A viewpoint on the Antarctic warming debate

Antarctic temperature plots through the history of the debate:

NASA 2004:

NASA 2007:

Steig et al 2009:

antarctic_warming_2009

 

O’Donnell et al 2010:

 

Some historical perspective:

“If your result needs a statistician then you should design a better experiment”

Ernest Rutherford quotes (Baron Rutherford of Nelson. New Zealander born British Chemist who laid the groundwork for the development of nuclear physics by investigating radioactivity. Nobel Prize in 1908. 1871-1937)

Personally, besides all the original obtuse PCA statistical sophistry, the buried weather stations, and other issues, now I simply think the issue boils down to: it’s weather, not climate.

See here as to why.

 

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41 thoughts on “A viewpoint on the Antarctic warming debate

  1. Ernest Rutherford said a lot of stupid things. That was one of them.
    Another was: “Anyone who expects a source of power from the transformation of the atom is talking moonshine.”

  2. Juice says “Ernest Rutherford said a lot of stupid things. That was one of them.”
    Lord Rutherford, the man who split the atom probably did say stupid things. Who doesn’t? Albert Einstein once said “God does not play dice”, an later had to apologise to Heisenberg.
    But Rutherford’s comment “If your result needs a statistician then you should design a better experiment” is not stupid, but profound. Juice, if you want to disagree with the arguments presented here, then address the arguments directly. Don’t waste our time with your ad hominem attacks on a Nobel prize-winner who won that prize in the days when it really meant something.

  3. A better comment would be “If your result needs a statistician and you don’t have a real one, then you should hire somebody to do it right.”
    The thing is… it’s easy to learn enough about almost anything to be able to find problems in someone’s experiment – but it’s really hard to be good at something without some solid experience in the field. Most climate scientists might be great at their own subspecialty, but have little to no experience in the things that are currently destroying their research results. Like statistics, or computer programming, or solar astronomy.
    Or, as one climate scientist once angrily told me, “insolation is a constant.” What?

  4. Juice says:
    February 13, 2011 at 10:53 am
    Okay, we know you don’t like Rutherford. Do you have anything of substance to contribute? Do you have the courage to tell us the rest of what you think? Lay it out for us. Be brave.

  5. John Johnston says:
    February 13, 2011 at 11:22 am
    Juice says “Ernest Rutherford said a lot of stupid things. That was one of them.”
    Physicist Rutherford is clearly making the point that a good physical experiment would be even better one if what one concludes from it does not depend on the finer details of a statistical analysis of the results. A very reasonable observation I would have thought.

  6. The use, or rather abuse, of statistics is at the heart of the current problem with science.
    The hunt for a signal amidst noise makes sense when looking into phenomena where the signal has intelligence (i.e. radio signals). Cleaning up the noise has a clear objective since you already know what the signal is supposed to be.
    When looking into natural phenomena all you can do is find patterns within the noise and then assume these have meaning. I am sure that many of the resolved patterns do have meaning, but too often we see that what is assumed greatly colors the interpretation.
    Beyond the fundamental problem of the meaning of a resolved signal lies the problem of cherry picking of parts of the noise to “help” in tuning a signal.
    I understand the motive in cleaning up input to remove random noise and bad data, but too often this filtering is done to make a case for reasons not is the data, but in the researcher’s bias. And to make matters worse, when this is pointed out, the researchers either can’t understand the criticism, or do and don’t care.
    It is very unfortunate for science that this kind of statistical abuse has been allowed to prosper. It has permeated to the top of academia and most scientific organizations.
    I doubt that changing the current paradigm will occur in my lifetime, but there are indications that there is movement toward a recognition of the problem.

  7. If you are going to use ‘statistics’, how good is your data sample? Do you have all of the highs and lows of temperature variations over the last one billion, three billion or 6.5 billion years? If not, how good is your sample, then? What, one millionth of the total data set represents the whole set?.. Crawl back into your cave and turn out the lights. Worthless opinion is like anal sphinctors, eveyone has one.

