Dr. Roy Spencer proves what we have been saying for years, the USHCN (U.S. Historical Climatology Network) is a mess compounded by a bigger mess of adjustments.
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USHCN Surface Temperatures, 1973-2012: Dramatic Warming Adjustments, Noisy Trends
Guest post by Dr. Roy Spencer PhD.
Since NOAA encourages the use the USHCN station network as the official U.S. climate record, I have analyzed the average [(Tmax+Tmin)/2] USHCN version 2 dataset in the same way I analyzed the CRUTem3 and International Surface Hourly (ISH) data.
The main conclusions are:
1) The linear warming trend during 1973-2012 is greatest in USHCN (+0.245 C/decade), followed by CRUTem3 (+0.198 C/decade), then my ISH population density adjusted temperatures (PDAT) as a distant third (+0.013 C/decade)
2) Virtually all of the USHCN warming since 1973 appears to be the result of adjustments NOAA has made to the data, mainly in the 1995-97 timeframe.
3) While there seems to be some residual Urban Heat Island (UHI) effect in the U.S. Midwest, and even some spurious cooling with population density in the Southwest, for all of the 1,200 USHCN stations together there is little correlation between station temperature trends and population density.
4) Despite homogeneity adjustments in the USHCN record to increase agreement between neighboring stations, USHCN trends are actually noisier than what I get using 4x per day ISH temperatures and a simple UHI correction.
The following plot shows 12-month trailing average anomalies for the three different datasets (USHCN, CRUTem3, and ISH PDAT)…note the large differences in computed linear warming trends (click on plots for high res versions):
The next plot shows the differences between my ISH PDAT dataset and the other 2 datasets. I would be interested to hear opinions from others who have analyzed these data which of the adjustments NOAA performs could have caused the large relative warming in the USHCN data during 1995-97:
From reading the USHCN Version 2 description here, it appears there are really only 2 adjustments made in the USHCN Version 2 data which can substantially impact temperature trends: 1) time of observation (TOB) adjustments, and 2) station change point adjustments based upon rather elaborate statistical intercomparisons between neighboring stations. The 2nd of these is supposed to identify and adjust for changes in instrumentation type, instrument relocation, and UHI effects in the data.
We also see in the above plot that the adjustments made in the CRUTem3 and USHCN datasets are quite different after about 1996, although they converge to about the same answer toward the end of the record.
UHI Effects in the USHCN Station Trends
Just as I did for the ISH PDAT data, I correlated USHCN station temperature trends with station location population density. For all ~1,200 stations together, we see little evidence of residual UHI effects:
The results change somewhat, though, when the U.S. is divided into 6 subregions:
Of the 6 subregions, the 2 with the strongest residual effects are 1) the North-Central U.S., with a tendency for higher population stations to warm the most, and 2) the Southwest U.S., with a rather strong cooling effect with increasing population density. As I have previously noted, this could be the effect of people planting vegetation in a region which is naturally arid. One would think this effect would have been picked up by the USHCN homogenization procedure, but apparently not.
Trend Agreement Between Station Pairs
This is where I got quite a surprise. Since the USHCN data have gone through homogeneity adjustments with comparisons to neighboring stations, I fully expected the USHCN trends from neighboring stations to agree better than station trends from my population-adjusted ISH data.
I compared all station pairs within 200 km of each other to get an estimate of their level of agreement in temperature trends. The following 2 plots show the geographic distribution of the ~280 stations in my ISH dataset, and the ~1200 stations in the USHCN dataset:
I took all station pairs within 200 km of each other in each of these datasets, and computed the average absolute difference in temperature trends for the 1973-2012 period across all pairs. The average station separation in the USHCN and ISH PDAT datasets were nearly identical: 133.2 km for the ISH dataset (643 pairs), and 132.4 km for the USHCN dataset (12,453 pairs).
But the ISH trend pairs had about 15% better agreement (avg. absolute trend difference of 0.143 C/decade) than did the USHCN trend pairs (avg. absolute trend difference of 0.167 C/decade).
Given the amount of work NOAA has put into the USHCN dataset to increase the agreement between neighboring stations, I don’t have an explanation for this result. I have to wonder whether their adjustment procedures added more spurious effects than they removed, at least as far as their impact on temperature trends goes.
