UPDATE: 8/18 10:30AM I spoke with Dr. Judith Curry by telephone today, and she graciously offered the link to the full paper here, and has added this graphic to help clarify the discussion. I have reformatted it to fit this presentation format (side by side rather than top-bottom) While this is a controversial issue, I ask you please treat Dr. Curry with respect in discussions since she is bending over backwards to be accommodating. – Anthony
===========================================================
[Update] My thanks to Dr. Curry for showing the graphic above, as well as for her comment below and her general honesty and willingness to engage on these and other issues. She should be a role model for AGW supporters. I agree totally with Anthony’s call for respect and politeness in our dealings with her (as well as with all other honest scientists who are brave enough to debate their ideas in the blogosphere). I also commend the other author of the study, Jiping Liu, for his comments below.
However, as my Figure 2 below clearly shows, any analysis of the HadISST data going back to 1950 is meaningless for the higher Southern latitudes. The HadISST data before about 1980 is nonexistent or badly corrupted for all latitude bands from 40°S to 70°S. As a result, although the HAdISST graphic above looks authoritative, it is just a pretty picture. There are five decades in the study (1950-1999). The first three of the decades contain badly corrupted or nonexistent data. You can’t make claims about overall trends and present authoritative looking graphics when the first three-fifths of your data is missing or useless. – willis
===========================================================
Guest Post by Willis Eschenbach
Anthony has posted here on a new paper co-authored by Judith Curry of Georgia Tech, entitled “Accelerated warming of the Southern Ocean and its impacts on the hydrological cycle and sea ice”. The Georgia Tech press release is here. Having obtained the paper courtesy of my undersea conduit (h/t to WS once again), I can now comment on the study. My first comment is, “show us the data”. Instead of data, here’s what they start with:
Kinda looks like temperature data, doesn’t it? But it is not. It is the first Empirical Orthogonal Function of the temperature data … the original caption from the paper says:
Figure 1. Spatial patterns of the first EOF mode of the area-weighted annual mean SST south of 40 °S. Observations: (A) HadISST and (B) ERSST for the period 1950–1999. Simulations of CCSM3 (Left) and GFDL-CM2.1 (Right): (C, D) 50-year PIcntrl experiment (natural forcing only),
Given the title of “Accelerated warming”, one would be forgiven for assuming that (A) represents an actual measurement of a warming Southern Ocean. I mean, most of (A) is in colors of pink, orange, or red. What’s not to like?
When I look at something like this, I first look at the data itself. Not the first EOF. The data. The paper says they are using the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) data. Here’s what that data looks like, by 5° latitude band:
Figure 2. HadISST temperature record for the Southern Ocean, by 5° latitude band. Data Source.
My first conclusion after looking at that data is that it is mostly useless prior to about 1978. Before that, the data simply doesn’t exist in much of the Southern Ocean, it has just been shown as a single representative value.
So if I had been a referee on the paper my first question would be, why do the authors think that any analysis based on that HadISST data from 1950 to 1999 has any meaning at all?
Next, where is the advertised “Accelerated warming of the Southern Ocean”? If we look at the period from 1978 onwards (the only time period with reasonable data over the entire Southern Ocean), there is a slight cooling trend nearest Antarctica, and no trend in the rest of the Southern Ocean. In other words, no warming, accelerated or otherwise.
Finally, I haven’t even touched on the other part of the equation, the precipitation. If you think temperature data is lacking over the Southern Ocean, precipitation data is much worse. The various satellite products (TRMM, SSM/i, GPCC) give widely varying numbers for precipitation in that region, with no significant correlation between any pair (maximum pairwise r^2 is 0.06).
My conclusion? There is nowhere near enough Southern Ocean data on either side of the temperature/precipitation equation to draw any conclusions. In particular, we can say nothing about the period pre-1978, and various precipitation datasets are very contradictory after 1978. Garbage in, you know what comes out …
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
oeman50 says:
August 18, 2010 at 11:34 am
I can understand the effect of snow on the albedo of ice, but that is not the issue. It is the effect of warmer water sea ice is floating on. I have looked up the thermal conductivity of pure water (0.561 W/mK) and of seawater (0.563 W/mK). This small difference in no way makes fresh water an “insulator” from sea water or makes it easier to cool, in fact it appears to be the opposite.
