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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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.
.3 degree C over 130 years?
As an “alarmed” layman trying to make sense of the conflicting claims of the AGW controversy, I proposed to my Senator a way to sort the whole matter out, once and for all.
In particular, I proposed a “High Carbon Lifestyle” tax for those with family incomes greater than $250,00/year and businesses with similar incomes. My fantasy bill would impose a surtax that would proportionately apply to taxpayers whose residential properties exceed 1,2000 sq. ft./resident (all residences, worldwide, considered and rising to a 100% surcharge if the ratio exceeds 5,000 sq. ft./resident). A similar surcharge for private aircraft travel. Also, elimination of the business deduction for business travel by airplane and elimination of all government funding for travel to conferences (to encourage video conferencing). Other provisions may be usefully added to the above.
The rationale for my proposal is that if our wealthiest and most powerful citizenry are willing to make draconian sacrifices to their lifestyle to reduce carbon consumption, then the AGW concerns are likely well-founded–otherwise, an alarmist hustle. Also, my proposal would allow our “betters” to lead from the front, for once, and lead by example.
A “little guy” way to sort out the AGW business, but I think it’s once that has something to recommend it.
Another hockey stick!
I am reading this as: The land surface temperature is the smaller portion of the dataset warming anomaly. The SST is the dominant factor here.
So, when I look at SST data and anomaly, I see the oceans cooling, and with it goes the global temperature.
ABC World News Tonight was trying to poke fun at Sen. Inhofe tonight, suggesting that “NOAA says” hottest ever is the trump card.
The Senator says the globe is cooling, and he’s correct. The newsman kept cutting the Senator off.
The interviewer’s parting suggestion of “NOAA says” was a cheap shot off interview.
Well of course the land contribution will be warmer now with all the rural sites disappearing from the dataset leaving more urban/airport readings in the mix, MMTS’s in bad sites, etc. Skewed raw data (with some that just magically appears to fill the gaps) that goes through a meat grinder with the past seemingly getting colder. Before you know it, I’ll be thinking my grandpa was slinging spears at woolly mammoths.
But the fundamental error BEGINS with Hansen’s changing/editing/”updating” of the raw data differently in his original 1990 plot of land temperature records since 1910, and the more recent highly skewed results of 2002 and 2008.
Before, in his original”research” – which I only trust because that was before he began making his money and reputation selling CAGW – the 1940’s temperatures were higher than the 1990 temperatures. Later, as he needed more and more dramatic “evidence” of CAGW to maintain his lifestyle and his “religion” of CAGW, the 1940’s got cooler an cooler with new paper.
What is the raw data trends of sites that have no UHI? What is the tend in sites that have NOT been corrupted by (false ?) TOBS changes by interested observers?
What are the real thermometer readings across the 20th century US countryside?
Zeke’s post wasn’t and explanation, it was making excuses for some pretty lousy work by Hansen/GISS
1. Technical point (and I don’t think that it sways the results, but can be important sometimes): Do you compute the trends on the smoothed graphs or the real data? you should do them on the latter, but use smoothing for display purposes,
2. The recalcitrance of Lasner is typical with what I see in skeptic world and we kill ourselves with it. Way too eager to want to believe something on our side and DOGGED in giving it up instead of fair. Also, just a bit of a logic and mental gap and not quite as shrewd as we ought to be analytically.
I have one nagging question about this all ordeal:
What is called Normal temp. as a reference to Anomally? Who decides where the Normal point is and why? Beacause if we concider the long range, the Normal point is way way down, since most of the time Earth is in glacial periods, with short warm periods like now (which is also in its end).
mike says:
July 23, 2010 at 7:47 pm
“As an “alarmed” layman trying to make sense of the conflicting claims of the AGW controversy, I proposed to my Senator a way to sort the whole matter out, once and for all………….”
Mike, I like the sentiment, but it’s wrong. Your proposed tax, like many of the taxes today, punish the successful segment of our society for no other reason than they are successful. I propose that no new taxes be levied that carry an exemption for anybody. If the tax is just, then all should share the burden. It is unreasonable to expect the fruits of our nation without laboring for them.
BTW, any significant “business” that I ever engage in requires up close and personal interactions. As far as video conferences go……I’ve never been part of one that wasn’t a complete waist of time. But that’s just my experience.
I answered Bob on his “climate Observations” and Bob wrote back:
***************
Frank Lansner said…
Dear Bob.
I offered you a bottle of wine if you would go through my new article:
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php
If you had done this, you would certainly not have written as you do.
One more time. Please look at PART 2 of my article, chapter 3.4.
This is where I explain that GISS inlcudes ocean in their station data series, and where I show a graphic of the ocean included.
So if anyone is aware of this, its me. The fact that you and others keep writing that you think im not aware of ocean data in GISS station “land” data might be my fault due to bad communication.
