is that the ocean has an albedo close to zero and land has an albedo of about 15% so the SST should go up more because it absorbs more energy.

    Um, specific heat? Currents? Evaporation? Energy temperature.

  136. From steven mosher on October 25, 2011 at 8:18 pm:

    (…)
    You have evidence that .4C of the warming in the land record is due to UHI bias. Lets use that as your starting premise and do some math and more logic. ok? Lets’ ignore that this would make the
    land cooler than SST, you could always adopt a different argument to handle that issue. (…)

    But the land is cooler than SST, see the NCDC baselines, thus that’s not an issue.

    The rest of your post reads like “Let’s assume the sky went green, then you’d think too many things looked like plants, and then if the sky went dark red you’d think too many buildings were made of brick.” Someone’s looking for which walnut shell the pea is hiding under, you ask if it’d make a difference if they were pecan shells, you even question if the person is certain they’re looking at walnut shells as they might be pecan shells. Anything possible to keep them from finding the pea…

  137. Combined graph showing all five datasets:

    http://www.woodfortrees.org/plot/best/mean:120/plot/gistemp/mean:120/plot/hadcrut3vgl/mean:120/plot/uah/mean:120/plot/rss/mean:120

    Note these are without baseline offset corrections – I haven’t done the calculation to work out the shift yet, but it’s clear visually that BEST has a lower baseline.

    Here are the 30 year trends for all five as well… BEST is quite a lot higher (~ 2.7K/cent) than the other four (all around 1.6-1.7K/cent) – I’m sure that will be an interesting item for discussion!

    http://www.woodfortrees.org/plot/best/last:360/mean:12/plot/gistemp/last:360/mean:12/plot/hadcrut3vgl/last:360/mean:12/plot/uah/last:360/mean:12/plot/rss/last:360/mean:12/plot/best/last:360/trend/plot/gistemp/last:360/trend/plot/hadcrut3vgl/last:360/trend/plot/uah/last:360/trend/plot/rss/last:360/trend

    Enjoy!

    Paul

  138. kramer says:
    October 24, 2011 at 5:01 pm

    “I emailed the BEST team a while ago asking if they could just plot the rural, unadjusted data. I got an email a few days ago saying it’s done.
    My question is, if the rural data unadjusted data agrees with the adjusted and unadjusted data, why bother to adjust the data at all?”

    There is the RUTI project that works only on rural data

    http://hidethedecline.eu/pages/posts/ruti-global-land-temperatures-1880-2010-part-1-244.php

  139. What do I have to do to get all on this Blog not to mention the BEST mob to grasp that one should not compare the apples (do best in cooler climes) of the 1800-2010 data set with the oranges (do best in warmer climes) of the 1950-2010 data that BEST seamlessly merges together, oblivious of the absence of the orange growing areas from ALL of BEST, CRU, GISS, NCDC et al before 1950.
    Evidently not even Willis can see it is wrong to compare apples with oranges. I give up!

  140. Now, BEST categorizes stations into rural and non rural. 16K rural and 23K not rural. do you think that percentage of rural is high? or is it low? Lets suppose you thought there were NO rural stations. none at all. what does .4C now represent?

    So there are 39K stations in the BEST data…
    So are there 39K stations contributing to the data for 1800?
    So have these 39K stations stayed constant for over 150 years?

    what does .4C now represent?
    A number that triggers my BS detector…

    do you think that percentage of rural is high?
    Who knows…
    Lets see some station analysis…
    Lets see if we have the great culling of stations…
    Lets see if we have the move to airports and the beach…
    Lets see if we have the descent from the mountains…
    Lets see if we have the retreat from high latitudes…
    Lets see how the rural mix changes with time…

    Until such time I am assuming BEST is an anagram of ET and BS.

  141. Brian D says:
    October 24, 2011 at 6:17 pm

    And this is how it is being reported in NZ:

    http://www.scoop.co.nz/stories/SC1110/S00058/experts-respond-analysis-confirms-global-warming-data.htm

    Interesting to see the potential reviewers comments in advance. And whom they choose to ask for a view.
    ____________________________________________________
    So now we know Watts Up With That.

    The “Skeptics” Muller and Anthony Watts, have now all agreed that there is no problem/contribution with the station quality and the Urban Heat Island Effect. Also the skeptics/deniers all now agree there was warming during industrialization during the last century. Now we can head to Durban and get on with applying a stranglehold to the economies of the industrialized countries and confiscating the land of the third world natives.

