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 …
A note of thanks to Just Tex for the kind and supportive words which were simply a direct reflection of the thoughts and experiences of many posters on this thread and this funnily enough highlights yet another wonderful aspect of WUWT, the illumination of thoughts and ideas and the transmission of those thoughts and ideas to a wide and varied community.
The human mind ingests and correlates information as an individual entity but rarely and interestingly a medium appears that seems to bring people together in a shared learning experience, a sense of identification in a shared quest if you will.
I see it as a meme crossroads or nexus if you will, an intersection of peoples thoughts stimulated by a subject matter that is of great interest and fed by the drought of real genuine information out there in the traditional media. We have suffered a drought of the knowledge we crave for so long that now we find a genuine stream of information and dialogue we may quench our thirst, its only to be expected therefore that a little excitement is in order?
May I second the description of Judith Curry as courageous and brave, whatever I may think of her current work, my admiration of her actions here is very high indeed.
Brian H bespoke:
“If the numbers were large, you’d have a case. But they are few, and biased-selected, and just generally low quality. FAIL.”
My response to Mr. Delbeke did not concern the amount of available Southern Ocean data. My response addressed the general questions of precision and accuracy and how large numbers of measurements tend toward the true mean, even despite large uncertainty in individual measurements.
Had you read the thread and figured out for yourself how this issue arose, you probably could have figured this out for yourself!
Brian Eglinton says:
August 18, 2010 at 7:58 pm
Well said.
It is, as you say, the use politics makes of the scientific result that introduces gross distortions on the value placed by scientists themselves. But also there exists a positive feedback: if the politicians like the exaggerations, they feed the scientists producing them with money, the ego of the young and not so young scientists is inflated, and they start to believe in their speculations.
That is why I periodically harp that decisions on the financing of research should be left to the individual institutes. They should be given a lump sum of money, preferably on a five year plan, according to their number of academics and statistics in publications, and the institute themselves should decide how to distribute it to the individual scientists. This was the usual way up to some decades ago, and it would again introduce a buffer between politics and academe, allowing different schools of research to flourish competitively.
Judith Curry says:
August 18, 2010 at 5:29 pm
Judith, I get this a lot when I point out problems with a GISS land temperature dataset. People say “look at the method”, as if somehow that explained everything. But the method used to get a wrong answer doesn’t matter. Again I urge you to contemplate what the HadISST dataset says about the region around Antarctica, say the bottom three lines as shown in Figure 2. If you find that to be “robust for the period since 1950”, I fear we may be talking at cross purposes. There is no data 1950-1980, just a straight line with a huge drop at the end of the 70’s. That is not “robust” on my planet.
Nor is this a question of “detailed accuracy of the observed surface temperatures.” We’re talking about missing data, not how accurate the data is. You don’t seem to understand the implications of the fact that for much of the period since 1950, the HadISST just contains a straight line, with no change year after year. That’s not a problem of “detailed accuracy”. That’s a problem of missing data.
Again I say it is not a question of “greater uncertainty”. It is no certainty at all, because there is no data. This means that the hypothesis rests on the shoulders of two models which have been chosen, not on ex-ante criteria, but because they kinda sorta look like the observations.
But the observations are built on false data, so the choice of models becomes flawed as well …
It seems to me (and please correct me if I’m wrong) that your idea is that the Southern Ocean is undergoing “accelerated warming” leading to a “paradox” of increasing Antarctic sea ice with a warming ocean. Your hypothesis, involving precipitation, is designed to explain that supposed paradox.
But in fact, both the Southern Ocean air and the sea are cooling, with the cooling increasing southwards towards Antarctica.
What does that do to your hypothesis and your paradox? My understanding of the scientific process says that in this case, it’s more than a minor reduction of support. It seems to my understanding of science that since the Southern Ocean sea and the air are cooling, increasing sea ice is no paradox at all, so your hypothesis is explaining a problem that doesn’t exist …
Thank you for your perseverance in this,
w.
boballab says:
August 18, 2010 at 8:20 pm
Many thanks, boballab, that’s what I was looking for.