  8. In the referenced WUWT thread “Mike” said:
    “Both papers show that most of Antarctica is warming.”
    Can one even say that? I would each paper has a statistical model that purports to show warming across the entire Antarctica continent based upon sparse data from around the edge of the continent. The real issue is do the models reflect reality in any way? From our experience of the US we would say that that a handful of stations around the edge of the continental US and a statistical model could not in any way model the entire temperature map of the US.
    I think its just numbers with no mechanism for validation.

  9. I may be naive about such things but I am amazed that anyone would ignore the one bit of Antarctica which sticks out, free of sea ice, into the Pacific Ocean during the decade that the PDO peaked, and ending with a big Modoki El Nino. If you stick your arm into a hot oven, your arm will get hot.

  10. Can some explain why Steig is still insisting, along with A. Revkin, that O’Donnell is planning to admit he was wrong on the major points? This is Steig’s Feb 9th post at RC which remains up:
    “Ryan O’Donnell made a series of serious of allegations against me at ClimateAudit, in the context of our friendly dispute about whether his new paper in the Journal of Climate supports or ‘refutes’ my own results, published in Nature.
    To his credit, Ryan has offered to retract these allegations, now that he is a little better acquainted with the facts.”
    I keep harping away at this, and I apologize for that. I guess I’m either crazy or naive. Or both. I mean, how can he leave this up knowing that as of Feb 11, it’s been demonstrated via O’Donnells actual response that his apology is confined to one tangential issue as below..
    “Subsequent to my post on Feb 7, 2010 here, Eric Steig informed me by email that he had not seen our Response to his Third Review, as I had previously assumed. I apologize for my misunderstanding on this point, which was, however, incidental to the major concerns expressed in my post. A more detailed response on matters raised in Steig’s most recent RC post and other issues will be forthcoming.”
    Evidently, as deep as my cynicism goes, it’s not deep enough. I apologize for hammering away at this, and I don’t have time to read through all the comments to see if it’s been discussed. But such brazen gamesmanship, when it can so easily be show to be such, surpasses understanding. Or my understanding anyway..

  11. DirkH writes,
    Delingpole has a good summary of the Steig affair. He concentrates on the abuse of peer review, not on the statistics.
    Delingpole has a strong political spin, sure enough, but shows that he understands nothing about peer review. Steig’s reviews were those of someone who thought O’Donnell’s paper had flaws but also merit; he helped make it good enough to publish.

  12. “Personally, besides all the original obtuse PCA statistical sophistry, the buried weather stations, and other issues, now I simply think the issue boils down to: it’s weather, not climate.” Or to be blunt you dont understand the discussion.
    Did you even pass high school math?
    REPLY:Did you even read the link? Attack the messenger with juvenile prose, ah, spoken like a true anonymous coward. Troll on brother, but do it somewhere else. – Anthony

  13. Phil writes,
    Antarctica is very large, very cloudy and very cold. There are few historical temperature records and those are sparse, gappy and noisy. Temperature reconstructions, like those shown above, are speculative, although they may be interesting.
    Sparse data is not the same as no data, or pure speculation. Steig’s and O’Donnell’s papers are about how to use the data we have as effectively as possible.

  14. Gneiss says:
    “Steig’s reviews were those of someone who thought O’Donnell’s paper had flaws but also merit; he helped make it good enough to publish.”
    I think Steig was pushed into a corner. He had no choice but to give in. O’Donnell’s paper was published depite Steig, not because of him.
    See John Brignell’s view of refereeing. It’s only a few paragraphs.