    And if anyone like Senator Inhofe objects that there has been no warming in the last decade there is always Trenberth’s missing heat hiding at the ocean bottom.

    As a propaganda campaign the BEST paper without review goes hand in glove with The National Oceanographic Data Center (NODC) recently posted a new Ocean Heat Content (OHC) anomaly dataset on its website.. (Again without peer reviewed papers)

    That is all this ever was, a propaganda campaign. The absolutely brilliant move of the BEST team was to rope Anthony Watts into agreeing to participate AND agree before hand to the results!!!! Having Judith Curry on the “Team” did not hurt either.

    Now the team can go to Durban and say with a straight face that Anthony Watts, the leader of the “Deniers” agrees with their study so “Consensus” has been achieved for the big go ahead.

    WE HAVE BEEN HAD!

  142. Based on mean of the 1979-1999 baseline that RSS uses, here’s my best attempt at aligning baselines:

    http://www.woodfortrees.org/plot/best/last:360/mean:12/offset:-0.42/plot/gistemp/last:360/mean:12/offset:-0.23/plot/hadcrut3vgl/last:360/mean:12/offset:-0.15/plot/uah/last:360/mean:12/offset:0.1/plot/rss/last:360/mean:12/plot/best/last:360/trend/offset:-0.42/plot/gistemp/last:360/trend/offset:-0.23/plot/hadcrut3vgl/last:360/trend/offset:-0.15/plot/uah/last:360/trend/offset:0.1/plot/rss/last:360/trend

    Something is radically different about BEST to the other 4 datasets. This is based on the data they published to create their analysis charts at: http://www.berkeleyearth.org/analysis.php. I’d be very grateful if people could check my logic here!

    Paul

  143. Willis Eschenbach says:
    October 24, 2011 at 6:31 pm

    Excellent post, Willis. It is getting some play around the blogosphere. Keep up the good work.

  144. Alan Clark of Dirty Oil-berta says:
    October 24, 2011 at 6:52 pm

    oMan says:
    October 24, 2011 at 4:53 pm
    “What was the magic of their being able to issue press releases now?”

    Literally, the $64 million question?
    ______________________________________

    I think it is more like $2,000 billion dollar question.

    “The carbon economy is the fastest growing industry globally with US$84 billion of carbon trading conducted in 2007, doubling to $116 billion in 2008, and expected to reach over $200 billion by 2012 and over $2,000 billion by 2020″ – World Bank Carbon Finance Report for 2007 http://www.carbonplanet.com/navigating_the_carbon_economy

    I agree with Willis, this a direct funnel of wealth from the poor into the pockets of the incredibly wealthy using crocodile tears from the likes of the United Nations, WWF and Greenpeace, and cries of its for the children. GRRRrrrrrr

    I am not as nice as Willis. I hope the “Scientists” who sacrificed their scientific objectivity and honor on the altar of fame and fortune are still alive to face trials of crimes against humanity. Unfortunately I doubt that will happen. They have too much power and money backing them.

    NOTE: 85% of todays starvation deaths occur in children 5 years of age or younger. There are over 30,000 deaths by starvation everyday. What is Al Gore and the World Bank doing? CONFISCATING THEIR LAND! (only 10% of Africans have actual deeds to the property their families own.)

    http://wattsupwiththat.com/2011/09/25/they-had-to-burn-the-village-to-save-it-from-global-warming/

    http://wattsupwiththat.com/2011/10/13/borlaug-2-0/#comment-767559

  145. Something is radically different about BEST

    Correct…. it is about a change in tactics…
    We have moved away from a simple hide the decline
    And evolved to a more subtle explain away the recent decline phase:

    http://www.woodfortrees.org/plot/best/last:240/mean:12/plot/gistemp/last:240/mean:12

    Notice the upward ratcheting temperature spikes since 1990…

    Notice that is each spike is followed by a decline….

    Notice how the following spikes are always worst than we thought

    Notice how we are currently in a decline….

    So the next spike is going to be even worst than we thought

    QUEL SUPRISE!

