Dr. Judith Curry writes about the Cowtan and Way paper which (according to some pundits) purports to “bust” the temperature pause of the last 17 years by claiming we just didn’t pay enough attention to the Arctic and Antarctic where there is no data. They do this by infilling data where there is none, such as NASA GISS tries to do by infilling temperatures from stations far away with their smoothing algorithm.
GISS station data with 250km smoothing:
GISS station data with 1200km smoothing:
Breathless interpreters of Cowtan & Way claim that by doing the same with satellite data instead of tortured surface data, Voilà “the pause” disappears.
Cowtan & Way are trying to address this lack of surface station data in these regions by doing infill from satellite data. At first glance, this seems an admirable and reasonable goal, but one should always be wary of trying to create data where there is none, something we learned about in Steig et al’s discredited paper on the supposed Antarctic warming. Plus, as some WUWT readers know, there’s a reason that satellite temperature data coverage doesn’t fully cover the poles. See the information on the UAH data at the bottom of this post.
A video of their methodology follows.
WUWT readers will note the before and after HadCRUT imagery from Cowtan & Way below. Take special note of the Arctic.
A discussion on that Arctic temperature infilling addition at high latitude follows Dr. Curry’s analysis.
Dr Judith Curry writes:
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Let’s take a look at the 3 methods they use to fill in missing data, primarily in Africa, Arctic, and Antarctic.
- 1. Kriging
- 2. UAH satellite analyses of surface air temperature
- 3. NCAR NCEP reanalysis
The state that most of the difference in their reconstructed global average comes from the Arctic, so I focus on the Arctic (which is where I have special expertise in any event).
First, Kriging. Kriging across land/ocean/sea ice boundaries makes no physical sense. While the paper cites Rigor et al. (2000) that shows ‘some’ correlation in winter between land and sea ice temps at up to 1000 km, I would expect no correlation in other seasons.
Second, UAH satellite analyses. Not useful at high latitudes in the presence of temperature inversions and not useful over sea ice (which has a very complex spatially varying microwave emission signature). Hopefully John Christy will chime in on this.
Third, re reanalyses in the Arctic. See Fig 1 from this paper, which gives you a sense of the magnitude of grid point errors for one point over an annual cycle. Some potential utility here, but reanalyses are not useful for trends owing to temporal inhomogeneities in the datasets that are assimilated.
So I don’t think Cowtan and Wray’s [sic] analysis adds anything to our understanding of the global surface temperature field and the ‘pause.’
The bottom line remains Ed Hawkins’ figure that compares climate model simulations for regions where the surface observations exist. This is the appropriate way to compare climate models to surface observations, and the outstanding issue is that the climate models and observations disagree.
Is there anything useful from Cowtan and Wray? Well, they raise the issue that we should try to figure out some way obtain the variations of surface temperature over the Arctic Ocean. This is an active topic of research.
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More from the same post at Dr. Curry’s site here
What is really funny is how Dana Nuccitelli has done an about-face since the satellite data now supports his argument. In his Guardian 97% piece [cited in Dr. Curry’s article] he’s all for this method.
But, just two years ago he was trashing the UAH satellite data on SKS as “misinformation”.
[http://www.skepticalscience.com/uah-misrepresentation-anniversary-part1.html]
But Dana thinks UAH data is apparently OK today. What a plonker.
I will give Dr. Cowtan props though for realizing what the hypers don’t. He says this in the Guardian article:
“No difficult scientific problem is ever solved in a single paper. I don’t expect our paper to be the last word on this, but I hope we have advanced the discussion.
I give him props for having a sense of reality, something sorely lacking in climate science today.
Here’s why trying to use the satellite data to infill surface data at the poles is problematic:
Take a look at this latest image for 1000mb (near the surface) from the polar orbiting satellite NOAA-18, one of the satellites UAH now uses for temperature data:
Source: NOAA/NESDIS Office of Satellite Data Processing and Distribution (OSDPD)
Note how the data near the poles starts to get spotty with coverage? Note also how the plot doesn’t go to 90N or 90S?
