The GISS Temperature Record Divergence Problem
Guest post by Tilo Reber
“Areas covered occasionally by sea ice are masked using a time-independent mask.”
So if there is sea ice coverage for any part of the year, GISS will not use SST values to cover those cells for the entire year. Those cells must be covered by extrapolations from land for that year. This means that when the area is cover with ice or with water or with part ice part water, it will have it’s anomaly extrapolated from land, regardless. HadCRUT, on the other hand, does not extrapolate their coverage. But they will use SST values for a cell when SST values are available for part of the year. If the area is covered with ice for the entire year, HadCRUT will not assign it a value. Therefore we get polar areas that are covered by extrapolation by GISS and not covered at all by HadCRUT.
When we look at the HadSST2 record, we see that the cool cells that show up above Svalbard in 2005 are consistent with the numbers in that record. And these then go into creating the sea surface portion of the HadCRUT3 temperature record. So, obviously, how cells are filled with data can have a profound effect on the anomaly value that those cells have. This leads one to wonder if extrapolations at the pole are legitimate. I decided to look at some of the northern Russian stations, at the GISS site, that show up as being so hot in the 2005 version of the GISS chart when compared with the 1998 version of the chart. I found that those big changes are in fact represented in the individual records – especially for the coastal stations. Here are three of them.
1998 Annual Mean – -3.39
2005 Annual Mean – 0.60 1998 – 2005 delta 3.99 C
1998 Annual Mean – -14.99
2005 Annual Mean – -10.79 1998 – 2005 delta 4.2 C
Gmo Im.E.K F: 77.7 N, 104.3 E.
1998 Annual Mean – -15.96
2005 Annual Mean – -12.67 1998 – 2005 delta 3.29 C
For comparison, let’s look across the Arctic ocean and see what was happening in Canada and Alaska at the same time.
Eureka, N.W.T.: 80.0 N, 85.9 W.
1998 Annual Mean – -17.38
2005 Annual Mean – -17.34 1998 – 2005 delta 0.04 C
1998 Annual Mean – -8.80
2005 Annual Mean – -10.44 1998 – 2005 delta -1.64 C
So it seems that the North American side of the Arctic changed little, or even got cooler between 98 and 05, the Russian side warmed considerably. Why is that? I think that this ice cover map gives us the answer. As is immediately apparent, the coastal ice cleared out far earlier in 2005 in northern Russia than it did in 1998. This is even though the rest of the globe was slightly warmer in 1998 than in 2005. When dealing with coastal stations, removing the ice and exposing the water is like taking the hatch off a heating source for the coastal thermometers. For stations that are in areas where the temperature is well below zero, exposing the immediate area of that thermometer to a surface that is above zero, changes everything. Looking at Ostrov Vize, we see that it is a small island, and therefore even more subject to changes in coastal sea ice. And when we compare 1998 months on this island with 2005 months we can see that there are differences in some of the monthly means that are larger than 10C. Even a partial ice cover as opposed to a complete ice cover will supply the stations with more heat.
So I think that we can safely say that the huge change in the anomalies of Russian coastal stations is mostly due to coastal sea ice changes. In fact, if we look at stations further inland in Russia, the coastal effect begins to decline. With this in mind, we need to ask if the GISS extrapolations of land based stations, particularly coastal stations, to the poles is appropriate.
The answer would seem to be that it is not, and the Svalbard case makes this perfectly clear. There we had a case where the SST anomaly was actually cool, and yet the land based extrapolation actually turned those sea based cells more than 3C hotter. Reaching across the Arctic Ocean with temperatures that are the result of a coastal sea ice effect cannot give valid answers for what the temperature anomalies away from those coastal stations should be. In fact, taking the variation that is represented by those coastal stations and extrapolating into the interior of Russia is also not appropriate, because the interior areas did not undergo the magnitude of temperature change of the coastal stations.
Looking at the SST temperature anomalies that NOAA uses for 1998 and 2005 it again looks like nothing exceptional was happening in the Arctic (Note, the chart will not retain the months that I selected; so use your own sample months and they will plot). It seems, from this analysis, that GISS polar extrapolations and interpolations are likely to simulate large variations away from the Arctic coasts that are really only present as changes at the Arctic coasts. And the GISS divergence from HadCRUT, as well as from UAH and RSS are likely to be errors instead of enhancements.
David S (11:29:15) :
I suggest using two placed at opposites sides of the globe – one in the Himalayas one in the Amazonian jungle.
Wait, maybe 4, with the above two and one in Antarctica and one at the NP.
Then we can extrapolate the temps world wide from there.
USA Today:
The bit about opening the water is also important. It tends to moderate the temperatures even more. It forced summers to be cooler and winters to be warmer. In Appendix I of my report I compared Port Hope daily temps to matching days at Belleville to see what differences there was in each day. I was amazed at the moderating effect Lake Ontario has on temperatures. Port Hope is right on the lake, yet Belleville only a hour or so from Port Hope, is not far inland from the lake. Yet, the temperature swings for Belleville is larger than Port Hope, with the winter having more deviation at Belleville than at Port Hope. Thus closing stations away from the Great Lakes, keeping stations on the lakes, will tend to show a warming trend where none exists.