For those that want to take a look at just how much data there is for SST’s, Bob Tisdale put up links on his site to NCAR that shows how muh there is and isn’t. Here is the links to NCAR so you can see for yourself:
http://www.cgd.ucar.edu/cas/guide/Data/coads.sst.f1.html
http://www.cgd.ucar.edu/cas/guide/Data/coads.sst.f2.html
http://www.cgd.ucar.edu/cas/guide/Data/coads.sst.f3.html
According to NCAR for the period 1961-80 there is less then 50% data just south of Australia, Africa and the 2/3rds point (going from north to south) of South America. The closer you get to Antarctica the less there is until basically there is no data. The period 1981-97 is not much better looking at it.
There just isn’t much data to be had for Southern Ocean SST’s.
Oakden Wolf says:
August 18, 2010 at 9:57 pm
Oakden, if Judith had said that their study used the data you reference, then you would have a very valid point.
But they didn’t. They said they used HadISST data. So I am pointing to the very large holes in the HadISST data, the data they actually used … and whatever may or may not be happening with your other data doesn’t affect either their study or my analysis in the slightest.
Where there might have been a little trash-talking going on before, a certain reverential tone has insinuated itself into this thread, that I find equally 0ff-putting.
While it is much to be appreciated that an author will discuss their paper on a (somewhat) hostile blog, it’s noted that it isn’t a one-way street and that that author has their own reasons for electing to do so.
It’s unlikely that we’re going to see a flood of prominent scientists, politicians, etc. following suit. Which blog would they choose? How much time could they really devote to it? There are only so many responses one can make when many are clamouring for attention.
It’s interesting to me what questions actually have been addressed here and in what depth. There were several time-outs for commenting on the comportment of the audience. Was there just a hint of supercilious condescension?
This thread is, above all, a testament to the significance of this blog rather than the stature of the esteemed guest.
Judith Curry says:
August 18, 2010 at 5:29 pm
I agree that the missing data does not falsify the hypothesis, but neither does it prove it.
We are then left with warming models for the Southern Ocean, and no competing models following the cooling to neutral routes.
That leaves shut the way to ruling out or whittling down the forces that are at work.
30 years ago, one would probably find only cooling models, if it were today.
Climate Science may therefore be observed to be cyclic itself.
Ah, the old paradox trick. Hilarious way to get more grants.
Is it also a paradox that it rains in the rain forests? What with global warming was supposed to have turned everything to bone dry dust from all the heat waves.
Oakden Wolf says:
August 18, 2010 at 9:28 pm
Three quick questions for Wayne Delbeke:
What is the “law of large numbers”?
What is the “central limit theorem”?
How is radar satellite altimetry performed to produce accurate values for sea level rise in the millimeter range?
An article on this theme: How can annual average temperatures be so precise?
____________________________________________________
I am sorry, I read the article you referenced (How can annual average temperatures be so precise?) and it is exactly the sort of article that drives engineers like me mad. It uses a statistical analysis to develop a number to several decimal places by repeating it many, many times then doing a calculated result. What about confidence limits? If I test a beam of certain configuration and material one thousand times and the average failure is at 1200.4355 kilograms with the maximum at 2000 kg and the minimum at 800 kg then I will actually use a design weight of 400 kg (safety factor of two). No way would I use the 1200.4355 figure as I clearly could be using a beam that could be over stressed by 50%. Unless I know why some beams failed at the lower number I MUST use the conservative number. I guess it doesn’t matter in climate science. But it sure matters when you drive a semi over a bridge.
As for “the Law of Large Numbers” you don’t have large numbers nor do you have similar conditions in measuring or the material being measured so I would suspect you have very weak correlations. It would kind of like measuring the properties of steel in Kansas versus Inuvik in Winter. Quite different – low temperature steel is required in Inuvik as regular steel shatters in the winter. I don’t think these widely different ocean temperatures are properly correlated … they have hugely different properties.