NOAA doesn’t even try to plot data from there, for the reasons that Dr. Curry has given:
Second, UAH satellite analyses. Not useful at high latitudes in the presence of temperature inversions and not useful over sea ice (which has a very complex spatially varying microwave emission signature).
NOAA knows high latitude near-pole data will be noisy and not representative, so they don’t even try to display it. UAH is the same way. Between the look-angle problem and the noise generated by sea ice, their data analysis stops short of the pole. RSS does the same due to the same physical constraints of orbit and look angle.
As you can see, the polar orbit isn’t truly polar. Here are maps from UCAR that helps to visualize the problem:
As you can see, the orbit path never reaches 90N or 90S.
Source: http://www.rap.ucar.edu/~djohnson/satellite/coverage.html#polar
They write:
Note that the orbit is slightly tilted towards the northwest and does not actually go over the poles. While the red path follows the earth track of the satellite, the transparent overlay indicates the coverage area for the AVHRR imaging instrument carried by NOAA/POES satellites. This instrument scans a roughly 3000 km wide swath. The map projection used in this illustration, a cylindrical equidistant projection, becomes increasingly distorted near the poles, as can be seen by the seeming explosion of the viewing area as the satellite nears its northern and southern most orbital limits.
So, not only is the satellite coverage distorted at the poles due to the look angle, the look angle issue actually causes the satellite to image a wider swath of an area known to produce noisy and highly uncertain microwave data. Basically, the higher the latitude of the satellite imaging past about 60N/60S, the more uncertain the data gets.
It seems to me that all that Cowtan & Wray have done is swapped one type of highly uncertain data infilling with another. The claim that the addition of this highly uncertain data to HadCRUT4 seems to contradict ‘the pause’ most certainly isn’t proven yet, as even Dr. Cowtan admits to in his caveat.
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The germane question IMO is, if using these new methods had increased the temp hiatus or indicated a large cooling trend, would they have discarded it as an error or still publishe?
The paper picks 1997 – 2012 for analysis. Why?
The paper picks UAH rather than RSS. Why?
The paper’s hybrid result claims 0.18 C rise from 1997 – 2012.
From Wood For Trees:
HadCRUT4 gives 0.08 C rise from 1997 – 2012.
UAH gives 0.16 C rise from 1997 – 2012.
RSS gives 0.00 C rise from 1997 – 2012.
So, the paper pulls data from UAH that covers 3% of the globe (the Arctic), adds it into HadCRUT4, and gets a temp rise that is higher than either UAH or HadCRUT4.
Oh really?!???
“It’s really funny how the ‘missing heat’ always goes into locations where we don’t have thermometers.” (Jimbo at 11:17am today)
Yup. Aaaaand that, boys and girls, is why Santa Claus lives at the North Pole.
Steig’s paper has been discredited and not just by O’Donnell [2010]. Please see my comments here, here and here. The powerpoint referenced in the second link is here. It is interesting that there is a newer paper than Steig’s (Bromwich, D. H., et al. [2012]), Tropospheric clouds in Antarctica, Rev. Geophys., 50, RG1004,
doi:10.1029/2011RG000363.) that references Comiso 2000 (discussed in my second link) that states:
Bromwich references over 200 papers but does not mention Steig [2009], even though Steig [2009] pretended to “correct” Comiso [2000]’s slight cooling trend in Antarctica to a slight warming warming trend, as explained in my referenced comments.
However, perhaps a better point to be made is a qoute from Comiso [2000] that I made in my third linked comment:
It would seem that determination of Arctic temperatures from satellite infrared data would have similar problems to those shown for Antarctica. From Minnis, P., et al. (2003) Distribution and validation of cloud cover derived from AVHRR data over the Arctic Ocean during the SHEBA year. In Proceedings of the 13th Atmospheric Radiation Measurement Science Team Meeting, Ed. by D. Carrothers, Richland, WA: Department of Energy.:
Cloudiness is significant in the Arctic (also from Minnis [2003]:
When individual temperature values have such large uncertainty, it is difficult to believe that claiming statistical miracles via the Central Limit Theorem or anything else can justify quoting trends in thousands of degrees C.