  15. Smokey writes,
    I think Steig was pushed into a corner. He had no choice but to give in. O’Donnell’s paper was published depite Steig, not because of him.
    Steig was not pushed into a corner or forced to give in. Reviewers have no veto power, and they don’t have to agree. Disagreement is in fact very common, and editors are the ones who make the call.
    For what looks like the clearest account of how things actually went down, I recommend Neilsen-Gammon. It’s quite different from the emotional versions on this site, and contradicts O’Donnell’s accusation that Steig suggested ridge regression. But it’s not all the same as Steig’s recollection either.
    http://blogs.chron.com/climateabyss/

  16. Gneiss says: “Steig’s reviews were those of someone who thought O’Donnell’s paper had flaws but also merit; he helped make it good enough to publish.”
    It was already good enough to publish, according to Reviewers B and C. Reviewer A was the only one who required a major rewrite. After all was said and done, Steig 2009 was still toast.

  17. Gneiss says: “Sparse data is not the same as no data, or pure speculation.”
    Untrue in this case. In Antarctica, there’s so little coherent data as to make zero difference between sparse and none. Remember the Trenberth epigram re Steig 2009? “It is hard to make data where none exist.”
    Gneiss says: “Steig’s and O’Donnell’s papers are about how to use the data we have as effectively as possible.”
    Absolutely untrue. O’Donnell’s paper shows that Steig’s statistical methods, such as they were, were seriously flawed. O’Donnell was not trying to create a definitive (or more “effective”) reconstruction with the data. He says: “…The only claim we make is – given the data and regression method used by S09 – that the answer is different when the method is properly employed. Period.”

  18. The most telling graphic is in the O’Donnell (2010) paper. It shows the temperature trends on the peninsula with trends that are not statistically significant “grayed” out. What this shows is that there is pretty much no significant anything except warming on the peninsula.

  19. An educated guess may be educated, but it is still a guess. For background see my previous comment:
    First, Schneider & Steig 2004 state (pg 5):

    In addition, monthly means of TIR data have a clear-sky bias because infrared surface temperature estimates cannot be made in cloudy conditions. Since the net effect of clouds on surface temperature in the Antarctic is warming (e.g. King and Turner 1997), monthly cloud-free averages from the infrared observations tend to be cooler than in-situ station observations by ~0.5 K (Comiso 2000).

    However, this ~0.5 K reference may be conservative as the actual quote from Comiso 2000 is:

    The results show that the cloud-free only monthly average is colder than the true monthly average by about 0.3°C with a standard deviation of about 0.6°C during summer and 0.5°C with a standard deviation of 1.5°C during the winter.

    However, Town 2007 has different estimates for the South Pole (which may be taken as indicative of the East Antarctica plateau – the largest area of Antarctica) (pg 556):

    Times of clear skies are 0.5–1 K lower than the monthly mean during summer, and 3–4 K lower than the monthly mean during winter.
    The difference between mean all-sky winter temperatures and mean clear-sky winter temperatures can be explained by the magnitude of the LNCRF (longwave net cloud radiative forcing). The difference in thermal emission of a radiatively black surface at -63°C (the mean clear-sky winter 2-m temperature) and a radiatively black surface at -59°C (the mean all-sky winter 2-m temperature) is approximately 8.6 W m^-2. This is nearly the same as the annual mean LNCRF of 10 W m^-2. Cloud radiative forcing can therefore explain all of the increase in monthly mean 2-m temperature from clear skies to all skies during the winter. Advection of heat and moisture aloft is responsible for maintaining the inversion-top temperature, approximately 400 m above the surface, at -35°C. This large-scale advection provides the energy that the clouds and atmosphere radiate to the surface, raising near-surface atmospheric temperatures.

    Second, please look at slide 27 here. This refers to figure 5 of Comiso & Stock 2001. They show that the mean monthly cloud fraction anomalies from 1982 to 1999 are decreasing by

    -0.50 ± 0.06% (ice sheet >2000m)
    -0.21 ± 0.04% (ice sheet <2000m).