  146. Louis says:
    October 24, 2011 at 9:45 pm

    The BEST press release makes the following claim about UHI:

    “The urban heat island effect is locally large and real, but does not contribute significantly to the average land temperature rise. That’s because the urban regions of the Earth amount to less than 1% of the land area.”
    _________________________________________
    This is the logical fallacy of Equivocation

    They say 1% of the land mass is cities – true

    HOWEVER they do not say how many climate stations are not in completely rural, no possible urban heat island effect areas. That is the I gottcha!

    As anyone who has followed WUWT for any length of time knows an actual rural station not sited next to a building/barbeque/Ac unit/road/airport/town/city…. is few and far between.

    It would be interesting to map the dropped thermometers to this satellite map of urban lights http://earthobservatory.nasa.gov/Features/Lights/

    The NASA blurb accompanying it is very amusing given the BEST pronouncement above.
    Suburban sprawl….
    “…Watching the familiar, rural landscapes of our youth give way to suburban sameness has become as much a part of modern American life as portable electronics, instant food, and wasted time in front of the television. Nearly all of us have had the disappointing experience of returning to what used to be the woods near our childhood homes and finding a new subdivision. Or we have been shocked to see that some corporate entity has erected aluminum-sided duplexes and an outlet mall in the middle of our favorite vacation spot.

    Like it or not, throughout this century, the United States has undergone a steady process of urbanization as a larger and larger percentage of the population has moved towards the cities. While increasing urbanization may have some positive impacts on our environment, such as the lower birth rates that come with a city lifestyle, scientists are becoming more concerned about the negative long-term effects. Unlike rural communities, urban sprawl completely transforms the landscape and the soil and alters the surrounding ecosystem and the climate…”

    Here are John Daly’s
    “…set of historical temperature graphs from a large selection of mostly non-urban weather stations in both hemispheres. This data originated with the NASA Goddard Institute (GISS) in the USA and the Climatic Research Unit (CRU) of the University of East Anglia, Norwich, England. (The graphs have been generated from that data using the Microsoft Works spreadsheet module). With a few exceptions, large cities have been excluded because of Urban Heat Island Effect distortions to long-term data. Stations with data up to 2000 or beyond are indicated in red (e.g. `Data to 2001′)….” http://www.john-daly.com/stations/stations.htm

  147. Tim Curtin says:
    October 24, 2011 at 10:31 pm

    . Interestingly the BEST data show only a very small acceleration in the GMT trend from 1991 to 2000, and an actual deceleration from 2001 to 2009, which belies their claim “the world is warming fast”, which should have read “the world is warming more slowly” (according to BEST) – but then they don’t do calculus at Berkeley anymore do they?
    _______________________________________________-

    Oh my gosh, now I have to clean the tea off my monitor again. ROTFLMAO.

    They certainly haven’t learned geometry very well either. All they seem to have in their “Tool Box of Tricks” is an infinite straight line.

    If I recall correctly from my long ago school days, in general nature hates straight lines. Archaeologists find this useful in finding man made artifacts.

    This straight line crap is another one of the great CAGW fallacies. Nature prefers curves and cycles.

  148. michael hammer says:
    October 24, 2011 at 11:11 pm

    Something I dont quite understand. In the early 1970′s the National Academy of Science published a climate reconstruction showing that temperatures fell by 0.7C ( about 1.3F) between 1940 and 1970. This was the basis for many articles in both science and environmental journals suggesting we were heading for dangerous global cooling (anthropogenic of course). The modern reconstructions now show no cooling over this period. Did the historical data change with time and if so, how does long documented historical data change with time?…..
    ________________________
    Check out the graphs

    (NOAA adjustment chart) http://cdiac.ornl.gov/epubs/ndp/ushcn/ts.ushcn_anom25_diffs_pg.gif

    Discussions:

    http://wattsupwiththat.com/2011/01/16/the-past-is-not-what-it-used-to-be-gw-tiger-tale/

    http://wattsupwiththat.com/2011/02/15/controversial-nasa-temperature-graphic-morphs-into-garbled-mess/

  149. David says:
    October 25, 2011 at 4:47 am

    I also would love to see an oceans only graph layered into the five data sets chart to see which data set follows the ocean air temp chart the most accurately.
    ______________________
    You might like to take a look at Frank Lancer’s work at Joanne Nova’s site. He does the ocean land temp analysis and gets something interesting.

    http://joannenova.com.au/2011/10/messages-from-the-global-raw-rural-data-warnings-gotchas-and-tree-ring-divergence-explained/#comment-625436

  150. #
    #
    Chris Hanson says:
    October 25, 2011 at 9:16 am

    Willis, When considering Muller’s false persona it worth a review of “Operation Trust” used by the Soviets in the early days;

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

    Fake and straw moderates are nothing new.
    _________________________________

    It is a lot older than that. Remember the Trojan Horse?