Gents, learn to work with the KNMI climate explorer. Check its results here.
HadCRUT Arctic data 66-90N, CRUTEM+HadSST:
http://climexp.knmi.nl/data/icrutem3_hadsst2_0-360E_66-90N_na.png
No net change between 1940s and present, natural cycle related to AMO oscillation.
Compare with combined station+SST data from GISS for the same area: the 1970-2005 warming is much more pronounced
http://climexp.knmi.nl/data/igiss_temp_250_0-360E_66-90N_na.png
Now lets compare only the ground stations: CRUTEM vs GISS
http://climexp.knmi.nl/data/icrutem3_0-360E_66-90N_na.png
http://climexp.knmi.nl/data/igiss_temp_land_250_0-360E_66-90N_na.png
Quite similar, since there are relatively few stations and both datasets use them all.
So the difference must be caused by SST data.
HadSST ocean data from CRU/Hadley:
http://climexp.knmi.nl/data/ihadsst2_0-360E_66-90N_na.png
No net change between 40ties and present.
AFAIK, GISS uses NOAA ERSSTv2 dataset, which is quite different and features beautiful hockey stick:
http://climexp.knmi.nl/data/iersstv2_0-360E_66-90N_na.png
Anthony, please make a thread about the KNMI Explorer, since it is beautiful tool. I have compared for example rural Armagh and Lomnicky peak Observatory temperature record with MSU data for given grids and found excellent agreement.
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Erik:
“One would have assumed that the people down south of the Equator would have noticed the presumably high temperatures there before last week’s NASA news release”
No, a central point in this scam is that no-one can notice anything. Any personal observation is irrelevant because of “local” effects. Hence the invention of the “global” temperature, determined not by observation but by algorithm. And if anyone could actually experience this global temperature, the changes are so small (less than 1C in a century) that they couldn’t possibly be noticed against the background variation (where I live about+/- 10C each day).
The Game of divergence can only be played as long
as people’s perceptions of reality can be manipulated.
We have reached that tipping point. AGW proponents
are beginning to look incompetent. Soon they will
look profoundly incompetent.
This is yet further evidence that “global” temperature is a meaningless concept.
It is impossible to say to what extent any particular area will warm if the average goes up or any particular area will cool if the average goes down. The average can go up while some areas cool and vice versa. There is nothing global about it other than the fact that the meaningless figure is calculated by playing with initial measurements that are taken from (a small number of) places spread around the globe.
@John a (11:35:36) :
Why don’t these people simply provide temperature records for the areas where they have thermometers, and leave the unmeasured areas blank?
It doesn’t add any value at all to our understanding … just to make a map appear filled in.
Interpolation is a technique to “fill in” blank spots in the data. It is very useful, and sometimes essential. If you are a mining engineer, it helps you make rational decisions on where to invest money in digging, even though you have limited data. If you fail to find anything, you might be out of a job…
Problem here is we are not making decisions on where to invest – we are trying to understand a complex system. And there is little feedback to those who are doing the interpolating. It’s one of the pitfalls of our computer age – it is so easy to run algorithms to “smooth” the statistical surface.
Leaving blank spots on the map looks quaintly archaic, but it’s really a pretty darn good idea!
This is intriguing.
It would be more persuasive if you could show exactly how the temperatures inland differ from those on the coast in Russia.
Also, what pattern do you see in the overall period from 1998 to 2009?
It certainly seems odd to extrapolate land temperature anomalies on to the ocean.
How well covered is this area by the satellite record?
Good for the Hadley Center. We should obviously believe everything they tell us now…. oops sorry, I forgot, they are duplicitous, lying, cheating, American hating, God hating, environmentalist, lefty, communist, child manipulating… and the worst… Europeans! My God! The sky is falling!
BTW, if we assume that the divergence is an error on the part of GISS, how significant an error is it? The plots at Hansen’s house don’t look like more than 0.1 degree, and the trends are close.
Interesting piece, but is it a knock against the overall GISS argument, aside from evidence of their self-serving tendencies when it comes to data manipulation?
Nitpick on presentation:
In
1998 Annual Mean – -15.96
2005 Annual Mean – -12.67 1998 – 2005 delta 3.29 C
“-” has three different meanings: first a separator, then a sign indicating the negative value of the following number, then a sign that seems to mean (in conjunction with the modifier “delta”) that the temperature in the year on the right (not the number itself) is to be subtracted from the temperature in the year on the left to give the result -12.67-(-15.96)=3.29.
Not that I’m mounting a defense of his method, but it is worth pointing out that the polar regions are but a very small part of the whole.
“DEK (12:03:19) : ”
You’re one of the 3-letter-trolls, right? Is MJK a flatmate of yours?
Andrew P.
