Part 1 of Comparison of GISTEMP and UAH MSU TLT Anomalies
Guest Post by Bob Tisdale
Note 1: The data illustrated in the following graphs are as I downloaded them from the KNMI Climate Explorer website. I made no effort to offset either dataset in the comparative graphs so that the two curves rested on one another. The graphs will show that GISTEMP anomalies are higher than UAH MSU TLT anomalies. This is a function of base years. Focus on the trends and the shapes of the curves, not the location of the curves.
Figure 1 is a comparison of Global GISS Surface Temperature (GISTEMP) and UAH MSU Lower Troposphere Temperature (TLT) anomalies. Both datasets have been smoothed with 12-month running-average filters.
http://i41.tinypic.com/34ryski.jpg
Figure 1
Similar graphs always create speculative comments about the basis for the differences between GISS and UAH data. In this post, I’ve segmented the globe, Figure 2, to locate the areas with the largest differences, in an effort to narrow the possible reasons for those divergences. The coordinates used are listed on the graphs. I’ve plotted the data and added the linear trends, but I have not speculated about the causes for the differences in the data for the smaller global areas.
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Figure 2
Note 2: GISTEMP data through the KNMI Climate Explorer is available with 250 km and 1200km smoothing. The graphs in the post use the 1200 km smoothing, which is the smoothing presented by GISS in their GISTEMP product. Figure 2, however, is the May 2009 GISS Global Temperature Anomaly map with 250km smoothing. Grey areas indicate locations with no data. These are the areas infilled by the 1200 km smoothing.
Note 3: Also keep in mind that the MSU TLT data reaches to 82.5N and 70S. The approximate locations of those latitudes are shown in Figure 2. UAH also fills in the polar data. On the other hand, MSU data has better global coverage in other areas where surface station data is lacking.
Note 4: And for the last note before looking at graphs and EXCEL-calculated trends, keep in mind that GISTEMP and UAH MSU TLT represent datasets made up of different variables. GISTEMP is composed of Sea Surface Temperature (SST) and of Land Surface Temperature data based on surface station readings. The UAH MSU TLT data represents the temperature of the lower troposphere.
COMPARISONS
Figure 3 illustrates GISTEMP and UAH MSU TLT anomalies for the Arctic, 65N to 90N. The GISTEMP linear trend for the period is 0.0595 deg C/decade while the UAH MSUTLT data has a linear trend of 0.0461 deg C/decade. Note how the GISS data exaggerates (or the UAH MSU data suppresses) the variations, especially after mid-2004.
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Figure 3
The North America Plus datasets, Figure 4, also include the Eastern North Pacific and the majority of the North Atlantic. The trends are significantly lower than the Arctic datasets, as would be expected. The linear trend for the UAH MSU TLT data (0.0185 deg C/decade) is greater than the trend for the GISTEMP data (0.0159 deg C/decade).
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Figure 4
The South America Plus datasets, Figure 5, also show a UAH MSU TLT linear trend (0.063 deg C/decade) that is higher than the GISTEMP trend (0.05 deg C/decade). These datasets also include major portions of the eastern South Pacific and western South Atlantic. Both linear trends are again significantly lower than the North American Plus datasets. Note the dominance of the ENSO signal in the South American Plus data.
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Figure 5
The Europe Plus datasets show the highest trends of those examined in this post. This should be due to the impact of the North Atlantic on Europe. As illustrated and discussed in my post “Putting The Short-Term Trend Of North Atlantic SST Anomalies Into Perspective”, the linear trend of the North Atlantic SST anomalies is more than 2.5 times the dataset with the next highest trend. The GISTEMP trend (0.429 deg C/decade) for the Europe Plus dataset is slightly higher than the UAH MSU trend (0.379 deg C/decade).
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Figure 6
The difference in linear trends is greatest in the Africa Plus datasets, Figure 7. The GISTEMP linear trend at 0.194 deg C/decade is more than twice the linear trend of 0.093 deg C/decade for the UAH MSU data.
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Figure 7
For the Asia Plus subsets, Figure 8, the GISTEMP linear trend (0.256 deg C/decade) is also higher than the UAH MSU linear trend (0.179 deg C/decade). The Asia Plus datasets have the second highest linear trends of the areas illustrated in this post.