“You can’t interpolate rising temps from something that isn’t rising.” (David Hoffer at 3:27pm today)
Apparently, it’s worse than that (See: Rob Dawg at Rob Dawg says: November 14, 2013 at 10:11 am
“reconstructing the unobserved regions” … .”)
You can’t interpolate (or whatever their “method” actually is — it makes zero difference) from NOTHING.
Bob Tisdale should be the one to post about this aspect, but, since he’s apparently out on the lecture circuit 😉 — FWIW:
This stupid paper (given that it reveals ANY truth) does at least indicate that the IPCC models which projected Arctic cooling are even WORSE than we already knew that they were ……….which isn’t saying much …………………. which makes this paper just a piece of junk.
As someone above aptly said: THEY ARE JUST MAKING IT UP AS THEY GO. Pitiful.
*************************
(some emphasis mine)
**To answer the argument that Tisdale doesn’t use ALL the IPCC models in his analysis:
(Source: Climate Models Fail, Bob Tisdale, Chapter 5 at pp. 180-84 (esp. Figures 5-22 and 5-26); See also Ibid, Chapter 2.8 Polar Amplification)
Oh, bother!
Re: the faux-poetry line breaks above….. (head shake) — I apologize. It’s happened to me before when copying from a pdf file into this comment box (on WUWT). I don’t know how to prevent it (because JUST LIKE GLOBAL CLIMATE I don’t know what causes it to happen the way it does, lol).
Above “SPECIAL NOTE” quote from Climate Models Fail is at p. 157.
GREAT POST at 6:58pm, Phil (the good one, NOT “The Dot”).
#(:)) Very helpful information. Thanks.
If we look at when the Arctic ocean is warming, the step up points are all during increasingly negative North Atlantic Oscillation episodes, which means that the Arctic ocean warming is a response to a cooling signal, typically during episodes of lower solar plasma speeds. Naturally with a warming signal we would expect more positive NAO conditions and a cooler Arctic.
UAH lower troposphere north pole ocean: http://snag.gy/6Aths.jpg
NAO: http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.timeseries.gif
I almost forgot! THANK YOU, ANTHONY, for all the great education above. Your time and effort putting that tutorial together is much appreciated.
There is some surface temperature data from northern latitudes, from DMI. IIRC, this is the Danish Meterorological Institute. This indicates surface temperatures north of 80 degrees north duriing their warmest couple months of the year being impressively regulated to close to the melting point of ice. Infilling or use of satallelite data available for 80-85 degrees north would indicate more warming trend than actually exists at the surface in the 80-degrees-plus north area.
Another (or related) infilling issue, which I have seen in GISS, is temperature measurement loactions in the Arctic having more snow / ice cover variability (and thus greater local surface albedo positive feedback) than areas that these locations represent, or areas that these locations are used to infill.
My favorite surface index is HadCRUT3, due to better correlation with both UAH and RSS than the other surface indices, including HadCRUT4.
Meanwhile, if one smooths UAH, RSS, or HadCRUT3 by a few years and plots a graph, it gets easy to see that the hiatus of global warming started in late 2011 – 12 years ago. 17 years requires cherrypicking to include a century-class El Nino in the beginning part of the time period under consideration. However, I give fair chance that global temperature will continue to largely flatline for another 20 years, and increase in the ~2035-2070 period at a rate little worse than that of from the early 1970s to ~2004-2005, and increase at a much slower rate after that. I base this on the periodic component that shows up in HadCRUT3.
[“Meanwhile, if one smooths UAH, RSS, or HadCRUT3 by a few years and plots a graph, it gets easy to see that the hiatus of global warming started in late 2011 – 12 years ago. ” Rather: “2001, 12 years ago?” Mod]
No, please, Steven. We are not worthy.
The abstract of the paper states that “The methods are validated on the basis of their skill at reconstructing omitted sets of observations.”
Surely this is the most important point? Remember everyone, a hypothesis is true or false based upon evidence alone, not whether it conforms to our pre-conceived beliefs one way or another. Has anyone with access to the entire paper looked at the validation methods used? How robust are they?
