By Steve Goddard and Anthony Watts
Some of the excellent readers of the last piece we posted on WUWT gave me an idea, which we are following up on here. The exercise here is to compare GISS and satellite data (UAH and RSS) since the start of 2003, and then propose one possible source of divergence between the GISS and satellite data. The reason that the start of 2003 was chosen, is because satellite data shows a rapid decline in temperatures starting then, and GISS data does not. The only exception to the downward trend was an El Nino at the start of 2007, which caused a short but steep spike. Remembering back a couple of years, Dr. Hansen had in fact suggested that El Nino might turn into a “Super El Nino” which would cause 2007 to be the “hottest year ever.”
The last six years (2003-2008) show a steep temperature drop in the satellite record, which is not present in the GISS data. Prior to 2003, the three trends were all close enough to be considered reasonably consistent, but over the last six years is when a large divergence has become very apparent both visually and mathematically.
Since the beginning of 2003, RSS has been dropping at 3.60C/century, UAH has been dropping at 2.84C/century, and GISS has been dropping at 0.96C/century. All calculations are done in a Google Spreadsheet here:
The divergence between GISS and RSS is shown below. Since the start of 2003, GISS has been diverging from RSS at 2.64C/century, and GISS has been diverging from UAH at 1.87C/century. RSS has been diverging from UAH at minus 0.76C/century, indicating that RSS temperatures have been falling a little faster than UAH over the last six years, as can also be seen in the graph above.
Below is a 250km map of GISS trends from 2003-2008. One thing which stands out is that GISS has large areas with sparse or no coverage. Notably in Africa, Antarctica, Greenland, Canada, Brazil, and a few other places.
Click for larger image
Many of the GISS holes seem to be in blue regions on the map. Here is a post and video of the GHCN station loss over the past several years globally, created by WUWT contributor John Goetz:
Here are two images showing the difference between GISS global coverage in 1978 and 2008:
Click for a larger image
Click for a larger image
There is a tremendous amount of station dropout in 30 years. Dropout is worst in the high northern latitudes, most all of Canada, and about half of Africa. Of particular note is the red band at the southernmost latitude, which “seems” to indicate a continuous coverage there. Of course we know that is not true, given the paucity of stations in the Antarctic interior. Read more here.
By contrast, while it doesn’t hit both poles (neither does GISS) UAH has much broader global coverage as seen below. Could this be part of the explanation for the divergence between GISS and satellite data? What do the readers think?
![[Image]](https://i0.wp.com/discover.itsc.uah.edu/amsutemps/browse/AMSU_A_15.latest.a_04.png?resize=520%2C278&quality=75)
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![[Image]](https://i0.wp.com/discover.itsc.uah.edu/amsutemps/browse/AMSU_A_15.latest.d_04.png?quality=75)
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How different would the GISS graph appear, if it showed a -3.6C/century cooling trend over the last six years? For reference, the steep GISS warming trend from 1980 to 2002 was about 0.4 degrees.
Here’s the difference between the two GISS global coverage charts above, ie, the stations that dropped out –
http://i44.tinypic.com/258ypzr.jpg
Gentlemen: Sorry for jumping in so late. Regarding the dispute about ENSO and the sensitivity of TLT versus GISS, etc., I’ve compared the two datasets (or a facsimile thereof) over the oceans. GISS has used OI.v2 SST anomalies for their combined data since 1980. Monthly OI.v2 SST data is accessible through the NOAA NOMADS system from November 1981 to present. AHU provides oceanic data in their monthly updated datasets. The outcome:
There are significant differences between the two, in recent years and in earlier years.
Here’s the difference (Global OI.v2 SST Anomalies MINUS AHU MSU Global Ocean TLT) from January 2003 to November 2008.
http://i42.tinypic.com/2uiekcw.jpg
But here’s the difference (Global OI.v2 SST Anomalies MINUS AHU MSU Global Ocean TLT) from November 1981 to November 2008.
http://i41.tinypic.com/351fznq.jpg
And here it is inverted (AHU MSU Global Ocean TLT MINUS Global OI.v2 SST Anomalies) from November 1981 to November 2008.
http://i42.tinypic.com/v4162q.jpg
Based on that curve, the differences for the oceans appear to result from the sensitivities of the two variables to ENSO events.
Regards.
Anthony says:
Fair enough…But, if I might throw out my own views (which may or may not be what Steve Talbot was thinking in his comment that you were replying to), what seems to happen here is that a lot of the commenters (and presumably many of the lurkers) take your analysis and jump to conclusions that are completely unwarranted because a more complete analysis would likely not support them. So, if you want to inform rather than misinform, it seems to me that it would work best to first be really really clear on the limitations of your own analysis from the start and second to point out to those who are jumping to unwarranted conclusions that those conclusions are not warranted from your analysis (which I have seen you do occasionally when people really step over the line and start tossing around accusations of fraud).
Of course, far be it from me to tell you how to run your blog…But I am just trying to give some constructive criticism!
