By Steve Goddard
We are all familiar with the GISS graph below, showing how the world has warmed since 1880.
http://data.giss.nasa.gov/gistemp/graphs/Fig.A2.lrg.gif
The GISS map below shows the geographic details of how they believe the planet has warmed. It uses 1200 km smoothing, a technique which allows them to generate data where they have none – based on the idea that temperatures don’t vary much over 1200 km. It seems “reasonable enough” to use the Monaco weather forecast to make picnic plans in Birmingham, England. Similarly we could assume that the weather and climate in Portland, Oregon can be inferred from that of Death Valley.
The map below uses 250 km smoothing, which allows us to see a little better where they actually have trend data from 1880-2009.
I took the two maps above, projected them on to a sphere representing the earth, and made them blink back and forth between 250 km and 1200 km smoothing. The Arctic is particularly impressive. GISS has determined that the Arctic is warming rapidly across vast distances where they have no 250 km data (pink.)
A way to prove there’s no data in the region for yourself is by using the GISTEMP Map locator at http://data.giss.nasa.gov/gistemp/station_data/
If we choose 90N 0E (North Pole) as the center point for finding nearby stations:
We find that the closest station from the North Pole is Alert, NWT, 834 km (518 miles) away. That’s about the distance from Montreal to Washington DC. Is the temperature data in Montreal valid for applying to Washington DC.?
Even worse, there’s no data in GISTEMP for Alert NWT since 1991. Funny though, you can get current data right now, today, from Weather Underground, right here. WUWT?
Here’s the METAR report for Alert, NWT from today
METAR CYLT 261900Z 31007KT 10SM OVC020 01/M00 A2967 RMK ST8 LAST OBS/NEXT 270600 UTC SLP051
The next closest GISTEMP station is Nord, ADS at 935 km (580 miles) away.
Most Arctic stations used in GISTEMP are 1000 km (621 miles) or more away from the North Pole. That is about the distance from Chicago to Atlanta. Again would you use climate records from Atlanta to gauge what is happening in Chicago?
Note the area between Svalbard and the North Pole in the globe below. There is no data in the 250 km 1880-2009 trend map indicating that region has warmed significantly, yet GISS 1200 km 1880-2009 has it warming 2-4° C. Same story for northern Greenland, the Beaufort Sea, etc. There’s a lot of holes in the polar data that has been interpolated.
The GISS Arctic (non) data has been widely misinterpreted. Below is a good example:
Monitoring Greenland’s melting
The ten warmest years since 1880 have all taken place within the 12-year period of 1997–2008, according to the NASA Goddard Institute for Space Studies (GISS) surface temperature analysis. The Arctic has been subject to exceptionally warm conditions and is showing an extraordinary response to increasing temperatures. The changes in polar ice have the potential to profoundly affect Earth’s climate; in 2007, sea-ice extent reached a historical minimum, as a consequence of warm and clear sky conditions.
If we look at the only two long-term stations which GISS does have in Greenland, it becomes clear that there has been nothing extraordinary or record breaking about the last 12 years (other than one probably errant data point.) The 1930s were warmer in Greenland.
Similarly, GISS has essentially no 250 km 1880-2009 data in the interior of Africa, yet has managed to generate a detailed profile across the entire continent for that same time period. In the process of doing this, they “disappeared” a cold spot in what is now Zimbabwe.
Same story for Asia.
Same story for South America. Note how they moved a cold area from Argentina to Bolivia, and created an imaginary hot spot in Brazil.
Pay no attention to that man behind the curtain.
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No wonder it’s warming so much at the Poles. There’s that big hole at each Pole extending all the way through the earth. Heat from the core of the earth, which is at several million degrees, is pouring out. 😉
stevengoddard says: July 26, 2010 at 10:48 pm “jose
_Anomalies vary tremendously over short distances”
# # Post: Note the area between Svalbard and the North Pole in the globe below. There is no data in the 250 km 1880-2009 trend map indicating that region has warmed significantly, yet GISS 1200 km 1880-2009 has it warming 2-4° C.
Not only distant but also seasonal anomalies can be significant as it happened during the period 1919-1940, with an extraordinary warming in the Arctic during the winter season – http://www.arctic-warming.com/ — while the summer temperatures changed only very little. .