Steven Mosher says:
“That pattern says warming trend increases with latitude.”
Two questions.
Why?
and
If true, why does he suppose that the trend continues beyond the latitudes that are measured? The infamous Gaussian or Normal curve is only one example of an increasing trend that levels off as it nears a peak.
davidmhoffer says:
November 14, 2013 at 1:35 pm
Ian W;
I hate to burst your bubble, but ghg theory has little to do with heat capacity or heat at all. We get very sloppy with terminology in this debate. The relationship is to energy flux and temperature. That’s why I said “energy balance” above rather than heat, but I am one of the ones guilty of sometimes using “heat” when that is the wrong term. Per your comment, water vapour does absorb but it also re-radiates, and this changes the mean radiating level and the temperature profile from surface to TOA as a consequence. Here is a pretty good explanatio:
http://wattsupwiththat.com/2011/03/10/visualizing-the-greenhouse-effect-emission-spectra/
Water vapor possibly does radiate according to its emissivity and temperature. However, water vapor also raises the enthalpy (specific heat) of the air meaning that more heat is required to raise the temperature of a volume of humid air than dry air. Which is what is being discussed, ‘trapping’ outgoing longwave radiation which water does, unlike CO2.
http://www.engineeringtoolbox.com/enthalpy-moist-air-d_683.html
It would really be useful for people to use the correct metrics. Temperature is the wrong metric for atmospheric heat content it should be kilojoules per kilogram then comparisons would be correct. Averaging temperatures of different atmospheric volumes with different enthalpies is nonsense.
Agreed. I have not yet, I hope to find some time to this weekend. For those interested, their methods are apparently discussed here:
http://www-users.york.ac.uk/~kdc3/papers/coverage2013/methods.html
Seems like an application of http://en.m.wikipedia.org/wiki/Simpson's_paradox
And/ or picking your statistics just right to counterdict known data that shows no trend. It’s a well known error in statistics and I would be very surprised that interpolating based on no trend produces a trend is not subject to some simple mistakr
Judiths rebuttal begins:
“First, Kriging. Kriging across land/ocean/sea ice boundaries makes no physical sense. ”
While this is true, that is not how the technique was applied.
They used kriging to estimate the surface temperature from the satelliite data which measures the troposphere temperature, not between surface temperatures.
Do sceptics blindly accept what they are told, or do they question it on principle?
I’m still waiting for Mosher to explain to me how stupid I am.
I’ve been waiting for years for ANYONE from the “let’s trend the temperature data” crowd to even TRY and mount a counter argument to my point that averaging temperature as a proxy for energy balance is a fool’s errand. Every physicist I’ve ever discussed this with agrees, with the possible exception of Joel Shore who admits the problem but maintains that the metric is still useful.
Use these methods on any equal amount of time in the last 12,000 years. Do the results provide an accurate forecast?
Now the door is open to adjust the 1980s downward because the cold polar amplification made that period to hot! Wait for it in AR6.
BogusSophist says:
November 15, 2013 at 7:20 am
“Do sceptics blindly accept what they are told, or do they question it on principle?”
My Null hypothesis is that warmists are corrupt.
Cui bono.
The combined available Arctic stations are no different in recent years than during the 1930’s and 1940’s.
http://imagizer.imageshack.us/v2/564x475q90/141/arctictempstrend.png
GISS recent data already takes the infilling into account and yet the difference between this and RSS is huge to warm only above 82.5N and keep the data sets the same average temperature.
http://imagizer.imageshack.us/v2/564x284q90/829/gissvrssextarc.png
Can any one see the Arctic above 82.5N being up to 100c higher than what the RSS should show?
This suggests the infilling of data is an artefact of the GISS data set and is there because it not scientifically possible to support the difference between the two demonstrated here. Hence, the huge temperature difference demonstrates the infilling data is the incorrect procedure. It conclusively doesn’t support the north pole is the only difference between the two data sets GISS and RSS.
I must admit to some bias in the area of interpolation. In my experience as a garden variety physicist, interpolation has been a very useful tool for retrieving or visualizing intermediate values in a computationally efficient way when the underlying dynamics being considered are well understood, with benchmarking experiments sufficiently dense throughout the range being interpolated. Using interpolation as a basis to modify one’s understanding of underlying dynamics just seems backwards to me.