I wrote in my article PART 4:
“I am sure that the algorithm or specific method used by GISS to combine Land temperature and SST explains some of these apparently odd findings. But whatever the “algorithm” used by GISS is, can it be justified that GISS gradually weights the warm NH-Land graph more and more? And ends up with around 67% NH land fraction in 2007 although NH only has 40% land? Maybe, this algorithm or method deserves some attention?
”
And in the WUWT article i write: http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#more-22126
I write:
“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.
”
Now, Your article, Bob:
You focus on the similarities between CRU and GISS – i suppose to say that the resulting GISS is ok?
The thing is, CRU and GISS ends up rather alike. But in CRU data i find much more direct land data adjustment than for GISS. On the contrary for GISS, the direct land data adjustments are not so big at all (to my surprice) but in stead the GISS warming trend thats similar to CRU comes when combining the SST and “land”.
SOmething thats messy in al this is, that you seem to trust that CRU land is not ocean while GISS is… Yes yes, GISS has ship and island data included, but a BIG part of the GISS ocean area in their “land” data is obviousy from coastal stations. These stations are exactly the same as for CRU. So its nonsense to say “CRU is just land data”.
Just becasue CRU says that their coastal stations are land while GISS (the same) coastal stations covers huge ocean areas, you cant just treat the same data as if completely different.
I have raised some serious problems in data, and I know you disagree strongly, but i have not seen conving arguments from you, its not bad will.
K.R. Frank
July 23, 2010 7:25 PM
*****************
Bob Tisdale said…
Frank Lansner: You wrote, “I offered you a bottle of wine if you would go through my new article:
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php
“If you had done this, you would certainly not have written as you do.”
It was my intent to eventually address your request, in a few days. I have other priorities. Also, I don’t drink alcohol. I gave it up.
You wrote, “One more time. Please look at PART 2 of my article, chapter 3.4.
This is where I explain that GISS inlcudes ocean in their station data series, and where I show a graphic of the ocean included.”
But your analysis where you assume that GISS increases land surface area does not address this.
You wrote, “I am sure that the algorithm or specific method used by GISS to combine Land temperature and SST explains some of these apparently odd findings. But whatever the ‘algorithm’ used by GISS is, can it be justified that GISS gradually weights the warm NH-Land graph more and more? And ends up with around 67% NH land fraction in 2007 although NH only has 40% land? Maybe, this algorithm or method deserves some attention?”
But GISS does NOT weight “the warm NH-Land graph more and more.” You need to mask the areas where land surface data extends out over the oceans in your analysis.
You wrote, “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.”
Please provide a link to an article written by a member of GISS where “GISS defends use of larger land fraction due to their 1200km zones around land stations reaching some Ocean areas.”
You wrote, “You focus on the similarities between CRU and GISS – i suppose to say that the resulting GISS is ok?”
I also included NCDC data. Or did you miss that? This post was not about the accuracy of land surface temperatures; it was about the contribution of land surface temperature readings to combined land and sea surface temperature data. And there is basically no difference between those of GISS, Hadley Centre, and NCDC.
July 23, 2010 8:34 PM
So we have:
Bob says :
**
You wrote, “One more time. Please look at PART 2 of my article, chapter 3.4.
This is where I explain that GISS inlcudes ocean in their station data series, and where I show a graphic of the ocean included.”
But your analysis where you assume that GISS increases land surface area does not address this.
**
Yes it does, i just gave you a few of the examples, again from WUWT:
“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.
”
To this you suggest that giss never said so, but thats another matter. GISS has used their 1200 km radius since Hansen and Lefebeff in1987 where they argue for this to be true.
And thats why i stressed, the the ODD thing is that this “land” data from GISS goes from a near blank ZERO in twenty years 1900-1920 and is then weighted strongly in recent years. Thats the problem! And as I said, if its not clear from my article its my fault, this I admit. But my point is strong and important non the less.
In my WUWT article
http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#more-22126
i even showed a graph where the land trends and Ocean trens goes opposite 1970-74 (BOTH using smoothed and 5 yr trend graphs) . So honestly i think the land vs. ocean issue was adresses in my article.
K.R. Frank
Bob then to your article, you focus on that there are land similarities between GISS, CRU and NCDC, right?
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 is why I chose to do a large work to create this article:
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php
-where i compare data publisher BEFORE the GW movement started an with data after and more.
K.R. Frank
Hi Bob,
Thanks..I enjoy your articles.
Figure 8 fits with my life experience in tropical Queensland, Australia in the periods since 1940. The time up to 1955 had dense cloud cover, many cyclones, and huge floods in summer periods. It got dryer, then in 1965, we went again back to that very wet cloudy pattern which reduced slowly after about 1976. It has been less cyclones, less floods and warmer temperatures since then. Less water vapour in the air, for whatever reasons, around the Equator seems to be a possibility..Be it Volcanos or whatever. I don’t believe CO2 alone since 1976 can cause that change, contary to the CSIRO’s constant barrage on our media.