Central Limit Theorem – since you brought it up – it appears to me that it does not apply to this situation due to the limits that the theorem requires to be valid. I am not a mathematician so I am probably not qualified to comment, but I can read the limitations listed for applying the theorem and I would guess it isn’t applicable.
You can’t make bad data of low precision into good data with high precision by applying mathematical formulae. If the original data is sparse or questionable, the results can be nothing more than conjecture. Reasonable conjecture perhaps, but conjecture non the less. I can build a bridge with reasonable conjecture … but the safety factor must be huge. Unfortunately, in climate science, there appears to be a lot of conjecture and a lack of statement of the possible variances. How hard is it to turn a plus number into a negative number given the accuracy of the data?
I used to write economic forecasts tailored to several hundred individuals doing revenue forecasts using historical performance to predict future performance. There were many instances of creating negative numbers out of positive data. They were pretty simple algorithms that projected revenues and profits out 12 months every three months. Real life determination of accuracy and precision. My company’s survival and return on investment and paying the bank and employees depended on it. I would not like to have had to depend on the paucity of uncorrelated information that this study uses as a basis to predict the survival of my company.
But, again, I am not a mathematician.
And as for the satellites being able to “produce accurate values for sea level rise in the millimeter range” … that is still an open debate.
From the “hockeyschtick” ( and there are many more including some on this site):
“As stated above “Since the difference series at separate time gauge locations have been shown to be nearly statistically independent (Mitchum, 1998), the final drift series has a variance much smaller than any of the individual series that go into it. Because of the relatively large number of degrees of freedom, this method outperforms calibrations from dedicated calibration sites, although it is only a relative calibration, meaning that it cannot determine any absolute bias.” Looking at the individual GPS-corrected tide gauges in the two graphs above compared to the satellite altimetric measurement at the corresponding location shows very large divergences of up to 25mm at a given point in time. Yes, if you sum all the anomalies from the carefully selected subset of tide gauges compared to the satellite records it is statistically insignificant from zero, but the large variances on individual records suggests much more doubt in the accuracy of satellite altimetry and/or GPS-corrected tide gauges than is commonly held. ”
If you read some studies on how satellite data is adjusted (yup – I said adjusted.) you will find that the signal amplitude is up to 300 mm (one foot for US readers) along with satellite drift. The satellites have to be constantly correlated with properly installed physical tide guages and appropriate algorithms applied to CALCULATE (not measure) what sea level amongst all those waves actually might be. Remember what you are measuring. A beam bouncing off a moving undulating surface from a satellite in a varying orbit both laterally and vertically with appropriate allowances for Doppler effect etc. etc. And we accept an accuracy of less than a millimetre? Not me. I worked too long with electronic distance measuring equipment on terra firma using instruments bolted to concrete foundations (which actually move quite a bit) to believe sub-millimetre accuracy from a satellite to a water surface.
(rant off)
JC- Eventually we will have better data sets and better models to work with. That is how science works. ))
There in lies the issue. Can you not see why people find the claims of the Cult to be fraudulent??? At present we are not seeing science being done for anything other than political activism,( & high moral purpose :-(). Until the ‘models’ are 100% accurate, and audited openly, no Government should be making policy decisions based on what looks like pure propaganda.
regards.
(any chance of a pic of your hands???)
WillR says:
August 18, 2010 at 5:57 pm
I think that should be the final word on the debate:
When you say garbage in garbage out, you are not understanding the scientific process. We posed a hypothesis, we tested it using data and model simulations, which support the hypothesis. If the data are bad and the model is wrong, that doesn’t falsify the hypothesis, it reduces the support for the hypothesis. So it doesn’t make any sense to say that our hypothesis is incorrect because there are holes in the sea surface temperature data set.