The techniques used by this paper seem to me more like extrapolation than interpolation. Extrapolation has been useful to check the implications of a proposed understanding of underlying dynamics and to suggest potential measurements to confirm the extrapolation of the dynamics. For example, the original postulates of the existence of black holes were extrapolations of a dynamical understanding (i.e. a solution of Einstein’s equations) of general relativity in the case of a spherically symmetric empty space with a single source of gravity (Schwarzshild) or a similar solution with rotational symmetry (Kerr). In these cases the solutions could be extrapolated to devise observations to determine if the solutions seemed to be realized in nature. Another example would be Dirac’s postulate of the existence of a positron by extrapolating solutions he obtained for his proposed Dirac equation.
Examples of unproductive (perhaps better described as counterproductive) attempts to extrapolate might be the epicentric view of planetary motions about a central earth as described by extrapolations of circles. This particular case produced one of the early “deniers” to suffer for believing his eyes, namely Galileo, who has only recently been de-excommunicated. Other examples are Lamarckian evolution and Balmer’s (1885) discovery of extrapolation of some spectral lines by numerological constructions of series. Balmer’s case is particularly interesting (perhaps relevant) in that when he learned that some experiments seemed to violate his formulas, he doubted the observations and not his formula.
So, in short, the application of “interpolation” in this particular paper seems to me more along the lines of past errors in extrapolation. It seems it would have been much easier and less trouble to simply say we need more and better measurements where we don’t have them now.
Balmer’s case raises another interesting issue, namely the notion of “credentialed climate scientist.” Balmer taught mathematics at a high school for girls and would not be considered, in today’s parlance, a “credentialed physical scientist.” Besides WUWT, I must admit I fairly regularly visit SKS, the Guardian environmental pages, Mother Jones, etc. to obtain information. The proponents of CAGW seem particularly intense about who is and who is not a “credentialed climate scientist.” For example Dr. Soon is described as “someone without credentials in climate science,” Dr. Matt Ridley excoriated in terms of “since when is zoologist Mat Ridley an expert on climate science?” Dr. Tim Ball is dismissed as a “mere geographer, not a climatologist.” Dr. Tol is dismissed as a “mere economist,” apparently not understanding the difference between econometrics and economics, etc. (Please forgive me for quoting the examples, but it is useful for the following contrast.) The classification of “credentialed climate scientist” seems to be reserved for scientists who advocate CAGW. (BTW, the list of contributors to the IPCC contain many economists, geographers, etc.) So, I looked for the “climate science credentials” for Drs. Cowtan and Gray. Doing a quick GoogleScholar one finds Prof. Cowtan is an accomplished and prolific worker in chemistry, particularly molecular imaging, crystallography, and related data analysis, image reconstruction and feature recognition, with many publications in those fields. This appears to be his first in “climate science,” but I may be wrong about that. It was harder to track down Mr. Way. It turns out he is a PhD candidate in geography at U. Ottowa, where geography is housed in the Faculty of Arts not Science. This appears to be his first publication, but again, I may be wrong. By no means do I mean to denigrate either chemists (I have worked with many and enjoy doing so immensely) nor geographers, or even PhD candidates; candidacy can be a wonderful experience.
Not being a climate scientist myself, I must admit to wondering from time to time what “credentialed climate scientist” means. It seems to me that Drs. Soon, Ridley, Ball, Tol, etc. possess as much scientific credential to warrant serious consideration of analysis they present as Prof. Cowtan and Mr. Way. What I do mean to point out is the remarkable asymmetry in notions of “credentialed climate scientist.”
In a perfect world, interested and talented parties could gather somewhere (the moon strikes me as a good place), have guaranteed research funding support, for a time forswear economic gain or attribution and accolades, and work on nothing but understanding the physical future of the earth. A specific goal would probably help. The Manhattan project comes to mind. Unfortunately, we seem stuck in a morass of agendas masquerading as science, and the science appears to be suffering for it.