    Muller has been a very effective Trojan Horse. Judith Curry too????

  151. steven mosher says:
    October 25, 2011 at 4:24 pm

    “remember. if we had 1000000 rural stations and only 1 urban with a huge 12C bias.. that one
    cities effect would be smothered. When we look at all stations good and bad, rural and not..
    the effect, the overall bias, is somewhere between 0 and .3C, lower if we consider SST and how close it is to the land.

    Then look at the 2 sigma width..

    and think about “power” in a statistical sense”

    Two comments. The first is that you are great at imagining fantastic scenarios which you can use to defend the fact that you are absolutely unwilling to discuss the facts on the ground, such as the quality of weather stations.

    The second comment could change your professional life. The second lesson that a good analyst learns is “Never make inferences from the characteristics of your system of representation to the characteristics of the world (what your system represents).

    Your thought “think about “power” in a statistical sense” is a clear recommendation that we should make inferences from our characteristics of our system of representation to the world.

    For example, before Riemann everyone thought geometry was intuitively clear and restricted to Euclid’s three dimensions; after Riemann, geometry became a branch of abstract algebra. Riemann put an end to a whole bunch of inferences from the characteristics of Euclidean geometry to characteristics of the world.

    At this time, Warmista are frozen in a statistical box of their own making that will not allow even to consider discussing empirical matters, except as those empirical matters are embodied in the box “already.”. There is no investigation outside the box.

  152. viejecita says:
    October 26, 2011 at 12:47 am

    Dear Mr Willis Eschenbach

    This is just to say Thank You !
    You see, for people like myself, being able to understand al the statistic measurements in the reviews of BEST statement, is really difficult. But you make a hard job easy. What you say, even a “brutita” like me can read through, and understand.

    “Gracias de nuevo, de su rendida admiradora española ”
    María Maestre

    Ay, mí favorita, Maria la jovencita … mil gracias pa’ ti tambien, y sus palabras de miel …

    Your kind words are much appreciated.

    w.

  153. Tim Curtin says:
    October 26, 2011 at 5:17 am

    What do I have to do to get all on this Blog not to mention the BEST mob to grasp that one should not compare the apples (do best in cooler climes) of the 1800-2010 data set with the oranges (do best in warmer climes) of the 1950-2010 data that BEST seamlessly merges together, oblivious of the absence of the orange growing areas from ALL of BEST, CRU, GISS, NCDC et al before 1950.
    Evidently not even Willis can see it is wrong to compare apples with oranges. I give up!

    Tim, that was totally incomprehensible. If you want us to see something, you have to be much clearer than that. My advice would be to take a deep breath, figure out exactly what you are trying to say, leave out the apples and oranges and anything extraneous, and start over.

    Or not …

    w.

    • Willis: I was referring to the complete absence of instrumental temperatures in the Tropics and sub-Tropics from the BEST data before 1910, and incomplete until 1940-1950, which must bias the trend in their graph. It is a similar issue with respect to UHI – any series of GMT based only on urban data since 1800 is bound to show a stronger upward trend than is warranted.

      I am glad that at least one here (Gail) has noticed my point about the absolute decline in the rate of change of the BEST anomalies in 2001-09, which gives the lie to the Muller inference that not only is the globe warming it is doing so more rapidly, as stated by The Economist in its report of BEST. Here is my letter submitted to The Economist:

      Your article “The heat is on” (October 22 nd) provides a mostly well-balanced account of the Berkeley Earth Surface Temperature (BEST) group’s review of global temperature sets. However, it does not fully address the difference between levels of globally averaged temperature and trends therein. For example, the global temperature levels shown in your diagram purport to show the global levels from 1800 to 1910 when the instrumental coverage of temperatures in the tropics was exiguous, thereby imparting a spurious upward trend over the period to 1950 as the tropics came on board, prior to much increase in the atmospheric concentration of carbon dioxide. Interestingly the BEST data show only a very small acceleration in the trend from 1991 to 2000, and an actual deceleration from 2001 to 2009, which belies your article’s final sentence “the world is warming fast”, which should have read “the world is warming more slowly” (according to BEST).