—————
Conduction is slow – convection is more important. The density gradient introduced by the freshwater stabilises the water column and reduces convection.
Pamela Gray, I am with you 100% on the need to better understand the natural oscillations. Jiping Liu and I have written several papers on natural variability in the Arctic and Antarctic, see below:
Liu, J.P., J.A. Curry, Y.J. Dai, et al., 2007: Causes of the northern high-latitude land surface winter climate change. Geophys. Res. Lett., 34 (14): Art. No. L14702.
http://curry.eas.gatech.edu/currydoc/Liu_GRT34.pdf
Liu, J.P., J.A. Curry and Y.Y. Hu, 2004: Recent Arctic sea ice variability: connections to the Arctic Oscillation and the ENSO. Geophys. Res. Lett., 31, L09211.
http://curry.eas.gatech.edu/currydoc/Liu_GRL31A.pdf
Liu, J.P., J.A. Curry, and D.G. Martinson, 2004: Interpretation of recent Antarctic sea ice variability. Geophys. Res. Lett., 31, Art. No. L02205.
http://curry.eas.gatech.edu/currydoc/Liu_GRL31.pdf
The rationale for considering “what if” scenarios of future climates is to test our understanding of these processes in a different parameter space. The climate model scenarios are “what if” scenarios of the future, they are possible scenarios of a future world. I have stated many times all over the blogosphere that climate models do not have any predictive capability on decade to century time scales. Such predictive capability would require knowledge of future natural and human forcing (which we don’t have), not to mention much better climate models. Nevertheless, the models are useful tools for trying to understand how the climate system works.
With regards to data quality in the Southern Ocean. There is very little before 1950, which is why we did not attempt to discuss the period prior to 1950. During the satellite era, the data is relatively good, although there are still problems. Data during the 1950’s and 1960’s is relatively sparse. There are several efforts underway to get more ship data (which exists in the form of handwritten logs) into the climate data bases. Jiping Liu is working with Chinese scientists to get Chinese ship data into the archives. So I think there is hope for improving the data situation in the near future, but the Southern Ocean is definitely a data sparse region.
You can’t make claims and present authoritative looking graphics when the first three-fifths of your data is missing or useless. – willis
Sure you can, just like ummm, (self snip) the Benedict Arnold’s: Senator John Kerry (Mass), Senator Joseph Lieberman (CT), Senator Bernie Sanders (VT) presentations discussing the issue of asthma rates in the NE. Missing data for the claim, they sound just like the EPA. They fail to mention that two thirds of the volcanoes on this planet are in the northern hemisphere.
http://www.epa.gov/NE/asthma/index.html
Asthma is a chronic condition in which the narrowing of the bronchial tubes in the lungs leads to wheezing and difficulty breathing. Environmental factors – such as mold, mildew, pet dander, environmental tobacco smoke, cockroaches, dust mites, vehicle exhaust and industrial and power plant emissions – can exacerbate asthma symptoms.
But what about living in the ash fallout zone of the most active volcanic regions of planet Earth? No data on ash fall in New England?
http://www.volcano.si.edu/world/find_regions.cfm
Iceland and Arctic Ocean
Kamchatka and Mainland Asia
Kuril Islands
Alaska
But New Englander’s can produce volcanic studies of climate effect, but no link to asthma?
THE EXPLOSIVE VOLCANIC ERUPTION SIGNAL IN NORTHERN HEMISPHERE …
http://www.geo.umass.edu/faculty/bradley/bradley1988.pdf
The state of climate science is now so predictible, this must be what I would imagine doing time feels like.
The 1940 period is very interesting. Globally there is a bump in surface temperatures that peaks in 1940 (land and oceans, both hemispheres). There have been attempts to explain this away by aerosol forcing, which is mostly a bogus argument IMO, particularly for the southern hemisphere. If you want to read more about challenges associated with the sea surface temperature data sets, read this summary by Rayner et al. https://abstracts.congrex.com/scripts/jmevent/abstracts/FCXNL-09A02a-1662927-1-Rayneretal_OceanObs09_draft4.pdf
Anyone willing to help me understand this????