    Third, did Steig 2009 in-fill the cloudy pixels using the clear-sky pixels by taking into account the cold bias in the clear-sky pixels? They don’t mention that they did in the text and, since they didn’t disclose their satellite data, it isn’t clear what they did. Furthermore, Town 2007 seems to say that clouds significantly warm the surface in Antarctica. If the cloud fraction is decreasing, then wouldn’t the “warm” fraction would also be decreasing? Combined, wouldn’t failing to take into account one or both of these create a warm bias in the trend?
    Fourth, if you try to take these apparently non-trivial issues into account when doing the hind-cast of the matrix for the pre-satellite era, what assumption do you use for the trend in the cloud fraction? Given the decreasing trend in the satellite era, would it be reasonable to cast that same trend backwards for the pre-satellite era? Would it be reasonable to assume the pre-satellite era cloud fraction was constant? If so, on what basis? The surface data in Antarctica seems to show an early warming, followed by a recent cooling. That is, the surface data trend would seem to show an inflection point. Wouldn’t it be reasonable to then assume that the cloud fraction trend for the last 50 years also had an inflection point? If so, when? If not, why not? The AVHRR-derived matrix is back-cast by anchoring it to the surface station records of the pre-satellite era. To what could you anchor a back-cast of the cloud fraction trend? Is there anything or wouldn’t it be mostly speculative?
    I submit all of the above as support for stating that the images in this post are speculative (not purely speculative, but still speculative), but without claiming perfection. My logic may be faulty, so I have tried to explain it in case I have misunderstood something.
    References:
    (Comiso 2000) Comiso, J. C. Variability and trends in Antarctic surface temperatures from in situ and satellite infrared measurements. J. Clim. 13, 1674–1696 (2000).
    (Schneider and Steig 2004) Schneider, D. P., Steig, E. J. & Comiso, J. Recent climate variability in Antarctica from satellite-derived temperature data. J. Clim. 17, 1569–1583 (2004).
    (Comiso and Stock 2001) Comiso, J. C and L. V. Stock, 2001: Studies of Antarctic cloud cover variability from 1982 through 1999. Proc. of the Int. Geosci. and Remote Sensing Symposium, vol. 4, 1782-1785.
    (Town 2007) Town, M. S., Walden, V. P., Warren, S. G., Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements, J. Clim. 20, 544-559 (2007)
    P.S. Steig 2009 claims that there is a net long-term warming trend in Antarctica. Comiso and Stock 2001 show a long-term (1982-1999) steady decreasing trend in cloud fraction. Given the warming of the surface due to cloud cover explained in Town 2007, this should mean a long-term cooling trend in Antarctica. Which is it: warming or cooling? And which can be more accurately measured by satellite: Cloud Fraction or Surface Temperatures? I submit this as more support for these images as speculation, although not pure speculation.

  20. @Gneiss:
    February 13, 2011 at 3:25 pm
    “he understands nothing about peer review. Steig’s reviews were those of someone who thought O’Donnell’s paper had flaws but also merit; he helped make it good enough to publish.”
    Do you really believe that, or more to the point, expect anyone here to? Is it not far more likely that Steig’s reviews were a damage limitation exercise that backfired, leading to further damage limitation from the pages of RC?
    It seems that to many AGW proponents, peer review is simply a reinforcement process, whereby any scrutiny of the scientific method (or lack thereof) in climate divination can be smothered with obfuscation, misrepresented, censored or squashed by any means necessary.
    This way, any progress of understanding is completely abandoned and we are left with an echo chamber full of zealots slapping each other on the back for their extreme cleverness in statistically eking out minute patterns from meaningless noise and mangled data. Obviously better this than to allow the impressionable public to get wind of uncertainty in the settled science though, don’t you think?