  154. kramer says:

    “…..I don’t think they are going to sentence the poor to more expensive energy. What they want to do is redistribute some of the higher energy taxes to the poor to help pay for the higher energy costs as well as help their collective net worth move closer to the rich (as the collective net worth of the rich decreases).

    They also want to do this on a global level so that at some point in the future, all nations have roughly the same per-capita wealth and standard of living.

    What I see are technocrats using science to achieve socialistic goals.”
    ______________________________________________________

    That cock and bull about socialism got smashed by reality I am afraid. “Socialism” is just the mask these greedy power hungry wolves hid behind. Do not forget that CAGW is backed by the likes of the World Bank.

    The so-called Danish text, a secret draft agreement….hands effective control of climate change finance to the World Bank…

    I suggest you read up on what the World Bank and IMF actually does to the poor
    “The World Bank’s own figures indicate that the IMF extracted a net US$1 billion from Africa in 1997 and 1998 more than they loaned to the continent. http://www.whirledbank.org/development/debt.html

    “Structural Adjustment Policies are economic policies which countries must follow in order to qualify for new World Bank and International Monetary Fund (IMF) loans… SAPs often result in deep cuts in programmes like education, health and social care, and the removal of subsidies designed to control the price of basics such as food and milk….the immediate effect of a SAP is generally to hike prices up three or four times, increasing poverty to such an extent that riots are a frequent result.” http://www.whirledbank.org/development/sap.html

    “…Davison Budhoo, a senior economist with the International Monetary Fund (IMF) for more than 12 years, publicly resigned in May, 1988…. To me, resignation is a priceless liberation, for with it I have taken the first big step to that place where I may hope to wash my hands of what in my mind’s eye is the blood of millions of poor and starving peoples. Mr. Camdessus, the blood is so much, you know, it runs in rivers….” http://www.thirdworldtraveler.com/IMF_WB/Budhoo_IMF.html Also: http://www.thirdworldtraveler.com/IMF_WB/Budhoo_50YIE.html

    Confessions of an Economic Hit Man… Interview: http://www.democracynow.org/2004/11/9/confessions_of_an_economic_hit_man

    After that background go and read the newest attrocities by Al Gore and the World Bank. This move to confiscate land in Africa will condemn more and more children to death by starvation .

    http://wattsupwiththat.com/2011/09/25/they-had-to-burn-the-village-to-save-it-from-global-warming/

    http://wattsupwiththat.com/2011/10/13/borlaug-2-0/#comment-767559

    Global Land Grab: http://www.inthesetimes.com/article/11784/global_land_grab/

    “Every day, almost 16,000 children die from hunger-related causes. That’s one child every five seconds. There were 1.4 billion people in extreme poverty in 2005. The World Bank estimates that the spike in global food prices in 2008, followed by the global economic recession in 2009 and 2010 has pushed between 100-150 million people into poverty.” http://www.bread.org/hunger/global/

    The spike in global food prices in 2008 was a coldly calculated move not chance. See: http://wattsupwiththat.com/2011/10/13/borlaug-2-0/#comment-767575

    You can not separate Muller’s “timely” release from the current global politics of the World Bank, financiers and the multibillion dollar Carbon trading scam. A scam that will sentence millions of people to death by hypothermia or starvation.

  155. woodfortrees (Paul Clark) says:
    October 26, 2011 at 7:18 am

    Based on mean of the 1979-1999 baseline that RSS uses, here’s my best attempt at aligning baselines:

    http://www.woodfortrees.org/plot/best/last:360/mean:12/offset:-0.42/plot/gistemp/last:360/mean:12/offset:-0.23/plot/hadcrut3vgl/last:360/mean:12/offset:-0.15/plot/uah/last:360/mean:12/offset:0.1/plot/rss/last:360/mean:12/plot/best/last:360/trend/offset:-0.42/plot/gistemp/last:360/trend/offset:-0.23/plot/hadcrut3vgl/last:360/trend/offset:-0.15/plot/uah/last:360/trend/offset:0.1/plot/rss/last:360/trend

    Something is radically different about BEST to the other 4 datasets. This is based on the data they published to create their analysis charts at: http://www.berkeleyearth.org/analysis.php. I’d be very grateful if people could check my logic here!