Whoops…I screwed up the coding on my previous post, but the first paragraph is Anthony’s words and the other two are mine.
REPLY: I fixed that for you. I welcome the suggestions. – Anthony
But note that the station dropouts don’t seem to have made any difference. To get a rate of change of global temperatures over time, you probably don’t need more than a few dozen stations globally.
REPLY: Gavin Schmidt once said that “only 60 stations are needed”. The surfacestations.org project will identify those best stations, (at least initially for the USA) and once we have done so, we should be able to cull a surface dataset with a higher confidence level. The way it is going thus far, the best stations represent ~ 10% of the total USHCN station set. For GHCN, I anticipate that number being even lower because of the dropout issue as well as the fact that a larger majority of GHCN stations are at airports than the USHCN station set. – Anthony
Roy (17:27:07)
I don’t think anyone but the very few principals know the answer to your imputed question. It is unseemly to talk of motive without evidence, but there are plenty who wonder. The passion with which Hansen addresses his subject makes one wonder whether he might justify fudging the numbers for a great cause, but frankly, the record is so confusing that motives can not be discerned with accuracy. I don’t doubt that Hansen started out with good intentions, truly might still have them, for the road to paradise is paved with good intentions. You have to watch your step on that road and pay attention to directions and roadside thermometers, or it is easy to lose your way. I think he’s lost, and really, I pity him.
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Isn’t AGW a case of analysis with the jump to a conclusion?
Don’t we have to wait for the future to see if the conclusion is really valid?
Andrew
Delta often tell stories.
http://www.gpsl.net/data/tempdiffs1a.png
GISS March 2008, region Jan through April. what happened?
I wonder if that is a clue on a network sensitivity to winter or summer in one region of the world?
(delta month from next month and plot, X is N-1)
crosspatch (18:31:15): “But note that the station dropouts don’t seem to have made any difference.”
On what basis do you make that statement?
Expanding on my earlier comment, the TLT anomalies and SST anomalies for some oceanic subsets correlate well. Others are so different I’ve had to go back and double check the data. The following are comparative graphs of TLT and SST for specific ocean subsets I’ve prepared for a post I’m writing now about the dominance of ENSO and volcanic eruptions on segmented TLT data for the Northern Low Latitudes.
LOW LATITUDE NH TLT vs SST
The Northeast Pacific data correlate relatively well, and they should since most of the north half of the NINO3.4 area is within that area of the Northeast Pacific. (The coordinates for the Northeast Pacific low latitude data are 0-30N, 180W-122W.)
http://i42.tinypic.com/2iw55cj.jpg
The North Atlantic data diverge at times. (The coordinates for the North Atlantic low latitude data are 0-30N, 62W-12W.)
http://i39.tinypic.com/sfvw9z.jpg
And in the Northwest Pacific, there is little correlation between the two datasets. (The coordinates for the Northwest Pacific low latitude data are 0-30N, 145E-180E.)
http://i44.tinypic.com/2lad15s.jpg
MID LATITUDE NH TLT vs SST
Also, I took a look at the Mid Latitude Northern Hemisphere TLT and SST data in a post titled “El Ninos Create Step Changes in the Northern Hemisphere Mid Latitudes” (catchy title, huh?):
http://bobtisdale.blogspot.com/2009/01/el-ninos-create-step-changes-in-tlt-of.html
The Northeast Pacific data correlate better than most. (The coordinates for the Northeast Pacific mid latitude data are 30-60N, 180W-122W.) Figure 9 in the post.
http://i41.tinypic.com/14buptf.jpg
The North Atlantic data diverge most times. (The coordinates for the North Atlantic mid latitude data are 30-60N, 62W-12W.) Figure 12 in that post.
http://i41.tinypic.com/zl5g93.jpg
But the Northwest Pacific data correlate pretty well in comparison to the others. (The coordinates for the Northwest Pacific mid latitude data are 30-60N, 145E-180E.) Figure 15 in that post.
http://i42.tinypic.com/2058prq.jpg
“Isn’t AGW a case of analysis with the jump to a conclusion?”
Not really, it was a conclusion followed by analysis hoping to validate the conclusion. In this case the chicken came first.
“On what basis do you make that statement?”
Because in a previous thread you can see that when the stations dropped out, there was no sudden change between the ground-based and satellite-based measurements.
“The surfacestations.org project will identify those best stations, (at least initially for the USA) and once we have done so, we should be able to cull a surface dataset with a higher confidence level.
Would love to see the list. I don’t think that even long to medium range forecast models would be worth much with only 60 reporting stations worldwide.
The world has cooled since 2003 because that is when the oceans starting cooling. Craig Loehle has a paper in press on this subject.
Looked at the correlations between the ENSO time series and the UAH data set.