  21. jorgekafkazar writes,
    It was already good enough to publish, according to Reviewers B and C. Reviewer A was the only one who required a major rewrite.
    Reviewers B and C, unlike Reviewer A, were not doing their jobs. As Nielsen-Gammon writes,
    “Meanwhile, reviewer B states that he/she doesn’t really understand the statistics, saying ‘I am not conversant with the statistical nuances of the analyses by Steig et al. and the approach adopted here, so trust that Eric Steig or Michael Mann will provide that needed expertise.’ Reviewer B has not seen any other reviews at this point, but is fully expecting that Steig or Mann ought to be one of the other reviewers.
    Reviewer C states that he/she carried out his/her review of O’Donnell et al. without re-reading Steig et al. ”
    After all was said and done, Steig 2009 was still toast.
    On reconsidering I have to agree with you that attacking Steig, not learning anything about climate or Antarctica, was the motive behind O’Donnell’s paper. But now it’s published, so is Steig’s paper toast? Only in certain corners of the blogosphere, like this one.
    Among scientists, that’s not how it works. O’Donnell is not the last word either. And then there’s that real Antarctica of rock and ice, where the patterns of warming (or not) will become more obvious in the years ahead. Reality might better fit Steig’s work, or O’Donnell’s, or neither.

  22. jorgekafkazar writes,
    Another untruth. You evidently didn’t follow the link, Gneiss:
    Evidently I didn’t, but I did. And when I said it shows no understanding, that’s the truth.
    Delingpole obviously understands all the critical points of peer review well enough, just as I don’t have to study horse anatomy to know a dead horse when I see one.
    If you say so.

  23. Gneiss says:
    February 13, 2011 at 6:10 pm
    “Among scientists, that’s not how it works. O’Donnell is not the last word either. And then there’s that real Antarctica of rock and ice, where the patterns of warming (or not) will become more obvious in the years ahead. Reality might better fit Steig’s work, or O’Donnell’s, or neither.”
    =====
    I vote for neither, considering the time constraints.

  24. Gneiss says:
    February 13, 2011
    Reviewers have no veto power, and they don’t have to agree. Disagreement is in fact very common, and editors are the ones who make the call.

    Depends upon the journal. The ones I reviewed for : three reviewers, two rejections, paper’s toast.

  25. The ones I reviewed for : three reviewers, two rejections, paper’s toast.
    That’s not a veto, that’s a vote. And it’s not what happened in this case.

  26. Among scientists, that’s not how it works. O’Donnell is not the last word either. And then there’s that real Antarctica of rock and ice, where the patterns of warming (or not) will become more obvious in the years ahead. Reality might better fit Steig’s work, or O’Donnell’s, or neither.
    Generally among scientists poor reasoning is not revisited. O’Donnell’s will not be the last word, for sure. However if the real world does fit Steig, then it will be purely by accident, because his paper is not sound.

  27. One of the most jawdropping bits of hard data that finally made me into a skeptic was John Daly’s plot of a cooling south pole. I made a wallet card of it to see how various people I ran into responded to this astonishing debunking of the claim that the entire globe was suddenly on a major upswing in temperature. The response was mostly the same, namely disbelief that whole populations of scientific bodies would simply ignore such damning dents in their alarming theory.
    How has this chart of what I called ‘The South Pole’ held up? The original is here: http://www.john-daly.com/stations/amundsen.gif It’s the Amundsen-Scott base and is indeed at The South Pole. Ten more years of data later, and…it’s feeling some heat finally, but not much: http://appinsys.com/globalwarming/climgraph.aspx?pltparms=GHCNT100AJanDecI195720090900110AR70089009000x
    It still does not seem to be getting the message that it should form the blade of a hockey stick. The closest stations that have data going back to the 1800s are Capetown, Africa (http://appinsys.com/globalwarming/climgraph.aspx?pltparms=GHCNT100AJanDecI185720090900110AR14168816000x) and Adelaide Airport, Australia (http://appinsys.com/globalwarming/climgraph.aspx?pltparms=GHCNT100AJanDecI185720090900101AR50194672000x) and neither corresponds to a Mannian hockey stick.
    I abandoned my wallet card though since the trend is no longer so linearly downsloped, in favor of super long thermometer records in the North (http://oi49.tinypic.com/rc93fa.jpg), along with a global average that shows a similar lack of any uptick in smooth warming (http://oi49.tinypic.com/2mpg0tz.jpg). Call me a simpleton, but these charts alone in their failure to show a change in trend is even more convincing than the oddity of limited span Antarctica data. Until I run into a serious discussion by about how actual thermometer records are not fit for the cover of IPCC reports, all this back and forth debate about statistical software settings makes me feel that both sides of this debate are failing to educate voters on the simple fact that thermometer data quite simply do not say what almost every left leaning citizen assumes it does. Being dragged into debate about statistics is a PR trap!

