A Very Informative Post — but not the way they think it is

And that very informative post is at the Watts Up With That blog. It’s even the “recommended” post there.


The title is “NOAA shows ‘the pause’ in the U.S. surface temperature record over nearly a decade.” It’s based on monthly average temperature anomaly for the 48 conterminous states of the U.S., using data from the USCRN (U.S. Climate Reference Network), which probably is the highest quality temperature data for the U.S., for climatological purposes. The theme of the post is that data since 2005 show a cooling trend, albeit not statistically significant, so it shows “the pause.” After all, it certainly doesn’t show a statistically significant warming.

Here’s the data together with a trend line estimated by least-squares regression:

linear

The estimated trend is -0.06 deg.F/yr (or, -6 deg.F/century). Here’s what uncle Willard has to say about it:


It is clear there has been no rise in U.S. surface air temperature in the past decade. In fact, a slight cooling is demonstrated, though given the short time frame for the dataset, about all we can do is note it, and watch it to see if it persists.

Likewise, there does not seem to have been any statistically significant warming in the contiguous U.S. since start of the new USCRN data, using the average, maximum or minimum temperature data.

There’s one thing I’ll have to agree with: that the time frame is short. The total time span is less than 10 years. For climate purposes, for determining the actual, relevant trend, it’s not nearly long enough — especially since this is for the 48 states of the U.S. only (not the whole world), and the noise level in that regional time series is a lot bigger than the noise level in global temperature.

How meaningful is the purported “trend”? To answer that question we’d have to know the uncertainty associated with the trend estimate. Of course (!) Watts doesn’t provide that. But one of his “reviewers” does, in what is perhaps Watts’ most “informative” graph, one provided by Willis Eschenbach, after Watts “… asked three people who are well versed in data plotting and analysis to review this post before I published it …“:

crn-mean-us-temperature-anomaly

It clearly indicates that the estimated trend is -0.6 +/- 0.68 deg.F/decade, which is the same as -6 +/- 6.8 deg.F/century. I get the impression that Willis Eschenbach is uncle Willard’s “go-to guy” for data analysis.

Problem is, that uncertainty range of -6 +/- 6.8 deg.F/century is a 1-sigma error range. That means it’s not a 95% confidence interval, it’s only a 68% confidence interval. Which doesn’t inspire a lot of confidence. If I claimed there was a trend based on 68% statistical confidence, what do you think the WUWTers would say? Of course, if we go by the 95% confidence interval (the de facto standard in statistics) then the actual trend could be as high at 7.6 deg.F/century. That’s a helluva lot! Which makes me wonder why Watts is so convinced that these data show an indisputable “pause.” (Just kidding)

Other problem is, even for a 1-sigma error range it isn’t correct. The residuals show distinct autocorrelation, a phenomenon which makes the estimated uncertainties from standard statistical software too low. To get a realistic estimate we’d have to correct for autocorrelation. I estimate that the corrected standard error (the corrected “1-sigma” error range) is actually +/- 13.1 deg.F/century. That means that even within the 68% confidence interval the actual trend might be as high as 7 deg.F/century. That too is a helluva lot. And within the 95% confidence interval, the trend might be as high as 20 deg.F/century. You read that right. Twenty degrees F per century.

What’s the bottom line here? If you analyze it correctly, you discover that using just this set of data, the actual trend could be as low as -32 deg.F/century or as high as +20 deg.F/century. That doesn’t exactly narrow things down, does it? In fact, for an honest estimate of whether or not the trend has (since 2005) been any different, faster or slower, than the trend leading up to 2005, using just this data set gives you an answer which is useless.

And that, ladies and gentlemen, is the truly informative aspect of Watts’ post. His analysis is useless but he still touts is as a clear demonstration of “… ‘the pause’ in the U.S. surface temperature record over nearly a decade.” I’d say it is very informative indeed — not about climate (!) but about about Anthony Watts’ blog — that he (and most of his readers to boot) regards a useless trend estimate as actual evidence of “the pause” they dream of so much.

Incidentally, there’s yet another problem with Willis Eschenbach’s “error bars” which are plotted on the graph (the yellow lines above and below the trend line, let’s call that the “error envelope”). They too aren’t right. Here is an error envelope for the trend line without bothering to apply the autocorrelation correction, just using the white-noise model:

raw_envelope

Let’s zoom in the y-axis so you can see the shape of the upper and lower limits:

bigyaxis

Note that the upper and lower limits are curved lines. Now let’s magnify the y-axis on Eschenbach’s graph:

resized

Notice that Eschenbach’s upper and lower limits are not curved lines, they’re bent straight-line segments? I think it’s safe to conclude that Willis Eschenbach doesn’t know how to do this calculation. Which makes him the perfect choice to be Anthony Watts’ “go-to guy” for data analysis.

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24 responses to “A Very Informative Post — but not the way they think it is

  1. Another informative aspect is that the post is written with the subtext that USCRN reveals a truth that the adjustment a comment, over this time USHCN and USCRN are virtually identical, (with USHCN having a slightly greater downslope).