The match is really bad using raw data. I shifted the ENSO data (http://www.cdc.noaa.gov/people/klaus.wolter/MEI/table.html) 6 months and divided by 6 to make the peak values closer to the temperature data. I then adjusted both the ENSO data and the UAH data so that the average slope from 1979 to 2008 was zero by applying a linear transformation to the data. The correlation coefficient for a linear fit to a scatter plot of MEI adjusted to UAH adjusted was 0.188 for the whole series and 0.644 for 1995 to present. Visually there is a good match for the recent data but not so much before 1995 which is verified by the correlation coefficients.
I have a plot of the time series for GISS UAH and ENSO (MEI) data on a crude plot. The MEI data has been divided by 6. The plot uses the Excel smooth line function.
http://gallery.me.com/wally#100002/ENSO%20vs%20UAH%20GISS&bgcolor=black
Correction: the plot in the previous plat used 13-month smoothing and the Excel smoothing line plot. 19:09:29
@ur momisugly David Archibald
David, you really let it all hang out with the prediction of over -.4C in May. How confident are you or was it basically a SWAG (or less)?
Over and over again we see the same error, but it is not fraud in changes to the numbers: Link http://wattsupwiththat.com/2009/01/14/distribution-analysis-suggests-giss-final-data-is-hand-edited/ . So the disregard to some of the stations use/used?
Anthony we are getting to a point that we need your certifying of stations
1,2-3,5 and run numbers on 1,2 V 3,5
we are running out of time… here comes January 19 (part A) ,20th (part B)
And BO well be making desions on lack of, or faulty data (not fraud) , just like W got on Iraq!
God help us all
Tim
Joel Shore,
How many temperature stations per square mile are there for the ocean areas???
Your reasoning is hopeful rather than factual.
C’mon, folks. Y’all have to respect NASA, James Hansen and GISS. There are many reasons to accept GISS data over the silly satellite data:
1) The ground-based GISS information is provided by THE premiere scientific agency in the world; after all, they sent guys to the moon, for crying out loud. How can you question the almighty NASA ?
2) The data is provided by NOAA stations and foreign stations which have impecable quality control procedures in place, as documented by Anthony Watts. You can be assured that any irregularities, such as BBQs under the temperature sensors or jet engines blowing on the sensors, have been addressed by the NASA experts, with computer-aided adjustments.
3) NASA has reviewed all the literature concerning UHI effects and determined that there is a very minor influence, which has been incorporated into computer programs that adjust the temperatures accordingly.
4) Adjustments have been made to lower all the temperatures in the ’30’s, because the thermometers and recording procedures back then sucked big time. This makes the temperatures of the latest part of the 20th century look high, but that is because NASA knows that CO2 is making them high.
5) You just gotta trust a governmental agency. After all, what motivation could they possibly have to fake anything or screw up? And have you ever seen a governmental agency screw up?
6) Computer programs, although written in Fortran, almost unintelligible, and not subject to any known QA/QC programs, have been posted on the Internet for your perusal.
Oh, and these brilliant people have also produced a computer model that tells us what the temperature will be in 2100!
Crosspatch,
You are right. I don’t want to see any more analysis and re-analysis ‘supporting’ AGW. The analysis has already been done. It’s a waste of time since we already know what’s going on. The science is in. Nothing else needs to be studied, scrutinized and no more questions need to be asked. No more papers with more evidence, ’cause we don’t need any. No more jumping to conclusions. We don’t need to wait for the future to see what happens.
Andrew
Joel Shore (18:09:28) :
“In other words, they understand the limitations in drawing conclusions from their data better than you do.”
You mean something like claiming we only have 4 years to save the planet? One might think that was a little more extreme than the current discussion. One might also think that “understand the limitations” is NOT something “they” have been practicing.
DR, when you look at the UAH data you will see that since 2001 there is a seasonal fall of 0.3 between December and May, most of the time. You will also see that an El Nino is good for +.2 or more and a La Nina is good for -0.3 or so. We are currently in a big La Nina, so add 0.3 to the 0.3 seasonal fall and you get 0.6 lower than where we are now.
kim:
“I think he’s lost, and really, I pity him.”
Me, too.
I agree with several posters that the absence of ocean coverage in the GISS is alarming. In my opinion, to leave out 70 per cent of the surface of the planet is a fatal flaw of their data.
Statistical and sampling theory permits that a random sample of a whole may be used to make an estimate of a certain property in the entire statistical population (eg political opinion polls usually cover only a few thousand people only). But the key to the sample’s accuracy is its randomness and representativity of the entire statistical population. To leave out oceans entirely inserts an inherent bias because it is well known that ocean temperatures do not behave the same as land temperatures (eg they move slower) and because oceans aren’t affected by urban heat island effect.
GISS is utterly corrupted and useless.
R.I.P.
crosspatch:
“To get a rate of change of global temperatures over time, you probably don’t need more than a few dozen stations globally.”
Ok – I’ll bite. Please tell me where these few dozens should be sited. The variablility in the many and varied areas of the continental US would justify your “few” all by itself, yet comprises little of the NH landmass.
Personally, I think the more the merrier, with respect to proper siting and orientation, no more “adjustments” and probably automate them. It would give us an opportunity to study climates relationship to weather…that last is a little joke.