Land Surface Temperature Contribution To Non-Polar Temperatures
Guest Post by Bob Tisdale
INTRODUCTION
Frank Lansner’s post Did GISS discover 30% more land in the Northern Hemisphere? at Jo Nova’s blog created a recent stir. Watts Up With That ran a similar post by Frank, Tipping point at GISS? Land and sea weight out of balance. Both posts spawned rebuttals/explanations, including Zeke Hausfather’s post The GISTemp Land Fraction at Lucia’s The Blackboard and my post Notes On The GISTEMP Ratio Of Land To Sea Surface Temperature Data, which Anthony Watts co-posted as GISS land and sea ratios revisited, on the same day that he ran Frank Lansner’s post.
Basically, Frank Lansner’s post contends that GISS has increased the ratio of land to sea surface data with time, from zero percent early in the 20th century to near 70% in recent years. With a close examination of the graph that was being presented as a reference, Frank’s land surface data looked unusual, and I believe Frank’s observations are skewed by his choice of base years, and possibly by his smoothing method. I discussed this with him in a detailed comment that I posted at WattsUpWithThat and Jo Nova’s website. Refer to:
OVERVIEW OF THIS POST
There are lingering beliefs that there’s something unusual about the way GISS handles land surface data. In an effort to dispel those misunderstandings, the land surface data contribution to combined land and sea surface temperature data will be illustrated in this post, using a very simple method. Sea surface temperature data will be subtracted from GISS, Hadley Centre, and NCDC combined (land and sea) surface temperature products. The remainders, which are the contributions of the land surface temperature data to the combined products, will be compared. Personally, I was surprised with the results. But first, we need to eliminate the effects of known differences between the GISS and the other two global temperature datasets.
GISS treats the polar regions differently than the Hadley Centre and NCDC. GISS has better land surface temperature data coverage than the Hadley Centre and NCDC in the Arctic and Antarctic. And the Hadley Centre and NCDC include Arctic and Southern Ocean sea surface temperature data as seasonal sea ice melts, while GISS deletes sea surface temperature from areas where there is seasonal sea ice. The treatment of polar data by GISS was discussed in GISS Deletes Arctic And Southern Ocean Sea Surface Temperature Data, which was also co-posted at WattsUpWithThat, GISS Deletes Arctic And Southern Ocean Sea Surface Temperature Data. So, due to those differences, this post will only examine the global temperature data between the latitudes of 60S and 60N. These latitudes represent approximately 85% of the surface area of the globe.
Note: It is also known there is little to no Antarctic land surface temperature data prior to the 1950s. But this can’t explain the results Frank Lansner was reporting.
DATA SOURCES
GISS and Hadley Centre combined (land and sea) surface temperature anomaly data were downloaded from the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
The KNMI Climate Explorer was also the source of Hadley Centre sea surface temperature (SST) anomaly data (HADSST2) used in its combined product. It also served as the source of the two SST components of the GISS combined product, HADISST from January 1880 to November 1981 and Reynolds (OI.v2) from December 1981 to present. The method employed to merge the two SST datasets used in the GISS product is discussed under Step 4 of the GISS current analysis webpage. The base years (1982 to 1992) used for splicing are different than those presented by the KNMI Climate Explorer for the GISS combined product, so I shifted the merged SST anomaly data to account for this.
I wanted to compare NCDC data in this post also, but it is not available through the KNMI Climate Explorer, and since the NCDC does not break down its standard combined surface temperature product into the desired latitude band (60S-60N) on its Global Surface Temperature Anomalies page, I used a second source. The NCDC also has SST, LST, and combined temperature anomaly data available through its ERSST Version 3/3b webpage, and it is available in multiple latitude bands, including 60S-60N. Scroll down to their link ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo under the heading of “ASCII Time series Tables”.
Figure 1 compares the combined global (land and sea) surface temperature anomalies of the standard NCDC product and the data available through the ERSST.v3b webpage. The trends are identical at 0.057 deg C/decade. The difference appears to be caused by the use of different base years. The standard NCDC product uses 1901 to 2000 for base years while the data available through the ERSST.v3b webpage appears to be based on the NCDC climatology of 1971 to 2000. So this post uses the NCDC SST and combined (LST and SST) data that’s available through the ERSST.v3b webpage:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo
http://i28.tinypic.com/vrsikk.jpg
Figure 1
Links to the data presented in Figure 1:
“Standard” NCDC Global combined product:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_ocean.90S.90N.df_1901-2000mean.dat
NCDC Global combined product through ERSST.v3b webpage:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.land_ocean.90S.90N.asc
Note: There are two different series of data available through the ERSST.v3b webpage. Those ending with .gv3.asc are recent additions, and since they have a slightly different trend and I have not found any mention of them in any other webpage, I have not used them in this post.