“Very interesting. Has this been addressed anywhere in the literature?”
Not that I’m aware of Andrew. It would be nice if someone like Pielke did a more complete statistical job than I have done. I feel solid about what I have found in a qualitative sense. But it would be nice to get it wrapped up quantitatively as well.
lichanos (11:58:00) :
“Problem here is we are not making decisions on where to invest ”
Actually, I think that is exactly what ‘we’ are doing.
Roger Sowell:
“A few cold winters (but not abnormally cold) from 1975 to 1985 produced a temperature trend that appeared to be global warming.”
Roger, look at the ENSO transition that happened right around 1977. Both before and after.
http://www.esrl.noaa.gov/psd/people/klaus.wolter/MEI/ts.gif
I have a silly OT question. It is so rudimentary that I have to wonder if I am missing something… Here are two ubiquitous graphs in the climate change debate:
First is the climate anomaly graph since 1880:
http://upload.wikimedia.org/wikipedia/commons/f/f4/Instrumental_Temperature_Record.png
Next is the “Spaghetti Graph”:
http://upload.wikimedia.org/wikipedia/commons/b/bb/1000_Year_Temperature_Comparison.png
Ok, now follow this simple line of reasoning and tell me where I am wrong.
1) The anomoly at 2000 is roughly +0.4 for both graphs.
2) The lead to the conclusion that the 0-line in very near to or equal in both graphs.
3) The Spaghetti Graph shows that out of all the 1100 years shown, only the last part of the 1900s registered a positive anomaly from the chosen mean.
4) “Zooming in” using the 1880-2000 graph we see that other than a brief stint in 1940, the global climate failed to climb above mean until about 1979.
5) So… here is the head slap moment.. does that mean that, by their own admission, the global temperature has only been above historic mean for about 35 of the last 1100 years?
NASA had a lot of practice manipulating, distorting or hiding data before the events exposed by Climategate.
We parted way in 1972 because NASA didn’t like experimental observations that showed:
a.) Severe mass fractionation of Xenon (Xe) isotopes mixed with excess Xe-124 and excess Xe-136 from a supernova at the birth of the solar system [“Xenon in carbonaceous chondrites”, Nature 240 (1972) 99-101].
http://www.omatumr.com/Data/1972Data.htm
b.) Mass fractionation of Krypton (Kr) and Xenon (Xe) isotopes in the solar wind material implanted in lunar soils [“The role of isotopic mass fractionation in the production of noble gas anomalies in lunar fines from the Apollo 15 mission”, Third Lunar Science Conference, vol. 2 (1972) 1927-1945].
http://www.omatumr.com/Data/1972Data1.htm
With kind regards,
Oliver K. Manuel
Former NASA PI for Apollo
Emeritus Professor of
Nuclear & Space Sciences
“Leif Svalgaard (12:08:57) :
Not that I’m mounting a defense of his method, but it is worth pointing out that the polar regions are but a very small part of the whole.”
The polar regions are very important for two reasons:
1. Humidity should be very low there, especially in Antarctica. How does this affect the water vapour greenhouse effect?
2. Temperature is very low, so much less LWIR should be radiated upward.
In both ways, the icecaps behave very differently from the rest of the globe. The AGW people always pointed out “Global Warming comes stealthily, you won’t notice because the poles are most affected”. This could explain why they have such a big interest in NOT getting real measurement values from up there.
Dan in California:
“It seems to me that there should statistically be both upward and downward adjustments.”
I agree with you Dan. Have a look at this adjustment chart from USHCN.
http://cdiac.ornl.gov/epubs/ndp/ushcn/ts.ushcn_anom25_diffs_urb-raw_pg.gif
At one time I had a link that broke it down by the different adjustment types. And they were all up.
How do those same Russian coastal stations compare between 2005 and 2007 when sea ice reached its “historic Minimum” levels. Shouldn’t this have lead to a 2007 that would be similarly proven statistically warmer than 2005?
The folks at NASA, have also decided that heavy-lift capability is not important for the U.S. space effort. Admittedly, I am not a rocket scientist but this decision does not make sense to me. Why are the leaders of these agencies so confused about their goals and missions? Money-nuts-both? How did these people get where they are today? The more I learn the less I understand…
In my non-scientific study of driving my car that has a themometer readout in the rear view mirror. I live near a small lake…depending on the weather there is anywhere from a 1-5 degree temperature difference between my house and the grocery store 1.8 miles away.
Then if I go to GISS and put get a list of ‘reporting stations’ near me I get this one listed as ‘rural’.
47.2 N, 122.0 W 425742060030 rural area 1913 – 2009
It’s right in the middle of a nice subdivision of relatively new homes. It’s not rural anymore.
Earth to NASA…extrapolating temperature anomalies over large areas based on the quality of your data is impossible.
“Tom (12:31:29) :
The folks at NASA, have also decided that heavy-lift capability is not important for the U.S. space effort. ”
Big O deep sixed the Constellation program.