Thanks in advance.
David says:
August 18, 2010 at 11:19 am
I still do not get the warming. The HadISST graphic Willis shows covering Southern ocean laditudes show a peak or near peak SST for all laditudes (except one) around 1985. Since then ALL laditudes show a decline. Am I incorrect in seeing this?????
Also Why did the study apparently only use data to 1999? “Jiping Liu says:
“We performed the EOF analysis on the area-weighted annual-mean observed SST south of 40 °S for 1950–1999.”
I just want to echo the sentiment that we should be polite and respectful to Drs. Curry and Liu. Some of us might have reservations about this paper, but there’s no reason why we can’t be civilised about it.
Oh, and I’d still love to know, like Lucy Skywalker, what “EOF” means. I’ll bet we aren’t the only ones, and not knowing that may well be impeding the best quality discussion here. So TIA to anyone who can put me out of my misery! 🙂
From a newspaper article in 1933…
Ice in the Weddell Sea. TABULAR icebergs of 20 miles or more in length have been noted from time to time by various antarctic expeditions, but in recent years their number seems to have increased in the Weddell Sea and the South Atlantic, especially the Scotia Sea. In an article in the “Geographical Journal” for May Mr. J. M. Wordie and Dr. Stanley Kemp discuss recent records of these bergs and their significance.
Messrs. Wordie and Kemp suggest that these bergs come from that coast, and indicate extensive changes in that region and the loss of thousands of square miles of barrier ice. These changes may have considerably improved the chances of penetrating that unknown quarter.
Complete article at http://newspapers.nla.gov.au/ndp/del/article/23271006
Empirical Orthogonal Functions
In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data. It is the same as performing a principal components analysis on the data, except that the EOF method finds both time series and spatial patterns. The term is also interchangeable with the geographically weighted PCAs in geophysics.
see: http://en.wikipedia.org/wiki/Empirical_orthogonal_functions
That was just before the update appeared. Wow, this completely changes my take. Plus several more sound comments, esp. George E Smith, Bob Tisdale, Cassandra King, PaulM.
This fast update in response to valid criticism, and apology, is what I love at WUWT, and its absence is what I
detestmiss at RC etc.The EOF mode identifies regions that are closely related and with strong gradient (spatial variability), and the PC indicates the amplitude of EOF as it varies through
time (temporal variability). More detailed information can be found at andvari.vedur.is/~folk/halldor/PICKUP/eof.ps.gz
The Article discussing icebergs in the Weddell Sea is:
Observations on Certain Antarctic Icebergs J. M. Wordie and Stanley Kemp
The Geographical Journal, Vol. 81, No. 5 (May, 1933), pp. 428-434
Paper concludes “If, as we conclude, these large bergs have their origin west of the Filchner barrier, the geographical change staking place in that region must be of exceptional extent and importance. In the aggregate thousands of square miles of barrier have been removed and, the recession of the ice edge must be extremely rapid. “
BarryW says:
August 18, 2010 at 11:02 am
Anthony/moderators!
I think you should consider some major snipping. Dr Curry has been courteous to those who frequent your blog and the snarkyness and name calling is inappropriate. Even the use of the term garbage WRT the data is bad form. What do people think this is: Real Climate?
REPLY: I agree, and unfortunately there have been some whom have spoiled the debate here and I have not been able to moderate as much as I’d like due to other obligations. And, unfortunately it is a catch22 post facto, going forward however, I will aggressively remove such comments or portions thereof, from both sides, that don’t advance the discussion in a courteous way. – Anthony
____________________
There is great irony in this exchange. Major snipping would, in fact, make this exchange MORE like Real Climate. What, do we have to be reverential if a real climate science might be listening in? It’s high time the academics who have fostered the CAGW came forward and defended their work in the trenches. Most of us are eager to learn, eager even to be taught. But that requires a transparent and free exchange of ideas. It’s the allowance of divergent points of view that make this blog worthwhile. Take that allowance away and you have nothing.
Oddly, the only comment that seems close to inflammatory that I’ve seen on this thread is the title. It infers rather warmly that Dr. Curry cooked the books. Anything said after that has to be seen in the context of that. But even that is a worthwhile point of view and I’m sure Willis and everyone else is willing to accept persuasive alternative explanations.