NON-POLAR SST AND COMBINED (LST & SST) SURFACE TEMPERATURE ANOMALY COMPARSONS
Figures 2 through 4 are comparison graphs of GISS, Hadley Centre, and NCDC SST and Combined (SST&LST) datasets for the latitudes of 60S-60N. All data has been smoothed with a 13-month running-average filter. They are being provided as references.
http://i26.tinypic.com/dmd2k1.jpg
Figure 2
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http://i32.tinypic.com/2gvitja.jpg
Figure 3
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Figure 4
CONTRIBUTION OF LAND SURFACE TEMPERATURE ANOMALY DATA TO NON-POLAR SURFACE TEMPERATURES
As discussed in the overview, to determine the contribution of land surface temperature anomaly data, the SST anomaly data was subtracted from the combined data. Before subtraction, the SST data was scaled by a factor of 0.755 to represent the ratio of ocean to land between the latitudes of 60S-60N. The remainders for each dataset are shown in Figures 5 through 7. Note that these graphs represent the remainder of subtraction, not the actual land surface temperature anomalies. To convert them back to land surface anomalies, they would have to be scaled.
http://i32.tinypic.com/14izupt.jpg
Figure 5
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http://i29.tinypic.com/2qak75i.jpg
Figure 6
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http://i30.tinypic.com/2ymc2vk.jpg
Figure 7
COMPARISON OF LAND SURFACE TEMPERATURE CONTRIBUTIONS
Figure 8 compares the remainders resulting from the subtraction of the scaled SST data from the combined (LST&SST) GISS, Hadley Centre, and NCDC products. As shown in Figures 5 through 7, the land surface residuals are noisy, so for this comparison, the data was smoothed with a 37-month running-average filter. While there are slight differences in the yearly and decadal variations in Figure 8, the linear trends for the three datasets are basically the same, differing only 0.001 deg C/decade.
http://i31.tinypic.com/33cp74w.jpg
Figure 8
This suggests, for the latitudes of 60S-60N, the differences between the combined products from GISS, Hadley Centre, and NCDC result from differences between the SST data they employ. Refer to An Overview Of Sea Surface Temperature Datasets Used In Global Temperature Products. And the most significant differences in SST anomalies occur before 1940. From 1880 to 1940, the SST anomaly data used by the Hadley Centre and NCDC have significant dips and rebounds, as shown in Figure 3 and 4, while the dip and rebound is much less pronounced in the SST data used by GISS, Figure 2.
SO HOW DOES GISS LAND SURFACE DATA DIFFER FROM THE HADLEY CENTRE AND NCDC?
The Hadley Centre and NCDC land surface temperature anomaly datasets represent continental land masses only, and on a global basis, both of those datasets exclude Antarctica. The land surface data presented by GISS, on the other hand, includes continental land mass data plus much more. First, looking at Figure 9, continental land mass data is extended out over the oceans in the GISS land surface temperature product with 1200km radius smoothing. (Figure 9 is a trend map available through the GISS Global Maps webpage, and it shows the regional changes in temperature anomaly from 1880 to 2009. I’ve cropped the map to show the latitudes, 60S-60N, used in this post.)
http://i31.tinypic.com/4kd9ns.jpg
Figure 9
Second, GISS also includes data from island surface stations and from “Ship stations,” and these values are also extended out over the oceans. This GISS dataset is a carryover from the methods developed by GISS back in the 1980s, when SST datasets were incomplete. They were attempting to simulate global temperature anomalies without using SST data. This is explained further in a WUWT comment from Zeke Hausfather to Frank Lansner in which Zeke quotes from a correspondence from Dr. Reto Ruedy of GISS:
In part it reads, “The curve NCDC and most likely you are computing shows the mean temperature over the land area (which covers about 1/3 of the globe, a large part of it located in the Northern hemisphere).
“None of our graphs represents that quantity. We could obtain it by creating a series of maps, then averaging just over the land areas (similar to what we do to get the US graph).”