    Paul

    Hey, Paul, good to hear from you. Thanks for the woodfortrees site.

    The problem you are having is that you are comparing best, which is land only, with gistemp (actually I think that one is GISS LOTI), hadcrut, uah, and rss. You need to get the land-only versions of those. See my links above for the locations of the land-only versions.

    Keep up the good work,

    w.

  156. Lars P. says:
    October 26, 2011 at 5:05 am

    kramer says:
    October 24, 2011 at 5:01 pm

    “I emailed the BEST team a while ago asking if they could just plot the rural, unadjusted data. I got an email a few days ago saying it’s done.
    My question is, if the rural data unadjusted data agrees with the adjusted and unadjusted data, why bother to adjust the data at all?”

    There is the RUTI project that works only on rural data

    http://hidethedecline.eu/pages/posts/ruti-global-land-temperatures-1880-2010-part-1-244.php

    ___________________________________
    Eye balling your/BEST rural data graph It looks like a net increase in temp of 0.2 from the peak in the 1930’s to the current peak (even Jones agreed the temp is not increasing since 1995)

    Given the error we can not even be sure that the 0.2 is even significant especially if we are still recovering from the LIA.

    If you go valley to valley (1885 to 1975) you do not even get 0.2 and surely we have seen a greater increase in industrialization from 1885 to 1975 than from 1975 to present. (CO2 data is from 1958 only)

    “…..The sum-of-energies model assumes that different energy sources dominate during different periods of history. For example, traditional renewables (wood, dung, etc.) were the world’s dominant sources of energy until almost 1900. Coal then was the dominant source of energy until the middle of the twentieth century, after which crude oil began to dominate. Oil remains the dominant source of energy to this day, but its share in the energy mix peaked in 1973 and has been declining since. The natural gas share of the energy mix has been steadily increasing and looks set to take over the number one position sometime early this century……”

    http://www.mnforsustain.org/pop_population_and_energy_zable.g.htm

    ERRRRrrrrrrrr if black carbon (soot) is also seen as a major contributor to global warming then how come the temperatures nose dived from 1935 to 1975 while the USA and EU were going full out building up and expanding industry after WWII???

    I am more inclined to trust this data set to give a realistic picture because the influences from cities is removed without the use of “Fudge Factors”.

  157. Anyone think we need to go back to the Raw data produced by the stations and throw out all the data recorded in GHCN by the NCDC.

    Has anyone been able to download the individual (264 Mb) station list in the Berkeley record?

  158. From Bill Illis on October 26, 2011 at 6:01 pm:

    Has anyone been able to download the individual (264 Mb) station list in the Berkeley record?

    Referencing this previous post of mine,

    Just for shots and goggles, I tried downloading the 253MB zipped text version, on dial-up, which ideally would take about 11hrs with an otherwise-unused connection.

    A day later (last night), I had a file the Archive Manager on my Debian Linux system thought was damaged. The built-in zip -FF command fixed it with a warning that data.txt was truncated, the repaired version reported as 181.7MB. Archive Manager was able to extract the files, barely, it sapped the resources of my old Dell P4 so horribly it would have repeatedly crashed if running Windoze, left the machine unusable for about ten minutes. Of the resultant files, there is data.txt, 590MB. After 10 minutes of the text editor trying to load it in, watching more records keep filling in at the bottom (uncertainty is always 0.0000?), I canceled that. The other largest file is flags.txt, reported as 12.6GB (yes, giga). I haven’t tried opening it. There are three other much-smaller files, less than 6KB each.

    The second downloading will be finishing in about two hours. I’ll see then if this copy is likewise reported as damaged.