Discussing annual average may make it difficult to detect significant differences. With regard to Spitsbergen and the arctic warming 90 years ago (details : http://www.arctic-warming.com/g.php ), the winter warming could only have been supplied by the Northern North-Atlantic, as any direct sun contribution, at this high latitude, can be ignored during the winter season.
Regardless on how GISS handled the available data from and around Spitsbergen in the 1910s , (Data: Jan/Feb::__ http://www.arctic-warming.com/f.php __) the warming is evident and effected the whole Northern Hemisphere, and had been recognised very soon.
( Ifft; George N. 1922, „The Changing Arctic”, Monthly Weather Review, Nov 1922: “Ice conditions were exceptional. In fact, so little ice has never before been noted. “; The Washington Post, Nov. 2, 1922 edition; “ Arctic Ocean Getting Warm; Seals Vanish and Icebergs Melt”..) ,
At least in the Spitsbergen case any generalisation should be met with reservation. .
Nick Stokes says: July 27, 2010 at 1:27 am
“Yes. it is.. Here’s the plot. Lots of correlation.”
Uhmm, Nick, looking at the graph, I see lots of correlation from about 1910-1950. But beyond that, no, not so much. In fact, from about 1950-1970, the anomaly looks inverted. According to your graph, it looks like Montreal gave up measuring their own temp about 1980. It looks like the graph starts about 1870 and ends with both about 1980 for a total of 110 years. Mont. and D.C. correlate very well for 40 yrs. Somewhat for 50 years and not at all for 20. Remember this is an anomaly graph not a temp graph, so similar shapes(bumps) aren’t correlation unless they are very close to each other. So, no, it isn’t correct to say Montreal and D.C. correlate. Sorry
Doubting Thomas says:
July 26, 2010 at 11:44 pm
Don’t panic. All those great scientists we have in the U.S. congress are looking into the GISS data. I can’t wait to see the cover-up. The cover-up is always the best part.
– dT
(Are there any scientists in congress? Any engineers?)
……………………………………………………………………………………………………………….
There are a couple. But they are few. Mostly it’s this:
“Suppose you were an idiot. And suppose you were a member of Congress. But I repeat myself.”
~Mark Twain
“It uses 1200 km smoothing, a technique which allows them to generate data where they have none – based on the idea that temperatures don’t vary much over 1200 km”
That’s incorrect. It is observed that there is a correlation between temperature anomalies at widely spaced locations. In fact, the correlation coefficient is 0.5 or higher out to distances of 1200km at temperate latitudes. The GISS methodology for calculating the temperature anomaly at a given point includes all data from within 1200km, with a weighting that varies linearly from 1 at 0km to 0 at 1200km.
“We find that the closest station from the North Pole is Alert, NWT, 834 km (518 miles) away. That’s about the distance from Montreal to Washington DC. Is the temperature data in Montreal valid for applying to Washington DC.?”
I got hold of weather station data from Montreal and Washington, choosing the station from each which had the longest record. I calculated the mean January temperature, and then subtracted it from the series, to convert it from absolute temperature to temperature anomaly. I calculated the correlation between the anomalies at the two locations. I found a Pearson coefficient of 0.75, which implies a significant correlation. So yes, if one had no data for Washington, one could make a pretty good guess at its temperature anomaly using Montreal data, and vice versa – at least for January. You may be interested in extending this analysis to the rest of the year.
It is always better to analyse the actual data, rather than argue from disbelief. Also, you should report correctly what the methodology actually is.
Bob,
I don’t find the fact that “the linear trends of the three global land surface temperature anomaly products from 1880 to 2009 are remarkably similar between the latitudes of 60S-60N” to be particularly interesting.
Hansen says that the reason GISS has diverged from HadCrut over the last decade is due to the Arctic.
And all three suffer from UHI and other issues.
“Note: Gray areas signify missing data.”
“David, Mr Goddard did not make clear what is being plotted here. It isn’t simple interpolation. The colors represent trends over 130 years, and the gray areas in the 250km plot show where info was not available for the full period. But that does not mean that there was no information there.
When GISS plots the 1200km trend plot, for most years they use the local data, which don’t appear in the 250km plot. They only interpolate to fill in the missing years.