It continues, “Since our interest is in the total energy contained in the atmosphere which correlates well with the global mean surface temperature, all our graphs display estimates for the global mean, the ones based on station data only as well as the ones based on a combination of station and ship and satellite data. Obviously, the latter is the more realistic estimate and we keep the first one mostly for the following historical reason:
“When we started out in the 1980s analyzing available temperature data, historic ocean temperature data were not yet available and we did the best we could with station data. As soon as ocean data compilations became available, we used them to refine our estimates (calling it LOTI). But we kept the earlier estimates also, mostly for sentimental reasons; they are rarely if ever mentioned in our discussions (see also the ‘note’ in the ‘Table’ section of our main web site).”
And continuing this post, the “‘note’ in the ‘Table’ section of [the GISTEMP] main web site” reads, “Note: LOTI provides a more realistic representation of the global mean trends than dTs below; it slightly underestimates warming or cooling trends, since the much larger heat capacity of water compared to air causes a slower and diminished reaction to changes; dTs on the other hand overestimates trends, since it disregards most of the dampening effects of the oceans that cover about two thirds of the earth’s surface.
And again, LOTI represents the GISTEMP combined land and sea surface data and the dTs represents the land surface data.
CLOSING REMARKS
The GISS Global-mean monthly, seasonal, and annual means dataset does not represent continental land mass temperature anomalies as many believe. It, therefore, cannot be employed in analyses like the one Frank Lansner is attempting to perform.
Dr. Ruedy’s statement that GISS could create a continental land temperature anomaly dataset similar to NCDC “by creating a series of maps, then averaging just over the land areas,” is another way of saying they could create it by masking the areas where the land surface data extends out over the oceans. And this was noted in the post Notes On The GISTEMP Ratio Of Land To Sea Surface Temperature Data.
Then there’s the similarity in the linear trends of the land surface contributions for the three combined datasets, Figure 8. It confirms the findings of the independent researchers who are creating land surface temperature anomaly datasets: the results are pretty much the same as the GISS, Hadley Centre, and NCDC data.
I’m interested in Bob Tisdale’s work. He seems to be a thorough worker. But I can only concentrate on so much of the details before my mind starts to jump… often to the next commentator. If I try to force myself to “concentrate” I simply fall asleep. I know. I’ve fallen asleep more often at the keyboard doing Climate Science than I’ve fallen asleep in bed over the last couple years!
I’m interested in Frank Lansner too. But I cannot disentangle which is “correct”, Frank or Bob, without falling asleep! However, my feeling is that while Bob may be more thorough on details in his area of expertise, Frank has a bigger picture… and that bigger picture, which includes the UHI/station degradation, is of great importance… and holds my interest. I trust my feelings, at least to indicate something worth examining a little more closely. Frank may also be right on the details too… or Bob may be. How can I tell – without falling asleep again?
How many others have experiences like this? Yet the official science papers are far worse. No wonder scientists flounder outside their expertise – so that some will say, Miskolczi / G&T is spot on… and others will say, Garbage… and all I can manage is hunches which are more humble than many commentators’ comments, but which I still trust and just keep quietly to myself, looking for bite-size evidence, rather than open to the flood of “expertise”/”disproof” of a Nick Stokes or a Ferdinand Engelbeen, that just overwhelms me and sends me to sleep again.
Courtesy, and not losing sight of human scale, are really important here. I have the feeling that Bob and Frank are gradually rubbing expertise off each other… and I look forward to the time when they will come to agreement in ways that I too can cope with, and understand.
Frank Lansner asked, “So if you really want to use GHCN based station data to learn about PURE land data, then you would have to mask using method “More than 1200 from a coast” – isnt that so?”
Are you saying that only land surface data inland 1200km from the coast should be evaluated? If so, why?
ArndB says: “It would presumably more correct to say: __Sea Surface Temp govern Land Temp__, and if this principle would be more observed, the reason for the temperature decline after the 1930s could be found by analysing the impact of WWII…”
If one assumes the global oceans integrate the effects of El Nino and La Nina events, the temperature decline after the mid-1940s could be explained as a change in the frequency and magnitude of ENSO events. Refer to my post “Reproducing Global Temperature Anomalies With Natural Forcings”:
http://bobtisdale.blogspot.com/2009/01/reproducing-global-temperature.html
Frank Lansner: You wrote, :The idea you have to exactly retrieve land data from these GHCN based temperature series from GISS, CRU etc. is very very complicated an inaccurate as i told you. ”
First observation about your comment. you write abouut GISS and CRU land surface temperature data as if they represent the same thing. As I have written to you repeatedly, GISS “land surface temperarure” data includes much more than the continental land masses. It is not the same as CRUTEM data.