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Figure 8
The comparison of the Australia Plus datasets, Figure 9, illustrates another occasion when the GISTEMP linear trend (0.076 deg C/decade) is less than the USH MSU linear trend (0.096 deg C/decade).
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Figure 9
The first thing that stands out in the comparison of Antarctic datasets is the difference in the signs of the linear trends. The GISTEMP data show a positive trend of 0.048 deg C/decade, while the UAH MSU data show a negative trend, -0.091 deg C/decade.
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Figure 10
The Antarctic datasets are also the noisiest of those illustrated in this post. But the real curiosity is the timing of the mid-to-late 1990s spike in the GISTEMP Antarctic data. At first glance, it appears to be a result of the 1997/98 El Nino. But the spike is more than a year early. In Figure 11, scaled NINO3.4 SST anomalies have been added to the comparative graph of Antarctic Plus GISTEMP and UAH MSU TLT data. The spike in the GISTEMP Antarctic data is not a response to the 1997/98 El Nino.
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Figure 11
Figure 12 illustrates the GISTEMP Surface Temperature and the two components of it: GISTEMP Land Surface Temperature, and OI.v2 SST data for the Southern Ocean. The source of the anomalous spike in the mid-1990s is the GISTEMP Land Surface Temperature data, not the SST data.
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Figure 12
Note 5: The GISTEMP Surface Temperature data from 90S to 60S is clearly dominated by the GISTEMP Land Surface Temperature data, though the surface area of the Southern Ocean (20.3 million sq km) is greater than the land mass of Antarctica (14.0 million sq km). This appears to be a function of Southern Hemisphere sea ice area, which can vary from 1.5 to 16.5 million sq km over the course of a year. During the winter, sea ice area increases. The land surface area then becomes greater than the sea surface area, making it the dominant dataset.
CLOSING COMMENT
I do not recall any discussions of a 1996 spike in the GISTEMP Antarctic surface temperature data. I have double-checked to assure I downloaded the data correctly. However, I have not tried to confirm whether or not the 1996 spike occurs in the individual Antarctic surface station data available from GISS:
http://data.giss.nasa.gov/gistemp/station_data/
A gif animation of the annual GISTEMP maps, Figure 13, does show elevated Antarctic surface temperatures in 1996.
http://i39.tinypic.com/2mwdopx.gif
Figure 13
SOURCE
THE GISTEMP Surface Temperature, GISTEMP Land Surface Temperature, UAH MSU TLT, and OI.v2 SST data are available through the KNMI Climate Explorer website:http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Posted by Bob Tisdale at 7:02 AM
gt (21:50:02) : Alright, we can agree that there’s an upward trend for temperature.”
We agree. But that’s irrelevant. For the “most sophisticated and spatially intensive weather collection system in the world” ie. North America, the average increase of the two data sets is 0.172 deg C/century. Tell me, how much will that increase sea level, cause starvation, kill polar bears, cause cancer, induce infertility, etc., etc., etc. From this analysis, the problems between the two datasets reside in areas with poor spatial distribution (for example, gray areas in Africa, Arctic), where Gisstemp imposes a flawed fill-in technique (similar to Steig et. al.).
Africa truly is the ‘heart of darkness’ where GISS is concerned.
A small correction,but for the Arctic graphs, either the slopes on the graph are mysteriously per decade, or the text should read 0.595 deg C/decade and 0.461 deg C/decade (i.e., 10x what it currently reads).
jmrSudbury (03:11:32) :
“gt (21:50:02) : Alright, we can agree that there’s an upward trend for temperature.”
“You would be hard pressed to find anyone who does not agree that there was an upward trend in the 80s and 90s. — John M Reynolds”
Not sure what you really mean here, but as to the upward trend in the 80 -90s, I’m hard pressed to find much of an upward trend at all, at least until the 1998 El Nino.
http://wattsupwiththat.files.wordpress.com/2008/09/uah_august2008.png
Very informative post, Bob. Any chance you are able to dissect Asia into north and south? I would be interested in the difference in trends that can be attributed to North Asia and Africa combined. It has been widely noted elsewhere that the former USSR record has problems such as rural-to-urban station dropout, and the African history is as much a guess as it is science (and should probably be omitted from the ‘global’ temperature history series).