  2. Sorry, last comment lost a bit – should be:
    Another informative aspect is that the post is written with the subtext that USCRN reveals a truth that the adjustment-plagued USHCN did not. But Zeke noted in a comment, over this time USHCN and USCRN are virtually identical, with USHCN having a slightly greater downslope.

  3. Straight lines? Lets see, if you took Excel’s LINEST, and stick-built the error bars from Y_bar +/- se_Y, and the slopes from m1+/-se1…. yeah, that’ll look like fancy-schmancy stats-guy error-bars!

  4. Thanks. BTW, I recall that the minimum number of years to find a global trend is ~13 years. It must be much longer if looking at only a piece of the globe. (Do Tony and Willis even know the meaning of the word “global”?) Plainly, a 9-year span for only the US is ridiculous.

    I don’t know whether this is generally known, but the basic trends can be found from weatherspark.com. On menubar, click More and then Global Warming and you can get graphs filtered any way you like. If you zoom in on US alone and 2004 as start year, you will find indeed -7F/century. Here is a link to start=1978 for US and it’s +4F/century: http://weatherspark.com/#!climate;a=USA/IL_60666/Chicago/Chicago_O'Hare_International_Airport;ctum=1;cth=800;ctmy=10;ctsy=1978;ctey=2013
    Endless entertainment.

    [Response: I think I should do a post about why I think the attention given to “the minimum number of years to find a global trend” is misdirected.]

  5. So when you’re in a hole – keep digging.
    Poor Willard is now resorting to UPDATES.
    UPDATE 1.
    First up is Zeke Hausfather’s comment as noted @Nick Stokes above. Willard interprests the comment thus – “USCRN and USHCN data align nearly perfectly, as seen in this graph. That seems almost too perfect to me. Networks with such huge differences in inhomogeneity, equipment, siting, station continuity, etc. rarely match that well.”
    So WIllard smells a rat and investigates thoroughly. To start with, Roy Spencer has a HCN-CRN temperature comparison for individual pairs of stations that show massive average adjustments (which is to be expected for individual unaveraged data, although Spencer doesn’t appear to be looking at trends).
    Presumably Willard didn’t pause long enough to read Spenser’s concluding remarks. “The good news is that the NOAA U.S. Climate Reference Network is a valuable new tool which will greatly help to better understand, and possibly correct for, UHI effects in the U.S. temperature record. It is to their credit that the program, now providing up to 10 years of data, was created.”
    Instead Willard spots that NOAA “don’t show the baseline period or baseline temperature on the graph.” (Of course, there might be a clue in it being so similar to the HCN data.)
    And they mis-spell “contiguous!!!”
    All this is so much like Climategate that Willard concludes he wants “full disclosure of method, code, and output engine for the USCRN anomaly data for the CONUS.”
    UPDATE 2
    The “almost too perfect”” match between CRN & HCN turns out to be hiding “differences”, this being the technical term used by Bob Tisdale to describe what is a 0.22ºF/decade (+/-0.12ºF) trend for CRN-minus-HCN 2005-to date. The relevance of these “differences” to Willard’s analysis remain obscure but they must be significant because Willard has “okayed” this second update’s publication on Wattsupia.

    Of course, we are used to Willard making a total fool of himself. But Willard has attempted to publish peer-reviewed work on US temperature records. So why does he here demonstrate such a poor grasp of the subject?

  6. Once again, Watts and co.: PWNED. They’ll never embrace… The Escalator. Being blinded by ideology and conspiracy theories doesn’t help much either.

  7. Did I miss something? The trend line is going down isn’t it?
    So the big question is how long do we have to wait, statistically speaking, to find out if this an eight-year phenomenon or a much longer trend? Another 2 years, 5 years, 10 years, 20 years, 30 years?
    The longer we have to wait, the harder it is for climate scientists.

    • Why do we have to wait? Why not look at the 20 – 30 years before that graph to notice the rather alarming trend? Just looking at the last 10 years is cherry picking. Oldest denier trick in the book. Once again, I give you: The Escalator. It’s also cherry picking because the contiguous US 48 states represents less than 2% of the entire surface of the Earth.

      There have been faux ‘pauses’ before, and there will be faux ‘pauses’ again. But the overall trend at time scales that are climatically significant (~30 years or more) is up, up, up.

    • “Did I miss something?”

      Yes, pretty much the whole point. In a noisy data set such as the US temperature record, a short time has no predictive value. So why focus on it? We do, after all, have longer timespans available for analysis–it’s just that the results of that analysis aren’t so congenial to folks like the WUWT crew.

    • The short-scale trend line isn’t significantly different than what has been seen before–it just isn’t strong enough data to contradict a 30 or 40 year trend line. In the financial realm, this sort of claim would be like saying a flat 1 month AAPL trend is is significantly related to yearly or longer term results.

      If folks actually invest money like they say they analyze these time series, they’ll lose their shirts.

      Statistically speaking, an eight year temperature phenomenon is noise, just like 30 days-ending-returns are noise for long-term decisions.