There is nothing complicated about retrieving NCDC or CRU or GISS land surface data. They are readily available on a gridded basis through the KNMI Climate Explorer. The problems arise when one assumes that GISS land surface data represents the same data as CRU and NCDC.
Hi Bob.
“You, however, take that dataset and assume it represents only continental land mass temperature anomalies. ”
Again, just one of the examples, from the WUWT writing:
“In general GISS defends use of larger land fraction due to their 1200km zones around land stations reaching some Ocean areas. But this does obviously not explain a land fraction that appears to go from near zero to around 70% globally during the 20th century.
”
Maybe its my English (??) but this text comes just after the essential graph in my WUWT article, it was ment to say:
“YES, according to GISS the “land” data is supposed to be not only land , but it does not explain that from 1900-20 the GISS “LAND” was weighted zero, and then recently weighted strongly.”
Again, i may not have communicated this well enough.
I am writing on a follow up, and i think this will make more obvious some issues of GISS “land” temperatures, and weighting hereof.
K.R. Frank
Frank Lansner: You wrote, “Bob then to your article, you focus on that there are land similarities between GISS, CRU and NCDC, right?” And you continued, “For me, a similarity between those three institution is simply not an argument in these climate gate times, im sorry. I may sound fanatic, but if eferything that these 3 institution agrees about is just a little true, i would have to turn alarmist pronto ;-)”
This post has nothing to do with “climategate.” Why are you introducing the topic? It appears as though you are trying to redirect the conversation to something other than the errors in your analysis.
In this post I removed a known difference between GISS and the other two datasets by limiting the data to non-polar latitudes. I then subtracted the scaled SST anomalies from the combined land and sea surface temperature anomalies. The remainders from the three datasets (the contributions of the land surface data) are remarkably similar:
http://i31.tinypic.com/33cp74w.jpg
What does that imply to you, Frank? To me, it implies that with all of the adjustments made to the data by GISS, Hadley Centre and NCDC, there is little effect on the long-term trend. To me it also implies that GISS does not weight the continental land surface temperature data differently than the Hadley Centre or NCDC. And this contradicts your posts.
Frank Lansner July 24, 2010 at 5:21 am: You wrote in part, “But this does obviously not explain a land fraction that appears to go from near zero to around 70% globally during the 20th century.”
You then rewrote it as, ““YES, according to GISS the ‘land’ data is supposed to be not only land , but it does not explain that from 1900-20 the GISS ‘LAND’ was weighted zero, and then recently weighted strongly.”
And this is the basis for this post and the basis for my post from last week. GISS does not change the land fraction so that it “appears to go from near zero to around 70% globally during the 20th century.” You need to mask where the land data extends out over the oceans in order to perform the type of analysis you are attempting. You also need to assure that your base years and method of smoothing do not skew your results, and as far as I know you have elected not to do these things. Why?
Also, I have presented a number of questions to you above, and you have not replied to them. Why? I reply to your questions.
I propose an “alarmed layperson carbon lifestyle” tax. After all, the block of population that earns income above $250,000 is so small that it would not make a dent in our unenlightened carbon emitting ways. The layperson tax would hit a larger group of citizens (who needs to drive to work anyway?) and thus have more impact. Our alarmists should light the way through self imposed dracnonian sacrifices in their daily lives. We can then measure the effects and go from there.
Sarcasm aside, it’s funny to see how some can just say that others shoud pay more for no other reason than that they have money.
Mike, I need money. Please give it to me. I swear that I will use it for a more worthy cause than you will. I swear.
Bob
Yes, what I was struck by was the small difference and the possibility of in that period of time that the accuracy of the source put the results in the noise.
Thanks for the response.
Bob Tisdale says: July 24, 2010 at 4:59 am, (Rely to: ArndB, July 24, 2010 at 3:27 am )
“If one assumes the global oceans integrate the effects of El Nino and La Nina events, the temperature decline after the mid-1940s could be explained as a change in the frequency and magnitude of ENSO events.”
By ocean dimension the El Nino and La Nina events are “peanuts”, as El Nino represents a temporary warm water pool over a small area of the entire ocean space down to 50 depth, but they are the most significant of the known and investigated events caused by the sea. But the status of the oceans is driving the atmosphere at any time, which is quickly observed when in coastal areas the sea wind (afternoon) changes to land wind (early morning). If an El Nino can have a distant impact, any other change of the ocean surface layer of a few dozen meters alters the running weather as well. The claim that there had been a prolonged El Nino from 1939 to 1942 may have contributed, but does not explain the extraordinary three war winters in Europe 1939-1942, and it is a great pity that science has been reluctant to investigate their causation. The massive interference of naval war on the marine environment from 1939 to 1945 could be seen as a large-scale experiment concerning the impact of human activities on weather and climate. It would contribute significantly to understand the ocean-atmosphere process, and the relevance of the oceans better.