  159. michael hammer says:
    October 24, 2011 at 11:11 pm

    “Something I dont quite understand. In the early 1970′s the National Academy of Science published a climate reconstruction showing that temperatures fell by 0.7C ( about 1.3F) between 1940 and 1970. This was the basis for many articles in both science and environmental journals suggesting we were heading for dangerous global cooling (anthropogenic of course). The modern reconstructions now show no cooling over this period. ”
    ====================================================================

    Your observation is spot on. As best as can be determined, the disappearance of the decline to a strong minim2um in 1976 is due to the inconsistency of the set of stations used in modern reconstructions of GMT. Thousands of stations came online in the post-war era in cities thast had not reported temperatures before. The post war-period also was one of intense urbanization and motorization of society in many countries. That is the factor that makes all recontructions which fail to maintain a FIXED set of stations over the entire stretch of time ultimately unreliable indicators of climatic “trends.” Contrary to the impression they present, BEST’s statistical massage of record fragments doesn’t begin to address that problem,

  160. @Bill Illis:

    Download successful, 10 files unpacked.

    data.txt 590.0 MB
    data_flag_definitions.txt 5.7KB
    flags.txt 12.6GB (Archive Manager reports an expected 631.8MB size)
    README.data 1.6KB
    README.txt 3.2KB
    site_detail.txt 8.7MB
    site_flag_definitions.txt 1.6KB
    site_summary.txt 1.3MB
    source_flag_definitions.txt 2.8KB
    sources.txt 7.1GB

    Text editor flatly said it couldn’t open the two biggest files, flags.txt and sources.txt. It made a brave attempt on the next largest, data.txt, but after about ten minutes of sluggish computing and the text editor being unresponsive I mercifully killed it. The rest opened fine.

    Want to play with the BEST files? Got supercomputer? With at least 30-40GB of RAM?

  161. Willis,

    Thanks for the pointer about comparing land with land/ocean – I really should have read into it more! I’ll add the land-only datasets you suggest when I get a chance and retry.

    This might solve another conundrum that one of my users, Mike Scott, pointed out a couple of days ago, and actually prompted me to add BEST in the first place: we can’t match Berkeley’s depiction of “HADCRU” in their analysis graphs with any variety of HADCRUT3. Is it possible they are using CRUTEM (land only) and mislabelled it?

    Paul

  162. Climate change charlatans do not do science. They manipulate science. They have been doing it for many years under the auspices of the IPCC. It is just that they have now well and truly been exposed by their own peers. They know they have been exposed … so what they are now doing is simply trying to desperately preserve what little is left of their once impressive reputations, every which way they can.

    These disgusting climate change charlatans cannot bring themselves to acknowledge that they may have been wrong all along about catastrophic man-made global warming. So, for them, it is all or nothing. I mean, come on, after all we have now learnt about the shortcomings with the US surface temperature data and about UHI effects, these climate change charlatans think they can still con the world?

    I cannot wait for a day when all these climate change rogues (well, they are certainly not honest scientists) dragged into the courts to be held accountable for grossly misrepresenting the science and for engaging in misleading and deceptive conduct.

  163. Here’s their actual un-smoothed monthly data:

    ;———————————————————-

    It’s cooked data.

    Your bias is in the mean used to calculate the anomaly.

    Why can’t you show us the un-molested data?

    Where’s the beef?

  164. Agile Aspect says:
    October 28, 2011 at 11:56 pm

    Here’s their actual un-smoothed monthly data:

    ;———————————————————-

    It’s cooked data.

    Your bias is in the mean used to calculate the anomaly.

    Why can’t you show us the un-molested data?

    Where’s the beef?

    That’s what they released …

    w.

  165. woodfortrees (Paul Clark) says:
    October 29, 2011 at 6:47 am

    Further to the above, in the unlikely event anyone is still reading here – I have now added land-only versions of GISTEMP, CRUTEM, RSS and UAH and compared with BEST, with baseline adjustment – see http://www.woodfortrees.org/notes#best

    You da man, Paul, and woodfortrees is a great resource.

    My thanks,

    w.

  166. Brian H says:
    October 26, 2011 at 1:27 am

    Dave Springer says:
    October 25, 2011 at 4:24 pm

    The big difference is that the ocean has an albedo close to zero and land has an albedo of about 15% so the SST should go up more because it absorbs more energy.

    Um, specific heat? Currents? Evaporation? Energy temperature.

    HTML quirk/typo above; the carets meaning “does not equal” didn’t reproduce. Here’s a “forced” version:
    Energy < > temperature.

  167. Theo

    “Your thought “think about “power” in a statistical sense” is a clear recommendation that we should make inferences from our characteristics of our system of representation to the world.”

    no. it a suggestion about looking at the property of tests we call “power” which is not what you think

Comments are closed.