    • John, regional climates can vary a lot. I wonder if the last decade or so of negative PDO has had a stronger influence on U.S. Land temps than the rest of the globe. Either way U.S. Temps aren’t really a high priority measurement if your looking for a way to gauge a warming signal (not that Anthony cares about that). U.S. Temps only likely matter in terms of political perception (polar vortex/dipole).

    • John, the best thing to do is to wait until your attention is drawn to a trend with the uncertainty properly stated (and explained) and where the start point hasn’t been cherry picked to maximise the strength of the argument.

      Alternatively, take a look at the whole record and see if such episodes have ocurred before and what happened then

      http://www.skepticalscience.com/graphics.php?g=47

      (fwoodfortrees.org is a great tool for checking this sort of thing).

      • One of my favourite trend graphers is this one “down under” at Hot Topic in New Zealand. Unfortunately, it hasn’t been updated with data since 2009, but the sliding button at the bottom to change the length of the trend period is great: you can look in real time at the effects of longer or shorter regression periods. It does all possible regressions of the specified time period, and you really get an idea of how the short-term trends are noisy and the long-term trends are much more uniform.

    • John. Take a look at this old Tamino post:

      http://web.archive.org/web/20081029173848/http://tamino.wordpress.com/2008/09/12/dont-get-fooled-again/

      Periods of declining temperature in a noisy temperature/time series that has a long-term positive trend are inevitable.

  8. Horatio Algeranon

    Don’t you know anything?

    > | < isn't supposed to show error bars

    It's a "frappy face" (combination frown/happy face) meant to highlight the different ways of looking at the graph

  9. Yes, John, you did, pretty much everything.

  10. Pete Dunkelberg

    Although the subject of this post is low grade analysis, it may also be of interest to look at seasonal regional trends, eg
    Arctic warming, increasing snow cover and widespread boreal winter cooling
    Judah L Cohen et al. 2012

  11. Horatio Algeranon

    I think it’s safe to conclude that Willis Eschenbach doesn’t know how to do this calculation. “

    I’d be willing to bet that even many of those who actually show the proper (curved) error lines “don’t know how to do the calculation”.that was used to get them.
    Just being able to plug the data into a statistics/graphing package and use whatever comes out (assuming it is correct, in effect) is a far cry from “knowing” how the results were obtained.

    The “plug and play” syndrome is not unique to one side of the climate debate.

    • Horatio Algeranon

      a far cry from “knowing” how the results were obtained
      …to say nothing of what the results actually mean (if anything)

  12. Well – actually I’d think they have a tiny bit of a point. If we look at James Hansen’s Global Temperature Update…

    http://www.columbia.edu/~jeh1/mailings/2014/20140121_Temperature2013.pdf

    …at Fig. 6 on page 4 we see that there has been a pronounced cooling in winter on the northern hemisphere (partially due to La Ninas). Which would make it plausible, that temperatures in the U.S. have gone down a bit, too.

    The funny thing is – those graphs make it much more easier to grasp why that has nothing to do with a ‘trend’ whatsoever. They show a steady rise of temperatures in summer and winter on the southern hemisphere. They show a steady rise of summer temperatures in the north.

    And they show that pronounced cooling in winter on the northern hemisphere … but only if you start your graph somewhere around 2004!

    Your calculations are correct as ever – but for the layman “…three times up and one time down doesn’t make a stagnation” it’s much simpler concept to understand…

  13. Aaron Lewis

    AGW is about total heat in the system. The air over the US does not hold much heat. Over the last 5 years, melting Arctic Sea ice absorbed more heat than is in the atmosphere over the US. Warming oceans absorbed more heat than is in the atmosphere over the US.

    With all that heat being sucked into the sea ice and oceans, it is amazing that the air over the US can find enough heat to drive a good thunderstorm, much less, a whole week of thunderstorms. The recent giant hail in the US is the stone cold proof of global warming. Let’s face it, it takes a ton of energy to make a good hail storm. To have that much heat left over after melting all that sea ice is amazing. Good hail storms are one of the benefits of AGW.

    (I mean there must be something good about AGW, and good hail storms is about as close as I can come to finding it. : )

  14. Well, I must say as soon as I saw you mention Willis Eschenbach, I knew it was a cock-up. It’s certainly a time-waster, but engaging him and explaining how he cocked it up will be a barrel of laughs.

  15. Well, I’ve learnt something – I didn’t know autocorrelation could be corrected for. I always understood it as being a ’cause for concern’, depending on how severe the Durbin-Watson statistic is.
    Would appreciate if someone could direct me to some reading on the correction methods and what they aim to achieve and what their shortcomings are.

  16. And here we have the next massively misleading graph on Wuwt:

    http://wattsupwiththat.com/2014/06/17/despite-the-hype-carbon-free-energy-sources-arent-gaining-traction-globally/

    Pielke claims a pause in carbon free energy consumption.

    He completely ignores the massive increase of total energy consumption (nearly 50% since the 90s) and the recent massive increases in alternative power.