I should add that for the colour challenged (8% of males) that all those coloured figures and charts are meaningless. They are plague among us.
Also for my part I’m wondering if the M&W2010 statistical analysis is applicable here, since the data points are so sparse is it not possible that nothing can really be made of them? And has a proper statistical testing been done to rule out that possibility?
I wish there was a simple way to explain EOFs (empirical orthogonal functions). Here are some links, and if somebody has an intuitive way to explain this, please pipe in!
Wikipedia http://en.wikipedia.org/wiki/Empirical_orthogonal_functions
ppt from iges ftp://www.iges.org/pub/straus/CLIM_753/EOF.pdf
Notes from Eugenia Kalnay at U. MD http://www.atmos.umd.edu/~ekalnay/notes3.pdf
Notes from David Randall at Colo. State Univ
http://kiwi.atmos.colostate.edu/group/dave/pdf/EOFs.pdf
With regards to the moderation, this thread is fine, it is the comments on the previous thread (Paradox of Antarctic Sea Ice) that were inappropriate. Thanks to Anthony for addressing the situation, particularly the latter half of this thread is good.
David, we chose 1999 as the end date because that is the end date of the 20th century climate model simulations. Again, the main point of this paper was not so much to document the temperature trend, but rather interpret the behavior of the sea ice in the context of surface temperatures, precipitation, and evaporation.
“”” Malaga View says:
August 18, 2010 at 12:52 pm
Empirical Orthogonal Functions
In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data. It is the same as performing a principal components analysis on the data, except that the EOF method finds both time series and spatial patterns. The term is also interchangeable with the geographically weighted PCAs in geophysics. “””
Izzat a ten sill-abble word for Fourier Analysis; or its equivalent. I’m fully aware of the procedure of representing some continuous function as a sum of orthogonal or ortho-normal functions; such as Sinusoids or Legendre Polynomials; Bessel Functions and the like. Is that basically what you are referring to or is this EOF something different.
It seems obvious to me that a function of multiple variables such as time and space (how about the global temperature map) can be represented by a “spectrum” of “frequencies” in each of those variables. And of course the theory of Sampled Data Systems, requires specific rules be followed to represent such continuous functions properly by a series of discrete samples ; specifically the Nyquist Criterion.
But other than these considerations; what is it that EOF has to offer; if anything. I dunno; which is why I am asking ?
George
I don’t pretend to understand the science and models but this this makes sense to me:
—
Judith Curry says:
August 18, 2010 at 12:16 pm
Nevertheless, the models are useful tools for trying to understand how the climate system works.
—-
I think that this is a good position for all climate scientists to take. Dr Curry has risen in my estimation for this single statement.
Willis, Judith, Jiping – thanks for having the courage to hold an honest, real world related “warts and all” discussion on a public blog. IMO progress comes from such things! 🙂
Dr Curry,
I don’t quite get the “empirical” part of your EOF, although I am quite familiar with the expansion of arbitrary continuous functions in terms of Orthogonal or ortho-normal functions as I just penned above. The “empirical” part throws me though.
Can you say more specifically what sort of Orthogonal functions you use for this representation; and possibly why that specific choice ?
George
Too many assumptions, along with the use of poor quality data and the fiction of computer climate models, make this paper less than convincing.
Nothing new about recent temperatures seen in the Antarctica either, as can be seen from the graph here:-
http://a.imageshack.us/img807/8771/jones7990n.jpg
As with climate everywhere, temperature in the Antarctic oscillates up and down over the years, and was doing so long before mankind started burning significant quantities of coal and oil.
Jiping Liu says:
August 18, 2010 at 12:57 pm
“The EOF mode identifies regions that are closely related and with strong gradient (spatial variability), and the PC indicates the amplitude of EOF as it varies through time (temporal variability).”
Thank you for taking the time to explain, Dr. Liu. However, and this isn’t your fault, that doesn’t quite do it for me because I lack the mathematical/statistical awareness to *fully* understand it.