Politics and science are like oil and water..!
One of the more interesting points raised by Frank is the departure of land temps from SST in more recent years, whereas in earlier days, the SST and land temps track each other closely. This is very clear in the above graphs in Bob’s article as well. A very strong indication that land temps are strongly contaminated by UHI (or strongly “homogenized” in recent years.
In his 4 part article linked to in his post above, Frank also compares land temps with UAH/RSS satellite records and find the same tendency. Its seems a strong indication that recent recorded warming in all the global temp products is for a large part down to UHI. This seems especially true for the GISS product.
I recommend reading Frank’s 4 part article. He raises a number of interesting points and questions beside this point that Bob now focuses on.
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php
Frank Lansner: My comment at my blog was, “But your analysis where you assume that GISS increases land surface area does not address this.”
Your reply here, “Yes it does, i just gave you a few of the examples, again from WUWT:
“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.”
##################
Frank: Let me rephrase my reply to you. But your analysis where you assume that GISS increases land surface area does not address this, because you do not mask the ocean areas where GISS has extended the land surface data out over the oceans. I’ve noted this numerous times. I wrote it in my post from last week…
http://wattsupwiththat.com/2010/07/17/giss-land-and-sea-ratios-revisited/
There I wrote, “So in order to properly create a weighted average of GISTEMP land and sea surface temperature data with 1200km radius smoothing, the land surface data where it extends out over the oceans would first need to be masked.”
I also noted it in a detailed comment to you that I posted at Jo Nova’s and at WUWT that I linked in this post. Here’s the link again:
http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#comment-435038
There, I ended with, “4.From an earlier comment at Jo Nova’s, you need to mask the land surface data.”
Have you masked the land surface data where it extends out over the oceans? No.
Bob, thanks for good answer.
You write: “Have you masked the land surface data where it extends out over the oceans? ”
No but I did a much better compare of UAH land vs. the different “land” graphs available.
As GeorgeGr just wrote:
“I recommend reading Frank’s 4 part article. He raises a number of interesting points and questions beside this point that Bob now focuses on.
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php”
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. The very same temperature data from all the “coastal” stations (the ones less than 1200 km from a coast …. !!!) are interpreted as partly ocean by GISS and yet the very same data from CRU is not viewed this way..
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?
But I have found 2 methods to learn more about these things, to validate these “land” data further, I will publish within a few days.
K.R, Frank
Frank Lansner: You replied above, “To this you suggest that giss never said so, but thats another matter. GISS has used their 1200 km radius since Hansen and Lefebeff in1987 where they argue for this to be true.”
To prove my point, that is a great example to use, Frank. In Hansen and Lebedeff (1987)…
http://pubs.giss.nasa.gov/docs/1987/1987_Hansen_Lebedeff.pdf
…they extended the 1200km smoothing out over the oceans because sea surface temperature data was so sparse. In other words, they did not merge it with sea surface temperature data. They extended the continental land, island, and ship surface station out over the oceans to simulate air temperature over the oceans.
You, however, take that dataset and assume it represents only continental land mass temperature anomalies. It does not. It represent much more.
You wrote, “And thats why i stressed, the the ODD thing is that this ‘land’ data from GISS goes from a near blank ZERO in twenty years 1900-1920 and is then weighted strongly in recent years. Thats the problem!”
You are using the GISS land surface data incorrectly, Frank. Again, you need to mask it where it extends out over the oceans. In the post above, I even included a quote to Dr. Ruedy from GISS. Here it is again, “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).” He continues, “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).”
In other words, GISS could create a land surface dataset for continental land masses but they would need to mask where the data extends out over the oceans.
You wrote, “i even showed a graph where the land trends and Ocean trens goes opposite 1970-74 (BOTH using smoothed and 5 yr trend graphs) . So honestly i think the land vs. ocean issue was adresses in my article.”
And I noted in a comment that ran at Jo Nova’s and WUWT that your land surface data looked unusual. Again, here’s a a link to that comment:
http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#comment-435038
You have since replied that you’ve tried other base years and see no difference. But I find that curious since I have shown you the differences are significant depending on the selection of base years. Here’s my attempt to reproduce your graph, using 1951-1980 as base years:
http://i27.tinypic.com/33e3kth.jpg
And here’s the same graph but in this case the base years are 1900 to 2000:
http://i30.tinypic.com/212bwxs.jpg
I will again ask you, What method of smoothing are you using? It is not a centered 60-month running-mean filter. Otherwise, your data would not have extended for the full term of the data.
Is it weighted to one side?
And have you tried a centered 60-month running-mean filter, as I asked, to see if that changes your values?