And I must admit that those adjustments constituting virtually all of the warming signal in the last 40 years is disconcerting. When “global warming” only shows up after the data are adjusted, one can understand why so many people are suspicious of the adjustments.
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Geoff Sherrington says: April 13, 2012 at 6:14 pm
Correction – transcribed into GHCN unadjusted.
Tim Clark says: April 13, 2012 at 6:46 pm
“Do you consider an increased temperature of 1.61C/century by 2073 as CAGW?”
Well, it’s not sustainable indefinitely. We have to figure out where we’re going with it.
Constant adjustment of data does not inspire confidence in the accuracy of the data collected .I would expect that very early data would be less reliable than the present data but it is the present data that is being adjusted and it does not seem that we ever get it right and no more adjustments are needed.All these adjustments to try to make average temperatures more accurate make the local temperature changes unclear the uhi effect is part of these local changes and if the local temperature is measured consistently we should see the way local temperatures are trending.The local weather stations were not meant to measure global or regional temperature only local temperature.
RE
Nick Stokes says:
@ur momisugly April 13, 2012 at 10:49 pm
Tim Clark says: April 13, 2012 at 6:46 pm
“Do you consider an increased temperature of 1.61C/century by 2073 as CAGW?”
Well, it’s not sustainable indefinitely. We have to figure out where we’re going with it.
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Nick: presumably, a rate of 0.0000000000161C per Century isn’t sustainable indefinitely… but do I take it this figure represents the “consensus” estimate of global climate sensitivity?And can you elaborate on your final sentence. Not sure I get the drift…
One of the claims against AGW scientists is that they have apparently started with a preposition (AGW) and massaged the data to fit.
We all know Dr Spencer’s position on AGW – he’s written books setting it out. How is it he escapes a similar accusation from “sceptics”?
If Dr Spencer is claiming that climate scientists have “fudged the data” he should be having a field day in the journals deconstructing the hypothesis. why is he not doing so? Are “sceptics” going to run with the conspiracy theory racket they seem to be reliant upon and claim he is being thwarted by vested interests?
I’m sure my own skepticism will be unpoplpular here but I suspect Spencer, profiting from contrarian books as he does, also appears to have a vested interest in maintaining his stance, despite the science.
And yet the satellite dataset Spencer maintains, clearly shows the trend he seems to want to deny in the surface record, despite the polynomial fit he applies “for entertainment puposes” but was faithfully reproduced as scientifically based by a contrarian journalist recently.
I think that is there are true sceptics here, perhaps Spencer deserves some of their attention and scrutiny.
[this sounds very like “trolling” so if you don’t wish to be considered a troll perhaps you could include some proof of your suspicions . . kbmod]
I can forsee entries in reference books from around 2200AD: “Climate Science; A branch of psychology from the late 20th/early 21st Century, which sought to use statistical manipulation of unrelated, incomplete and low quality data sets to induce mass hysteria in the consumers of the results, and neurosis in the practioners, ultimately affecting government policies and raising vast amounts of unwarranted and unjustified tax revenues. See also Atlantis, Hollow Earth, Flying Saucers, ChemTrails, TinFoil Hats, Doomsday Cults, Fraud.”
Roy, you note that “I took all station pairs within 200 km of each other in each of these datasets, and computed the average absolute difference in temperature trends for the 1973-2012 period across all pairs. The average station separation in the USHCN and ISH PDAT datasets were nearly identical: 133.2 km for the ISH dataset (643 pairs), and 132.4 km for the USHCN dataset (12,453 pairs).”
A significant reason for the lack of agreement is that such UHI as took place, was not at the same time at each observing station. Another significant reason, one that shows in Australia, is that the noise in the data is very large compared with the signal being sought. I’ll start to believe UHI estimates when the baseline, unaffected record for a station can be measured for a couple of decades, so that any UHI change can be measured relative to the baseline. I can’t find a baseline here. All I get is noise which does not correlate with any factor I have available.
Nick Stokes says: April 13, 2012 at 10:42 pm Re raw data and GHCN
Nick, when the BOM send data to NOAA or Met Office or whomever, do they currently send Tmax and Tmin as read from Min-max thermometers read once a day, or as calculated from many readings per day? Before the BOM had many-per-day capability, they used to send Tmin and Tmax from thermometers. Has there been a change and if so, have you ever seen details of a splice as the instrumentation changed?