Tim Clark (08:01:46)
Opps, forgot to say; good analysis Bob! I’m counting on you to keep me posted on ENSO. I’ve got a lot of money riding on it. ;~0
Another thorough, sober and informative analysis, thanks.
Igsy: You asked, “Any chance you are able to dissect Asia into north and south?”
In the second post, I’ve provided a look at Asia in general and that Soviet Union “Hot Spot”.
You wrote, “I would be interested in the difference in trends that can be attributed to North Asia and Africa combined.”
As noted in this post, I use the KNMI Climate Explorer for the data. It’s a coordinate-based system. The UAH MSU TLT data at KNMI, unfortunately, is not divided into Land or Ocean data, so I can only grab portions of each continent, in an effort to reduce the effects of any mixing of Land or Ocean data. Therefore, for the land and ocean comparisons, Parts 2 and 3 of this post, I can’t combine two continents without getting ocean data in there too.
A lot of instances of “degrees per decade” need to be changed to “per annum” or multiplied by ten.
DR (06:26:48) :
Uh, no. Satellites measure bulk atmospheric temps. Those effects would largely be restricted to the surface and not far beyond certain areas. Satellite would be negligibly influenced by them.
Adam (21:02:08) : I wouldn’t be surprised if that region had the best data, however it should be remembered that trends higher up are generally supposed to be greater.
Bob:
A real interesting result would be if you scaled the satellite and surface data so that their interannual variability matched. ENSO events appear to have a larger impact aloft for instance. I try to make use of this with HadCrut and UAH annual data to figure out what the biases in the data are:
http://www.climateaudit.org/phpBB3/viewtopic.php?f=3&t=740
My conclusion is that the satellite data indicate significant bias in the surface data.
One thing that jumps out at me right away is how much influence El Nino and it’s aftermath (as outlined by Bob) has influenced the linear trend of temperature. Take away the El Nino peak alone (never mind the aftermath) and the trends are considerably less (for UAH). Look at Africa, SA, Australia, even the Arctic. By eyeballing it, they have insignificant trends are even negative trends pre ~ Oct 1997. Europe seems to run to a different drummer – AMO perhaps. Maybe I’m biased so time to try and repeats Bob’s work looking at pre/post El Nino.
Eagerly awaiting parts 2 and 3.
Hey, have you seen the series of record high temperatures in Texas? The highest daily temp in San Antonio and Austin were broken, and it’s going to continue for a week or so…
REPLY: Yes and I also heard about the record cold and continued snow cover in Churchill, but I didn’t write about that either. Nice try though. – Anthony
The likelihood of an El Nino or La Nina condition lasting only once would be an unsupportable idea. These events probably seasonally echo into the future for quite some time. The warm or cool pool eventually works its way to other parts of the ocean and has an echo affect. Until we know just how much subsequent temp changes are due to a previous oceanic oscillation, we won’t know how much of the data to remove in order to find a signal that is caused by something else. In my opinion, the subsequent stairstep rises or falls that we see are echoes (IE off-set) of oscillation influences. The sudden sharp and significant changes are due to their onset. The rest of the noise is probably related to regional and local complex weather chaos. Given the complex nature of endogenous natural weather pattern drivers, finding ANY signal that is tiny would be harder than finding a blond hair in a straw stack.
It would be interesting (and fun) to overlay Dr. Hansen’s prediction from his 1988 congressional testimony on Figure 4. As I recall, he insisted we would have an anomaly of around 1.1°–1.2°C by now.
Flanagan (11:04:30) : “Hey, have you seen the series of record high temperatures in Texas? The highest daily temp in San Antonio and Austin were broken, and it’s going to continue for a week or so…”
I have, for the last year or so, been trying to convince my daughter (in Austin) that gorebull warming is a con.
Right now in San Antonio it is 101°F (heat index 105). Has been triple digits for the last week, and also forecast to continue. The local utility set a record yesterday for energy usage. I’d be hard pressed right now to convince her it is just weather, but its been hotter – In June 1998 Austin was 111°F and San Antonio 107°F.