Always interested in your fine work; Regards ArndB
Please, Frank, you keep iterating the same nonsense over and over. The rebuttals of Bob, Zeke and other should have given you pause long ago about the correctness and relevance of your analysis. Please ponder what Bob Tisdale is saying.
Or go back to the Lucia thread and read what eg carrot eater (eg. Comment#49424) has to say to you:
http://rankexploits.com/musings/2010/the-gistemp-land-fraction/#comments
You know that I do not not subscribe to CAGW but I wish you would abandon this topic. It is a dead end.
Lucy Skywalker says:
July 24, 2010 at 4:43 am: I love your comments, Lucy; they never make me sleepy. Dare I say: I Love Lucy!
Niels A Nielsen: Regarding your July 24, 2010 at 6:45 am comment:
Thank you, Niels. There are just so many ways I can present this.
Outstanding post…
Lucy Skywalker: I completely agree with you and I just don’t have the time or energy to delve into the data enough to make my own conclusion. It puts me to sleep just thinking about all the effort these two guys have given this subject.
And while it is important we get all the technical details correct, I think this issue is just that, a technical one. It is not the most important one. I think we can trust that GISS, Hadley Centre and NCDC all come up with pretty much the same results. However, I don’t think those results are correct due the homogenization, adjusting, poor siting, UHI problems, etc. that has been done to the raw data. I’m still putting my faith in the satellite record, which clearly says, 2010 isn’t the warmest year of record. It is too bad we don’t have satellite data for the 30s. What we are experiencing now, at least in the US, isn’t anything like those years.
As the “alarmed” layperson of an earlier posting, I can see from the couple of comments my “High Carbon Lifestyle Tax” proposal has garnered that I didn’t make my point clearly.
Let me try again. My proposed tax is not intended to raise money and it is not intended to allow anyone to shirk a necessary shared sacrifice. Rather, it is intended to “smoke out” the truth of the conflicting AGW claims. If great sacrifices are required by society, in terms of carbon-reduced lifestyle, to save us all from being burnt to a AGW crisp, then I, as little guy, am more than willing to do my part. But before I “bite the bullet” at the say so of certain enlightened folks, at least some of whom are poised to make big bucks on alternative energy and carbon trading, I want to first observe our wealthiest and most powerful citizens showing the way as we transition to a world of rabbit hutches and bike paths. Leadership from the front and by example, in other words.
My proposal would ensure proper leadership by our elite or confiscation of their wealth by taxation (which wealth could be better used outfitting their up-scale rabbit hutches and bicyles in ostentatious, low-carbon splendor). Then, once us “small people” see our best and brightest making such sacrifices we could be sure the planet really is in a “jam” and we need to shoulder similar sacrifices, as well. On the other hand, if such a tax is not palatable to the wealthiest and best connected of our citizenry, then most likely the whole AGW business is a hustle by some rich guys trying to get richer and us cannon-fodder can blow the whole scare off and get back to guiltless Sunday drives in our SUV’s. My proposal assumes, of course, that the elite tier of our society is enlightened enough to moderate their opulent life-style if they knew and truly believed such life-style downsizing was necessary to save Gaia from becoming a Venusian hell-hole. I hope I have not made an unreasonable assumption.
To put a fine point on the matter, the science of AGW is of interest, but the public policy that flows from it is the item of greatest concern to us all–especially since so much doubt has been raised about climate science bias and politicization. Hence my proposal as a means to get to the heart of the public policy issue. Fish or cut bait.
ArndB: You wrote, “The claim that there had been a prolonged El Nino from 1939 to 1942 may have contributed, but does not explain the extraordinary three war winters in Europe 1939-1942, and it is a great pity that science has been reluctant to investigate their causation.”
I believe the European wartime winters have been studied. I recall reading something about them (a paper?) within the last five years, though I don;t have any idea when the paper was written. And recall Tamino writing something within that last two years, so that may be a place to start looking for links. But then you went on to discount ENSO events.