Doug in Seattle:
At April 13, 2012 at 4:21 pm you say;
“Documenting this is important. Sadly however, getting it into the published record may not happen.”
I wish to correct that to ‘getting it into the published record IS NOT POSSIBLE’.
This matter was the subject of the ‘Climategate’ email from me and, therefore, the subject of my submission to the Parliamentary investigation which whitewashed ‘The Team’.
I have repeatedly reported on WUWT that it proved impossible to publish a paper which provided an intercomparison of data sets for mean global temperature (MGT). I was its lead author.
The intercomparison showed the differences in trends between the MGT data sets proved the data were of unknowable accuracy and, therefore, are worthless as indicators of global and hemispheric temperature changes. It considered reasons for this according to two different understandings of the nature of MGT, and it recommended changes which would enable the data sets to be useful indicators.
But the data in the data sets kept changing between submission and publication of the paper. This required rejection of the paper for correction of its analysed data. Oh, and Nature rejected it because the Editor said, “Nature does not publish comparisons of data”.
Eventually, we gave up attempting to get it published (with rejection because of need to update its data and, therefore, analysis). I then attempted to get ‘The Team’ to decide on what is a proper procedure which would stop the continual data adjustments of the MGT data sets.
So, the publication of Roy Spencer’s work on WUWT is important. In science only the evidence matters and it does not matter who published it or where. His work is published above and can be referenced to here. But it cannot be published in ‘conventional’ journals because the data will change between its submission and agreement to publish.
Richard
Andrew says: April 13, 2012 at 11:34 pm
“but do I take it this figure represents the “consensus” estimate of global climate sensitivity?”
None of these figures relate to anything global at all. They are about ConUS. And I do not propose my figure as the correct one – it is the unadjusted result. In fact, the USHCN adjustments are well justified, especially TOB, which is a big one. The times of min/max obs are recorded; they have drifted from evening to morning, and that has a clear and calculable trend biasing effect. They would be clearly wrong not to adjust for it.
We have to figure out where we’re going with adding carbon to the atmosphere because if we keep doing it, it’s going to get hot. We’ve burnt about a tenth of readily available C. And it will take a long time to get an agreement to get it under control, so we’d better start.
I think we should not welcome something just because it provides pleasant results. Dr. Spencer’s way of doing population density adjustments is suspicious at best and in my opinion wrong. Urban heat island does not introduce trend changes, it introduces temperature shift which changes with many factors generally summed up as station siting quality which may (and does) change over time. In Dr. Spencer’s work, station siting is approximated by population density and there are even no changes to it considered. If that was true, then assuming there was no warming, badly sited stations would not produce a different data trend, they would just produce higher average temperatures with the same (zero) trend. Yet the adjustment is done assuming there are no changes to station siting and yet done by manipulating station trends. Dr. Spencer also didn’t care to explain his method in sufficient detail and based on the result I assume he sucessfully decreased trends even for lowest population stations – no wonder he got no warming as a result.
USHCN adjustments are suspicious, but not because they differ in a strange way from Dr. Spencer’s data.
One question I have is what is the meaning of [(Tmax+Tmin)/2] in relation to the temperature at a site? What is the ‘average temperature’ on any given day? As for long term temperature analysis what exactly is it telling you? If the average temperature as defined by [(Tmax+Tmin)/2] goes up, it could be – either both min and max going up; min alone; max alone; min going down at a lesser rate than max is going up. Surely only Tmax and Tmin have a meaning not the average of the two.
Nick Stokes:
At April 14, 2012 at 1:12 am you say and assert;
“We have to figure out where we’re going with adding carbon to the atmosphere because if we keep doing it, it’s going to get hot.”
Really? You know that? How?
Please prove it because atmospheric CO2 concentration has been increasing since at least 1958 and to date there is no evidence of any kind that this has had any effect on making the world “hot”.
And please note that this is important to the present discussion because – as Dr Spencer’s above article demonstrates – any changes to the world getting “hot” are so small that they are difficult to discern at ground level. Also, the satellite-derived data show the Earth has not been getting “hot” to a significant degree in recent decades.
Richard
I have given my above statement some more thought. By definition Tmax is usually recorded on day n, Tmin is usually recorded on day n+1. This is because the meteorological day is defined as 9am to 9am. Is there any correlation between Tmax and Tmin apart from a seasonal one?