Over the past months, I have learnt a great deal at WUWT and am continually striving to learn more. I’m gradually getting the confidence to ask what are probably naive questions, the answers to which are something I can then build on.
So – can anyone put this in layman’s language? Maybe an analogy, even? Once I get that, I may be able to map it to, and absorb for future reference, the meaning of the terminology.
The central point of Willis’ that comes across, regardless of my lack of understanding of some of the finer points, is that the paucity of data over much of the period of study renders its conclusions unwarranted. I’m quite prepared to accept to the contrary if evidence is produced that that is not the case. I look forward to convivial discussion.
I have read the paper and I have some problems:
The paper states:
“As shown in Fig. 4b, SST under sea ice in the 2090s is a few tenths degree warmer than that in the 2000s,”
Most of the sea ice lies at >65 degrees S lat. According to Willis’s graph of actual temperatures, this area is at -1 to 0dC. Looking at figure 4b, it does not seem that a “few tenths” translates into “enough tenths to put us above freezing.”
Also, according to NOAA: “Multi-year ice is less common in the Antarctic than the Arctic, and is usually confined to the western Weddell Sea and isolated embayments at other locations around the coast. Ocean currents and the atmospheric circulation result in a net divergence of sea ice around the continent, causing most of the ice to melt in the summer as it drifts into warmer waters, or as the upper ocean heats up as the open water areas within the pack absorb solar radiation…
The ablation season of Antarctic sea ice is rarely associated with the presence of melt water on the surface of the ice.”
So an increase in rainy precipitation is going to have very little effect on the sea ice, since there won’t be much sea ice. The average summer temperature in Antarctica is -6dC. Even on the balmy Peninsula, the temp is around 2dC in the summer. So, there will have to be quite a bit of warming to bring rain past the coastline. It will still be cold enough during the winter for the precipitation to fall as snow (that whole absent-sun-thing). So there will be plenty of snow insulation in the ice-growth season.
The increase in Antarctic sea ice is occuring during the SH winter. There is very little change in the sea ice extent during the melt season. see: http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.area.antarctic.png
In fact, if you look at only the last two years, minimum extent does not seem to predict maximum extent.
I also have a big problem with the snow-insulating-water idea. Unless this just got mangled in the press release. The sea ice forms from freezing sea water, not congealed snow. In the summer, it is melting ice that cools the water. Snow is not nearly dense enough to come close to the heat transfer of ice. Even rain falling in those latitudes would be PRETTY COLD WATER. And, since rain drops are also more dense than snow, I’m guessing there wouldn’t be much difference in the effect on SST.
Coalsoffire says:
August 18, 2010 at 1:13 pm
Hopefully much of the ad hom ect. have been snipped already (I know you have a full plate already, Anthony). That is what I was complaining about. Critiquing the paper is what this entry should be about and I hope this exchange is useful to Drs. Curry and Lui and I appreciate their time here. It has been interesting to read whether or not I wind up agreeing with them. Exchange of ideas is what Real Climate does not seem to be about, and I hope people see that piling on is not useful, though we’re all guilty of it a one time or another (myself included).
Bill Tuttle
1 how can one *reasonably* claim to get a ± 0.06°C accuracy from an instrument (a water-temperature gauge in a ship’s boiler intake line) that can only be read to the nearest .5°C and may have an instrument error of another whole degree C,
assuming the errors are randomly distributed (which is reasonable for the problems you posit) they will balance out with more measurements and the more measurements you use the less likely the error of any individual measurement has to distort the cumulative value. a fair coin has a 100% “error rate” when tossed once (will only get within 50% of the actual random distribution of heads-tails in coin-tosses of a fair coin and will never produce that distribution on a single toss), however a trial of 10 coin flips has an “error rate” of about 15%, flip the coin a million times and the variation from the 50% heads-tails ratio is so small as to be not worth worryiong about – the coin none-the-less has a 100% error rate on one toss. this does require that the errors be randomly distributed, but that is a reasonable assumption in the case of thermometers. whether or not you can actually get a ± 0.06°C accuracy from the measurements in this paper is a different issue ( i have difficulty accepting that claim although not worth my time to test it), but trials using measurements with randomly distributed errors have smaller errors as more and more of measurements accumulate.