  28. Reality might better fit Steig’s work, or O’Donnell’s, or neither.

    I have a hard time trying to follow what you are saying as a fair representation on what happened when this sentance shows that the whole point of the argument, which was stated clearly both in text followed by in graphics, is being missed by you.

  29. Although it is true that Ernest Rutherford was born in New Zealand, to
    describe him as “New Zealand born” implies that as a babe in arms
    he was whisked away elsewhere. In fact, E.R. graduated from Canterbury
    University. And that’s not Canterbury, England.

  30. #
    #
    climatebeagle says:
    February 13, 2011 at 12:55 pm
    In the referenced WUWT thread “Mike” said:
    “Both papers show that most of Antarctica is warming.”
    Can one even say that? I would each paper has a statistical model that purports to show warming across the entire Antarctica continent based upon sparse data from around the edge of the continent. The real issue is do the models reflect reality in any way? From our experience of the US we would say that that a handful of stations around the edge of the continental US and a statistical model could not in any way model the entire temperature map of the US.
    I think its just numbers with no mechanism for validation.
    #######
    then you havent read the paper and you dont understand how calibration and verification works or how one constructs a model with hold outs.

  31. The thing about Rutherford was that he was a great experimenter, and encouraged many in his field to think outside the square, I think 10 or 11 of his trainees and colleagues went on to get nobel prizes.
    His quip about statisticians was right for the time.
    Not for nothing he was buried near Newton in Westminster abbey.

  32. steven mosher says:
    February 13, 2011 at 10:24 pm
    “then you havent read the paper and you dont understand how calibration and verification works or how one constructs a model with hold outs.”
    Are you actually trying to say that the “Models” can give an accurate view of USA temperatures just using a few Temperature sites on the Coast?
    Have you looked at the USA/Canada temperature map lately?
    If you used the West Coast you get Warming. Look at the East Coast you get massive cooling.

  33. John Marshal says “Perhaps ‘Juice’ is a statistician.”.
    No, mate. Were Juice a statistician, he or she would have known what Rutherford meant by his statement “If your result needs a statistician then you should design a better experiment”. Note – he did not say “If your experiment needs a statistician”. Just the result, John.
    Lord Rutherford was a scientist. He knew that the only thing that statistics can “prove” is correlation. Indeed, they are all about correlation, not causation. A scientist may use statistical analyses when assessing whether phenomena merit close investigation. He may use statistics to help him formulate theories about the underlying causes but never as proof, per se.
    Graphs of New Zealand statistics in the nineteen-sixties present three almost identical correlations for NZ birthrate. The birthrate declined in almost exact inverse relationship with the rise in the sales of three commodities – apples, televisions and oral contraceptives.

  34. It is also seems illogical to mix the temperature data of areas that have clearly different climates. When I audited climatology in college (1980), we studied a map that showed different climate regions. Accompanying the map were temperature and precipitation data by month for a particular area. I went back to look at it, but it did not have Antarctica included. Too little data perhaps? Anyway, as many others have noted, the peninsula is clearly a completely different climate regime from the continent, and the continent from the oceanic fringe of the continent. It seems to me that it would be interesting to have climatologist suggest station sites that would more clearly delineate the climate regions of the Antarctic. If Antarctica was inhabited as thickly as Australia, I daresay that several different climate regimes would be identified over the continent.
    This has always perplexed me about the global temperature also. How are the differing regional climate characteristics accounted for in creating and comparing world wide temperature averages? Are stations placed on the globe to account for climate regions, and weighted for that region?
    Also,

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