You ended your comment with, “In my WUWT article
http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#more-22126
i even showed a graph where the land trends and Ocean trens goes opposite 1970-74 (BOTH using smoothed and 5 yr trend graphs) . So honestly i think the land vs. ocean issue was adresses in my article.”
I don’t believe you have since you have not redone your analysis with the land surface data masked over the oceans, Frank. You also haven’t determined the impact of your method of smoothing. And while you claim to have tried other base years, you have not presented them. Did you try using the base years of 1880 to 2009?
trbixler says: “.3 degree C over 130 years?”
I assume you’re referring to Figure 8. As I noted in the post, …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.
# Frank Lansner says: July 23, 2010 at 11:02 pm (concerning your interesting paper, at hidethedecline/12th July, 2010)
Part 4: Perhaps we can say: „Land Temp = Sea Surface Tem“; and
Part 1: “Phil Jones, 1985, about the temperature decline after the 1930´ies: “No satisfactory explanation for this cooling exists, and the cooling itself is perplexing because it is contrary to the trend expected from increasing atmospheric CO2 concentration.”
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, and the naval activities at sea since September 1939, which was immediately followed by the extreme winters 1939/40, 1940/41 and 1941/41, the coldest winters in Northern Europe for more than 100 years , and when the naval war went global after Pearl Harbour (07 Dec. 1941) , these activities may have contributed to the yet still not explained three decades global cooling (1940- mid 1970).
Concerning winter 1939/40 in short (top left column): http://www.oceanclimate.de/A_Large_Scale_Experiment_with_Climate/A_Large_Scale_Experiment_with_Climate.pdf
Concerning WWII: http://climate-ocean.com/
PolyisTCOandbanned says: “Technical point (and I don’t think that it sways the results, but can be important sometimes): Do you compute the trends on the smoothed graphs or the real data? you should do them on the latter, but use smoothing for display purposes,”
I computed them on the smoothed data. Only the y-intercepts are different than the original Figure 8:
http://i31.tinypic.com/nx5egz.jpg
It made (and most times makes) no difference in the trends, so I took a shortcut and displayed only one graph.
Regards
rbateman says: “I am reading this as: The land surface temperature is the smaller portion of the dataset warming anomaly. The SST is the dominant factor here.”
SST data represents 70% of the surface temperature anomalies globally, and in this post with the latitudes of 60S-60N, it represents 75.5% of the data. SST is the dominant dataset. Land surface temperatures mimic and exaggerate the changes in SST due to a number of reasons, polar amplification, UHI, poor station siting, etc.
It is unscientific to discuss changes of tenths of degrees a century for the globe, when the errors are hugely larger.
Part of the misuse of science involves the vexed “anomaly” method of expression.
If you select a time period as a reference base, you have to change the reference value each time a station in the reference period is added, removed or altered. Since this is a near-continuous process, you can derive almost any “anomaly” story you wish, simply by choice of a reference set favourable to your argument. Or, for that matter, the temperatures outside the reference period, which are also added, dropped and adjusted almost continuously.
Who is interested in a fight about moving targets that are presented as a stationary time series?
Who is interested in fairy story 1200 km interpolations when stations a few km apart routinely report differences of more than a deg C?
Who is interested in filling in missing data by averaging, when the very reason for the data being missing can be because of anomalous weather?
Why, oh why cannot we simply work in real physical numbers, even if they are deg C rather than K? Why can we not select a set of truly rural stations – and then start the process of refinement and comparison?
It is untenable that much past proxy work is (probably) wrongly calibrated because one cannot get an agreed and plausible instrumented temperature series.
It’s fair amazing how the 1945-1970 decline has been steadily brought to near level over the years, by successive adjustments. Some must be phony.
Time to lift the game. Clean slates, please.
e_por says: “I have one nagging question about this all ordeal:
What is called Normal temp. as a reference to Anomally?”
Each of the global temperature anomaly data producers (GISS, Hadley Centre, and NCDC) selects the base years. And NCDC uses a number of base years, depending on the dataset. But as you’ll note in my Figure 1 above, the choice of base years has no real impact on the long-term trend. It shifts the data up and down, changing the years on the graph when the data intersects with zero degrees. There also are some minor changes in the month-to-month variations but they are the same each year.
GeorgeGr says: “One of the more interesting points raised by Frank is the departure of land temps from SST in more recent years, whereas in earlier days, the SST and land temps track each other closely. This is very clear in the above graphs in Bob’s article as well. A very strong indication that land temps are strongly contaminated by UHI (or strongly “homogenized” in recent years.”
The divergence of land surface temperatures from sea surface temperatures is not only impacted by UHI. Land surface temperatures are also affected by land use changes, polar amplification, thermal inertia, etc. Does Frank account for these in his analysis?