You wrote, “By ocean dimension the El Nino and La Nina events are ‘peanuts’…”
Peanuts? The equatorial Pacific extends approximately 170 deg longitude or almost half way around the globe. The tropical Pacific SST anomalies are directly impacted by ENSO events and they can peaked at 0.9 deg C (1997/98 El Nino), then dropped to -0.34 deg C during the subsequent La Nina, and that’s even with the dipole effect between the eastern and western tropical Pacific. The last time I checked the tropics represent more than one-third of the globe, so we’re looking at about one-sixth of the surface area of the globe that is directly impacted by ENSO events. Based on weekly SST data for the 1997/98 El Nino, NINO3 SST anomalies peaked at more than 3.6 deg C and NINO1+2 SST anomalies peaked at 4.4 deg C. What else? Through coastally trapped Kelvin waves, ENSO events also directly impact the sea surface temperatures of the American coast from Chile to Alaska. Through the strengthening of surface winds and currents and the reduction in cloud cover, La Nina events directly warm the PWP, SPCZ and Kuroshio extension. Through known changes in atmospheric circulation, ENSO events impact land surface and sea surface temperatures globally. The only other periodic natural forcing/variable that has a larger multiyear impact on global temperature is a catastrophic volcanic eruption. You call those peanuts?
Regards
C James: You wrote, “And while it is important we get all the technical details correct, I think this issue is just that, a technical one. It is not the most important one.”
Agreed. This post was simply an attempt to dispel misunderstandings and suppress the chain reaction rumors.
# Bob Tisdale says: July 24, 2010 at 9:09 am
___ I believe the European wartime winters have been studied. I recall reading something about them (a paper?)
___ The only other periodic natural forcing/variable that has a larger multiyear impact on global temperature is a catastrophic volcanic eruption.
Presumably you have come across the:
Letter to NATURE; “Extreme climate of the global troposphere and stratosphere in 1940–42 related to El Nino, by S. Broennimann, J. Luterbacher3, J. Staehelin, T. M. Svendby, G. Hansen & T. Svenøe; Vol 431, 21 October 2004, p. 971f.
The paper concludes: “ that the global climate anomaly in 1940 to 1942—previously poorly documented—constitutes a key period for our understanding of large-scale climate variability and global El Nino effects”, based on the assumption that there had been a prolonged El Nino effect from 1939-1942. The claim (prolonged El Nino) is mainly based on sea surface temperatures, which are highly unreliable as discussed in a paper from 1997:
http://www.oceanclimate.de/English/Pacific_SST_1997.pdf
For example Henry Diaz and G. Kiladis (1992, p.18) conclude that there was an El Nino in 1939 and an El Nina in 1942. Even when one regards a size between Australia and Africa as a reasonable equivalent for the size of the pool of warm water representing an El Nino, the pool by cubic kilometres is small in comparison with the dimension of the ocean in space and depth.
Concerning the impact of the oceans in case of a serious volcanic eruption, back in 1992 I analysed why the Krakatoa event in August 1883 did not resulted in a devastation decline of global temperatures, although the sun amount of solar energy received was clearly reduced for a period of several years.
http://www.whatisclimate.com/conditions-for-the-protection-of-the-global-climate.html#_aa12
Five years after the eruption of Krakatoa, the scientific work on the events of the year 1883 were temporarily brought to a close with the “Report of the Krakatoa-Committee of the Royal Society.” The most amazing aspect of the report is that it does not contain any mention of possible relevance of the oceans. The investigation shows that the most likely reason for the fairly stable air temperatures in the aftermath of Krakatoa had been the heat supply by the oceans.
With regard to understanding the three extreme WWII winters little to nothing has been done. Since the 19th century, winters had become successively milder. “The present century has been marked by such a widespread tendency towards mild winters that the ‘old-fashioned winters’, of which one had heard so much, seemed to have gone for ever. The sudden arrival at the end of 1939 of what was to be the beginning of a series of cold winters was therefore all the more surprising,” reported the British scientist A. J. Drummond in the QJoR Met. Society as early as 1943. He also notes: “Since comparable records began 1871, the only other three successive winters as snowy as the recent ones (1939/40, 1940/41, 1941/42) were those of the last war, namely 1915/16, 1916/17, 1917/18.”
Just a coincident? The role of the ocean and seas on the war winters and the global cooling could be well studied along the WWII naval activities in Northern Europe’s waters, and in the Northern Atlantic and Western Pacific since 1942.
Thanks for your reply and best regards ArndB
At the risk of turning this into a 2 discussion thread, I cannot let Mike’s comment go without rebuttle.
First and foremost, why not let science smoke out the truth. How does a tax on non-scientists get us closer to this “truth” that you and the rest of us seek?