Flanagan:
That’s just weather.
What does it prove? Just because it’s hot somewhere doesn’t mean anything. What’s causing the heat? Show us some direct evidence that it’s due to greenhouse gas emissions.
Hot weather is not an indicator of AGW. Neither is climate change. That fact that someplace is unusually hot or the climate is changing means absolutely nothing.
And the places where there is record cold? Well, it sure ain’t cold masking the warming, either!
What these graphs clearly show is post January 1998 stable and declining global temperatures during the period of greatest ever manmade CO2 emissions growth. According to EIA data about 85% of the world’s growth in CO2 emissions since 1990 occurred after January 1998. Yet despite this huge CO2 emissions growth driven by the developing nations actual global temperatures moved in the wrong direction compared to strongly increasing temperatures predicted by IPCC climate change models. The models are wrong so the so called science underlying the models is wrong. We need to stop pretending otherwise.
Excuse me Anthony, but I wasn’t criticizing your reporting (or not) of these events at all, I was simply mentioning it. BTW, which Churchill are you talking about? Following weather underground, I found a Churchill Kansas (35 °C – 4°C above average), a Churchill Pennsylvania (32 °C – 5 °C above average) and Churchill Manitobe (CA – 7 °C, 4°C below average)?
But maybe what you could have reported is the 2 months-long heat wave in India, that alreaky killed hundreds of people…
Flanagan (11:04:30) :
“Hey, have you seen the series of record high temperatures in Texas? The highest daily temp in San Antonio and Austin were broken, and it’s going to continue for a week or so…”
You complain when record cold weather is reported. Now, you report record warm temps. Does the word hypocrite mean anything to you?
BTW, this warm weather is nice where I live under the same ridge in the jet. After temps 20+ degrees below normal earlier this month a nice 10-15 degrees above is welcome. We may even get back to normal for the month. Could do with a little less humidity though.
I think posts of daily updates of weather, be it hot or cold, should have a rule attached. If you wanna post it, tell us why this local event is happening weather wise. If you want to talk about weather, show us you know something about weather drivers.
Bob Tisdale (01:16:30) :
Mike McMillan and Anthony: I’ll be happy to change formats for future posts, but I copy and paste the graphs from EXCEL to MS Paint and I only have one png choice in Paint. There’s no selection for 24 bits. Could you recommend some other image software?
Try IrfanView. http://www.irfanview.com/
It is free, very lightweight and does all formats you can think of, plus some more. Very nice for resizing and many other tasks. I have used it for years, cannot live without it.
Tim Clark: You wrote, “North America, the average increase of the two data sets is 0.172 deg C/century.”
That should be 1.72 deg C/century. My mistake in the text. The per annum figures in the equations are correct. I’ve corrected the text in the version on my website.
timetochooseagain and Mark Nodine:
Thanks for picking up my typos on the trends. Arctic and North America were incorrect in the text of the post. They’ve been corrected in the versions at my website. That’s what I get for proofreading before 7:00am.
Hey Pamela, are you still keeping your bet about the northwest passage not opening? Because 1/3d of it is already free, and the rest doesn’t look nice.
http://arctic.atmos.uiuc.edu/cryosphere/NEWIMAGES/arctic.seaice.color.000.png
There’s something wrong with these graphs — look at the horizontal axis. Clearly, they display slightly less than 30 years of data, instead of slightly more (as Jan 1979-May 2009 would imply). If the endpoint is May 2009 (which seems to make sense) then a consistent interpretation of the axis means they start in January 1980.
Right???
Frederick Michael: You wrote, “There’s something wrong with these graphs — look at the horizontal axis. Clearly, they display slightly less than 30 years of data, instead of slightly more (as Jan 1979-May 2009 would imply). If the endpoint is May 2009 (which seems to make sense) then a consistent interpretation of the axis means they start in January 1980.”
Nothing’s wrong with the graphs. Refer to the note directly above the dates in the title block of each graph. The data have been smoothed with 12-month running-average filters. This “shortens” the data at each end. The actual period covered can be seen in the start and stop points of the trends.
Thanks for keeping an eye out for errors, though.
Regards.