”
So, when they compute the “global temperature average” to determine whether warming has happened or not, are they using fabricated, smoothed, and infilled data, or only the actual hard measurements?
If you answer that they use the smoothed data, then the trend is going to have exactly the same problem outlined here… they’re creating a ficticious baseline based on guesses to compare to (since, as you say, they don’t have measurements in south america and africa) in addition to the smoothing “spreading around” the heat with 1200 km distances.
Steve Goddard: You wrote, “Similarly, GISS has essentially no 250 km 1880-2009 data in the interior of Africa, yet has managed to generate a detailed profile across the entire continent for that same time period. ”
Actually, they do have data for the interior of Africa:
http://i25.tinypic.com/2z7lrty.jpg
They simply do not meet the 66% record threshold GISS uses for creating trends.
Bob Tisdale:
“Since the maps with 250km radius smoothing have much less data from which to create trends (than the maps using 1200km radius smoothing), the trends will be different.”
But it’s not “data.” Data is a measurement, not a guess. The 1200km smoothing creates the APPEARANCE of data where data doesn’t exist, then uses the fabricated data to generate a trend line which is ultimately meaningless.
Bob,
If they “do not meet the 66% record threshold GISS uses for creating trends” then they shouldn’t be in their trend maps.
I’m surprised that you are defending them.
The graph Fig.A2.lrg.gif at the top purports to show that global temperatures have increased by about 8 degrees C between 1900 and 2000.
I’ve seen plenty of weather stations around the world where the temperature has been flat over that period, or has risen less than one degree, or has dropped.
Can anyone give me the names of any of the weather stations used to produce the above graph where the temperature has risen by 8 degrees C or more over the hundred years?
I wish to check.the data for those weather stations.
Since most weather stations will have scarcely risen at all, there must be some very very hot ones somewhere. Or the graph is wrong.
My government has just imposed an Emissions Trading tax, partly on the basis of that graph.
The NZ Minister of Climate Change showed a similar graph in a slide show last week, with a graph of CO2 growth also plotted to attempt to show how the two have moved together.
It’s very disappointing that many of you don’t understand some basic principles of meteorology and climate.
OVER LAND, regional temperature trends must correlate! I repeat: “REGIONAL” trends.
Coastal stations, instead, must not be used to infer trends over the sea.
All that means that, as a climate land region is identified, almost all the land stations over there must have a similar trend. If a station doesn’t correlate, it’s because of some non climatic influence.
Different reasoning is needed for coastal stations. It is not garanteed, in fact, that sst and air temperature have always the same trend or a trend of similar magnitude.
As an example, think at the Arctic Ocean. Over there, air temperature at a 2m elevation is bounded by the presence of ice or a mixture of ice and water. In coastal Siberia, instead, Summer temperature are free to climbe to +30° under some meteorological conditions. An anomaly of, say, +10 °C, over Siberia can’t be found over the Arctic Ocean, wathever Hansen thinks.
The only problem I see, is to identify climate regions. In some areas, 1200 km could also be a good approximation, in others is not. It depends on latitudine, geography and climate.
HAS: From a naive empiricists point of view isn’t the issue here the error limits around the various estimates of temperature (and then of trends)?
.
Yes. And the error can be quantified.
BBk says:
BBk, you have a very wrong idea about interpolation. Everything anyone says about any spatial field is based on interpolation. You can’t measure every point – you have to settle for a finite subsample which then represent the rest. So it’s meaningless to harrumph about “fabricated” data.
When you compute a global average, no explicit interpolation is necessary. You can interpolate points and then add them if you want but the summed result is still just a combination of the data points – just with different weighting. Where points are sparse, you’re just regarding them as representing a larger area. That increases the error range.
Paolo: The only problem I see, is to identify climate regions. In some areas, 1200 km could also be a good approximation, in others is not. It depends on latitudine, geography and climate.
.
I think that is an excellent point and a question within the ability of several of the technical bloggers. Its a question with an answer (even if I don’t have one at hand).
BBk replied: “But it’s not ‘data.'”
The numerical values created by 1200km radius smoothing is data. It might be data derived through methods that you disagree with, but it is data.