Senondly, why does someone else have to go first before you make a sacrifice? Do you really think those that propose a carbon free energy world and those that profit from it will set the example for self sacrifice? Would that person be someone like Al Gore?
You want leadership from the elite or you threaten confiscation of their wealth. I hope that one day you will see how easy such loigic can turn against you. Taxation used to be a means for funding the constitutional functions of the government. Now we sit back in our chair and say, they don’t live the right way, let’s take their wealth. I cannot make the connection between the two and it concerns me that you can.
Lastly, you close with the hope that you have not made an unreasonable assumption. I think you have made several unreasonable assumptions. To assume that the “elite’s” lifestyle is the key to preventing the earth from becoming a “venusian hell hole” is naive in the extreme. Just as naive as assuming that public policy should flow before the facts are discerned. It may be done that way and you may be used to that methodology, but I would rather be on more firm ground scientifically before rearranging every facet of interaction between supposedly free people.
ArndB says:
July 24, 2010 at 6:31 am
the 3 War Years make a great argument against letting the Green Agenda toy with the climate at scale.
The millions of gallons of dispersant condoned by EPA in the Gulf with unknown long-term consequences are an example, along with Dept. of Fish & Game poisoning of Lake Davis, Plumas Co, Ca.
They don’t care what goes wrong.
Bob Tisdale says:
July 24, 2010 at 3:54 am
Could you do something on Polar Amplification?
I’d like to know how that works and what it affects.
“And while it is important we get all the technical details correct, I think this issue is just that, a technical one. It is not the most important one. I think we can trust that GISS, Hadley Centre and NCDC all come up with pretty much the same results. However, I don’t think those results are correct due the homogenization, adjusting, poor siting, UHI problems, etc. that has been done to the raw data. ”
1. It is a technical detail that Frank got wrong. It points to a couple things. Its very difficult to speak about GISSTEMP with any authority UNLESS you have gone through the code. When you do go through the code you’ll see that Frank is just flat wrong. he’s misinterpreted a graph. Its also clear that there are dangers in posting data without the code. GISS post a “legacy” graph. One that has been misinterpreted. Its important to those of us who lobby for open code and data, that people who make mistakes about freely posted material be candid and forthcoming when they make mistakes.
2. The results of the three agencies is substantially the same. More importantly their results have been matched by several independent citizens, from many sides of the debate.
3. No one who asserts there are fundamental issues with the GISS approach has seen fit to invest the few days of coding it would require to “prove” the case. Every attempt I am aware of has confirmed the general soundness of the approach.
4. On the “correctness” of the answer. No answer is correct. There are two things we need to concern ourselves with. Error and bias. WRT Error the LLN is our friend, provided there is no BIAS. So lets talk about BIAS
A. Sampling bias. The concern here is that we have a sample that is BIASED toward
higher TRENDING stations and grid cells. Whats the evidence and whats the
theory? I’ve resampled the sample of stations. That is, I randomly selected stations and recomputed the mean. no difference in trend. I’m going to resample
on a cell basis ( pick 3×3 grid cells and resample) I already know the answer.
the answer will be NO DIFFERENCE IN TREND. I know this because the distribution of trends for the cells is rather normal looking, a bit leptokurtic
if I had to guess. Theory says that the trends at the Northern latitudes will
be higher than those at lower latitudes. polar amplification. observation bears
this out. The highest trending cell is a high latitude cell. That means, missing data
NORTH of this cell, is likely to be at or above the trend observed at a lower latitudes. Adding more stations, covering more of the globe will not change the global average in any appreciable manner. If anything increased sample will raise
the trend. I make this estimate based on theory( polar amplification) and observation of know data and its distrubutional characteristics.
B. siting Bias. The Surface stations project will help us get a better handle on the
QUANTIFICATION of the bias. From theory we can expect the bias to be in BOTH
directions. Positive ( too hot) and negative (too cold). The latter fools people somewhat, but shading can and does cool sites. The issue with siting bias is:
1. Magnitude.
2. Mean direction (positive or negative)
the CRN rating was created by Dr. leroy. His associate has done some field studies of the bias. Those preliminary estimates indicated a warm BIAS of .1C. That is,
for CRN ,2,3,4 the mean BIAS was .1C warmer than a perfect site. CRN5 was not tested. This also confuses people. The bias, a mirco climate issue, is modulated by
several factors. somedays you see it, other days NOT. The main difference between
CRN 2,3,4 and CRN 1 is the VARIANCE in the measures. ‘2’ refers to the Spread of the data. with a CRN2 you can see temps as HIGH as 2C hotter or as Low as 2C cooler. The mean, is a +.1C. the SPREAD is 2C. Same for CRN3 and CRN4.