“I know I can’t think of an answer to that.”
Perhaps by explaining that hypotheses are attempts to explain data, not the other way around.
Wayne Delbeke: August 18, 2010 at 8:52 pm
You can measure something “precisely” to three decimal points, but if the object has high variability, the “precision” is meaningless since it is “inaccurate”.
Your comment accurately described the precise point I was making.
Ummmm — trying to make.
I seem to be still waiting for Dr. Curry’s response concerning my question about her apparent acceptance that the hydrological cycle can vary in speed.
If one extrapolates that capability globally and if one recalls that more convection can arise from more evaporation without a temperature rise and that more evaporation is caused by extra downward IR then one has a mechanism whereby the warming effect of more CO2 can be negated without an observable temperature rise because the extra energy in the system all goes to latent heat.
boballab: August 18, 2010 at 10:32 pm
For those that want to take a look at just how much data there is for SST’s, Bob Tisdale put up links on his site to NCAR that shows how much there is and isn’t.
Bob’s post got me to poking through my copy of HadCRUT3. Section 3.1 gave me what I was looking for:
“The marine data are point measurements from moving ships, moored buoys, and drifting buoys, so the anomalies for any one grid box come in general from a different set of sources each month. This means that marine data have no equivalent of station errors or homogenization adjustments. The marine equivalent of the station errors form part of the measurement and sampling error, and adjustments for inhomogeneities are done by large scale bias corrections.
“A bias correction is applied to remove the effect of these changes on the SSTs. This correction depends on estimates of the mix of measuring methods in use at any one time, and of parameters such as the speed of the ships making the measurements. An uncertainty has been estimated for the correction; again, details are in [Rayner et al., 2006].
“As with the land data, the uncertainty estimates cannot be definitive: where there are known sources of uncertainty, estimates of the size of those uncertainties have been made. There may be additional sources of uncertainty as yet unquantified (see section 6.3).” [My emphases — plural.]
“Estimates,” “uncertainties,” “cannot be definitive,” “may be additional sources of uncertainty.”
So, in addition to a paucity of actual surface temperature measurements in the Southern Ocean, the ones that were made have been adjusted pretty much by “educated guesswork.”
George E. Smith says:
August 18, 2010 at 2:20 pm
“Well let me cast my self adrift on the thin ice (Southern Ocean style) where only fools (like me) don’t fear to tread.
For those non mathematicians who have no idea what Orthogonal Functions are; here’s my stick on a sandy beach explanation.”
Many thanks for this, George. It advances my understanding that little bit further.
Willis Eschenbach says:
August 18, 2010 at 10:20 pm
“What does that do to your hypothesis and your paradox? My understanding of the scientific process says that in this case, it’s more than a minor reduction of support. It seems to my understanding of science that since the Southern Ocean sea and the air are cooling, increasing sea ice is no paradox at all, so your hypothesis is explaining a problem that doesn’t exist …”
Willis, I was struggling in my own mind to articulate what the problem was for me, but your post did so perfectly – far better than I ever could have. The thing is, the very hypothesis itself appears to be moot if not pointless.
I would like to know whether Dr. Curry actually accepts your point that cooling is occurring. If she doesn’t, and has firm evidence for that, fair enough. If not, well, I’m at a loss to see any foundation for this particular study, regardless of the quantity or quality of data available.
Willis: You asked, “What is the source for your ICOADS data and graphs?” with respect to these maps:
http://i37.tinypic.com/t8x4ox.jpg
I created the maps at the KNMI Climate Explorer. Select “1800-2007: 2° COADS SST” as the field on the “Monthly Obsevations” page. On the right-hand side of the page are a number of menus. Under “Investigate this field”, the first option is “Plot this field”. That allows you to make maps and Hovmuller plots. For those maps of the ICOADS data I also shifted the contour levels out of the range of the data variability so that it printed the maps of reading locations with basically only one color.