To the assertions that GIStemp uses different data for the 250 vs 1200 km plots:
The SAME data is fed into GIStemp for both. GIStemp will ‘spread it around’ from where it really is (a single point for each station) to either a 250 or a 1200 km distance.
Depending on which “STEP” in GIStemp you look at, this may or may not be used to ‘fill in missing data’. The version of code that lets you choose the range is not the version that I’ve worked with, so I’m not certain exactly where they do it in the web plots. But in the non-web portion of the code (that OUGHT to be used to make the web plots) the distance of the ‘spread’ is a parameter. I’d expect the ‘spread’ to be done mostly in the “STEP3” part of GIStemp where it calculates the anomalies (what is on the plots) for each grid/box and where you have a parameter for the size of the ‘spread’ used. By that time, all the ‘homogenizing’ infilling and the UHI adjustments have been done (and with their own different distances of spread. 1000 km IIRC in the version of GIStemp from last year.)
So the actual temperatures will have been spread around via homogenizing and UHI adjustments long before you get to the Grid/Box step and set it to 250 or 1200 for that step. The same data will be used from the same real point sources in both cases, though the stations that get merged together into any one grid/box will change with the size of the box.
Yeah, kludgey.
http://chiefio.wordpress.com/2009/11/09/gistemp-a-human-view/
stevengoddard replied, “If they ‘do not meet the 66% record threshold GISS uses for creating trends’ then they shouldn’t be in their trend maps.”
They aren’t in the trend maps. That’s the point. The trends for Central Africa, and Asia, and South America do not appear in the trend maps with 250km radius smoothing because they don’t meet the data availability threshold for the maps you’re creating on the GISS webpage. But with the 1200km radius smoothing, more data exists, and because of the increase in data availability, the trend maps for the GISTEMP product with 1200km radius smoothing are more complete. You may disagree with how GISS creates the data with their 1200km radius smoothing, but the increase in data is the reason for the differences in trends and their spatial completeness.
You wrote, “I’m surprised that you are defending them.”
I’m not defending anyone or anything. I pointing out errors to you that exist in your post.
Cool it down babies!
http://weather.unisys.com/surface/sst_anom.html
stevengoddard replied, “I don’t find the fact that ‘the linear trends of the three global land surface temperature anomaly products from 1880 to 2009 are remarkably similar between the latitudes of 60S-60N’ to be particularly interesting.”
Others might find it interesting, Steve, which is why it was a general comment and not addressed to anyone in particular.
You continued, “Hansen says that the reason GISS has diverged from HadCrut over the last decade is due to the Arctic.”
If the only difference of any value is the Arctic, then why does your post include trend maps for Africa, Asia, and South America? You introduced the lower latitudes, not me.
You wrote, “And all three suffer from UHI and other issues.”
“UHI and other issues” are not the subject of your post.
Bob,
Why don’t you write up a separate article about the issues you find interesting?
The point of this article was to show that the GISS 1200 km smoothing is inconsistent with their 250 km smoothing – and that they are claiming to know long term trends in places where there is little or no data .
Do you disagree with that thesis?
“Even worse, there’s no data in GISTEMP for Alert NWT since 1991. Funny though, you can get current data right now, today, from Weather Underground,”
Arr, well that would be because the Alert NWT weather station was originally run by the Royal Canadian Airforce and in the 1990’s control was handed over to the Canadian Environmen ministry. Sadly it seems nobody in team AGW could bother themselves to find out why 20 years of the most recent data was missing from this fine site, but then again it doesn’t show warming in the period 1951 to 1990 so why bother??? If they had gone to the Canadian Environment ministry I suspect they would have got the complete record.
Hi Steve,
“GISS Swiss Cheese”, by the way:
can you explain why among the GISS data for Switzerland (there are several stations mentioned: Geneva, Basel, Zurich, Saentis, Gotthard, stBernhard, Payerne, Jungfraujoch) there’s only one them – Saentis – showing the whole timescale from 1880 until 2010 (have a look at the graph around 1919!) . All the others stop in the eighties, some even in the sixities.
Thanks
JonK
Bob,
Your explanation is unpalatable.
The GISS maps say that grey areas represent missing data. If they can’t calculate an accurate 250 km trend for a limited area, then they certainly can’t calculate an accurate 1200 km trend over a larger area.