Leroy, limited study will of course be supplemented by Anthony’s larger study.
But, based on the limited field study, one should not EXPECT to see a large bias.
one should expect and plan to find a small positive Bias.
C. Adjustment and homogenization BIAS. Much of the data that goes into GHCN has
already been homogenized and adjusted by the source data maintainers. GHCN adds QC on top of this. The source homogenization and adjustments are a BLACK BOX.
One cannot conclude from this that the adjustments introduce a warm bias OR a cool bias. One cannot suppose either case. I would not expect 200 individual countries to systematically introduce a warm bias or a cool bias. Absent substantial evidence to the contrary, one can rationally assume a zero mean Bias. However, THIS is one issue that nobody has run down to the source data. This is an answerable question.
Again, there is a difference between
A. believing adjustments are biased warm. (the disbeliever position)
B. believing the are Zero mean Biased (the warmist position)
C. Being Open minded and asking people to look at the question ( lukewarmers)
D UHI.
UHI bias, like microsite bias can be both positive and negative. Although on an area basis, warm bias tends to be larger. In one particular study a cool bias on average of 2.6C was noted in areas where there was canopy(>64% canopy cover). sun cover. go figure.
“Portland metropolitan area can experience a
negative UHI during summertime afternoons. The
regions that experience a negative UHI are those
with greatest canopy coverage as determined by
the first rule of daytime tree structured regression
models, this is generally the area encompassing
Forest Park. Forest Park is the coolest region of
the city and is generally 2-4 ºC cooler than the
rural surrounds and can be up to 10º C cooler than
surrounding urban regions. During the afternoon
(Figure 6a), the warmest areas of the city are just
across the Willamette River (to the east) from the
downtown area, an area characterized by
commercial land-use and an industrial area just to
the north of the downtown between Forest Park
and the Willamette, these regions experience a
predicted UHI intensity of up to 5 ºC. ”
In areas where there was no cover you can get a warm bias. This bias is driven by Building size. Smaller buildings lead to a cool bias, larger building to a substantial warm bias.
The Evidence shows the bias can be warm or Cool, depending on the location. This goes all the way back to Oke’s seminal work on UHI. So again, this observation suggests that we should look closely at the particulars before jumping to conclusions.
jst:
Greatly appreciate your reply. Your rejoinder was thought-provoking; some of the thoughts it prompted follow:
We both agree on the proper place for science and taxes in our government. But there are powerful interests, I strongly suspect, that do not agree and have chosen to push a self-serving cap and trade tax and renewable energy policies by means of pseudo-science scare tactics and the considerable propaganda resources at their disposal. Sweet reason and good science are hardly likely to prevail in a contest with such interests, however much we might wish otherwise. Not that we shouldn’t be working on the science, as well.
You say my logic “can turn on you.” As I see it, these guys already have their hands half-way in my pocket, I’m merely responding in kind.
My proposal fights fire with fire. In so many words: If I must sacrifice my figurative SUV to save the planet then my betters must also sacrifice their palatial homes, private jet, yachts, etc. And since I’ve got a “little guy” distrust of plutocrats, I’d require that those fine fellows go first.
My proposal would “smoke” out any hustle attached to AGW advocates and their cap and trade tax and alternative energy agenda items by insisting on “mutually assured destruction” of everyone’s lifestyle. That is, if AGW advocates aren’t willing to share with the helots the draconian life-style sacrifices entailed in their low-carbon brave-new-world, then almost certainly the whole AGW business is an alarmist crock and there isn’t any real peril to dear old Gaia. That’s the method behind the madness of my proposal.
Not being totally naive, I estimate my fantasy “High Carbon Lifestyle Tax” would go nowhere in Congress for obvious reasons. But rather than satisfying ourselves with an occasional amusing story of Al Gore’s or John Kerry’s (others could be named) hypocrisy, I’d rather expose that hypocrisy (and the probable deceit it reveals) with a concrete legislative proposal. At a minimum, I think a legislative debate of my proposal, even if it leads to a likely rejection, has the best potential to derail climate legislation in its current form–namely, the big shots keep all their toys and even make money off the deal, while us kulaks loose it all.
Thanks Mike. Good stuff here. I like the direct approach. That means getting their hand out of my pocket before trying to insert mine in theirs.
Exposing hypocrisy requires a science before public policy approach. I think that gets us to where we both want to be. Nobody ever said citizenship was easy.