The reason for this is simple offshore flow. Since the water around Antarctica is usually warmer than the near water land surface, air over the water rises then descends over the land causing wind to blow off shore.
Very correct comment . The data I accumulated during my stay in Antarctic (only summer) completely supports that .
a) The prevailing winds come from the continent
b) the air temperatures at/near shore are always colder (actually subzero) when the winds come from the continent
c) It cannot rain when temperatures are sub zero but it snows instead what is the case most of the time both in winter and in summer .
d) The Antarctic Peninsula , especially its northernmost tip is a very special atypical case . Its temperatures in summer are anomalously high with regard to 99,99% of Antarctic and have always been . Both the absolute values and trends do not represent the Antarctic . Of special note is that the Peninsula is the place which has the highest density of data sources .
Quote, Judith Curry, “What has been noticeably absent so far in the ClimateGate discussion is a public reaffirmation by climate researchers of our basic research values: the rigors of the scientific method (including reproducibility), research integrity and ethics, open minds, and critical thinking. Under no circumstances should we ever sacrifice any of these values”
Circumstance would suggest that this paper is a continuance and re-affirmation of past behaviour thru its invention of data.
Measure our disappointment against the promise to do better.
Summary of some of the ways in which the paper is misleading:
1. Patchiness of data in the post-1950 period is glossed over by the use of EOFs creating a misleading impression of smooth continuous data.
2. Title says accelerated warming. Paper shows decelerating warming.
In fact the HADSST data in the paper (fig2A) and shown in Willis’s graph shows no warming at all since about 1980. (and the post-1980 period is where the data is most reliable).
3. Paper says “warming is reduced poleward”. In fact the warming reduces so much poleward that it becomes cooling!
4. Abstract claims observations show ‘substantial warming’. But they dont – most of the graph is either blue or pink, slight warming or slight cooling.
5. Paper talks of “paradox”. Press release headlines “paradox” of increasing ice in a warming climate, but paper shows cooling near the poles – there is no paradox.
Willis, Bob Tisdale
This is the familiar plot for CET
http://homepage.ntlworld.com/jdrake/Questioning_Climate/_sgg/m2_1.htm
It took approximately 800,000 bits of data to produce a temperature record covering a small part of the UK, which in itself is a miniscule part of the globe.
The accuracy is probably no more than half a degree or so, but fortunately we have numerous written records and observations the data can be checked against.
Land- unlike currents- doesn’t move or vary in thickness, and air temperatures vary much more than sea temperatures. So appreciating we are comparing apples with oranges can anyone give me some idea of just how many bits of actual verifiable data points have gone to make up the study which Willis is examining and how accurately that can depict a vast moving mass of a liquid which isn’t at all well mixed?
Tonyb
1DandyTroll says:
August 18, 2010 at 11:38 pm
Here is another paradox:
Find someone who does not wear sunglasses.
Ask them to describe how bright the sunlight is these days.
Dr. Curry,
Thank you for posting here and elsewhere. Your attempts at civil constructive discourse are welcome.
If I understand your mechanism, increased temperatures have increased regional precipitation in the SO. The increased precip acts as an insulator which permits sea ice to extend out farther.
Some questions come to mind, if you don’t mind:
1) how much precipitation is required to insulate an area the size impacted by sea ice?
2) do you have available records of precipitation in the SO?
3) the records of temperature in SO seem to indicate rather trivial warming, mostly long before what is generally recognized as a significant CO2 could have taken place. How do you reconcile this in your modeling work?
5) You contrast this with the Arctic where you say a lot melting has occurred. How does this reconcile with studies that show sea currents and wind patterns- both which
many people believe the evidence shows are highly variable- are responsible for recent declines in Arctic sea ice. How does your model take into account the idea that wind pattern and current fluctuations could in fact be responsible fluctuations in sea ice in the Antarctic region of the SO as well as the Arctic?