Well, they have to adjust everything now ; because they have found Antarctic Urban Heat Centres are twice what they thought they were….
http://www.businessweek.com/news/2012-04-13/penguin-count-doubles-as-satellite-spies-on-birds-poop-stains
Richard S Courtney says: April 14, 2012 at 2:06 am
“Really? You know that? How?”
Greenhouse effect. Putting CO2 in the air impedes outgoing IR. Heat accumulates, temperature rises. Flux balance then restored (until more CO2 accumulates).
As a typical geologist practicing in the private sector, I am deeply sceptical of all things CAGW.
When trying to figure out geological structures, mineralisation trends etc., I obviously construct models in an attempt to try and explain what is happening. However, the golden rule is: IF THE DATA DOESN’T FIT THE MODEL, THEN THE MODEL IS WRONG, NOT THE DATA.
In ‘climate science’ it is the exact opposite: IF THE DATA DOESN’T FIT THE MODEL, THEN THE DATA IS WRONG, NOT THE MODEL. So, the data has to be adjusted/manipulated/tortured to fit the model. Roy Spencer’s analysis of USHCN data here is yet another classic example of this.
If geologists followed the so called logic of ‘climate scientists’, we would very rapidly run out of oil, gas and most metals.
If the world follows the logic of ‘climate scientists’, which requires pouring trillions of dollars into a futile attempt to solve a non-problem, it will be an economic disaster.
Ajusting the data is not autmical bad , however what is all important is the justifcation for doing so it made clear and is valid , and to often its simply not and then to compound the problem the raw data ‘goes missing’ so you then can’t check on what has been done and if it makes sense .
However, this is merely in line with the first rule of climate sceince , if the model and reality differ in value its reality which is in error. If you have faith in ‘the cause’ all of these types of problems disapear .
[snip . . please post with content, thank you . . kbmod]
The graph is taken from Warren Meyer’s site.
http://www.coyoteblog.com/coyote_blog/2007/07/an-interesting-.html
Typically for Meyer, it is wrong. The graph is in degrees F, the captions are in C, leading him and now you, to overstate the trends.
More diligence, more genuine scepticism required.
No sir, Goodridge already proved that CO2 has no effect on temperatures by demonstating that rural stations do not show any warming over the last 100 years despite of global CO2 increase. http://wattsupwiththat.com/2012/03/30/spencer-shows-compelling-evidence-of-uhi-in-crutem3-data/
It is also known from the 19th century that plants need CO2 to grow and the more CO2 in the atmosphere, the more plants grow (classic chemical cinetics) So the most sensible thing to do is to pump CO2 into the atmosphere..
However, if you want to live in a cave with no light and no running water, be my friend and go. Don´t expect me to join, thanks. But please, don´t try to impose a global dictatorship over this.
Hm, they could simply directly paint the temperature charts in powerpoint or the tool of their choice. This would reduce costs (why maintain all those stations?) and we get to the same results.
Post modern science when continuously changing historical records. Year after year history gets
“improved”, the 30s-40s get colder, now almost aligned to the 60s-70s, the record 98 slowly surpassing 34 but now also getting a little colder. At the time of the record no 200x managed to beat 1998, but now slowly all are growing, or rather 1998 is slowly sinking.
It is not that new data adds at the end of the graph but the whole graph moves like a living snake to fit whatever the adjusters adjust.
http://suyts.wordpress.com/2012/04/11/this-isnt-about-the-climate/
edbarbar says: April 13, 2012 at 10:12 pm
How do the satellite temps compare? Are these adjusted too? And what about BEST?
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In 2008 I found Hadcrut3 ST was warming at ~0.07C/decade faster than UAH LT. Different altitudes, but much less warming was observed from satellites.
See Fig. 1 at
http://icecap.us/images/uploads/CO2vsTMacRae.pdf
Satellite temperatures are often adjusted a few months after readings – my observation from 2008-2009 is that the UAH adjustments are typically very small.
No personal opinion on BEST, except that the name may be a misnomer.
http://wattsupwiththat.com/2011/11/03/a-considered-critique-of-berkley-temperature-series/
Kasuha says:
April 14, 2012 at 1:49 am
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It makes sense that urbanization adds some amount of temperature, an offset, at the current time. This is a static view of urbanization. But as the population grew, it would actually add to the trend. This is easier to imagine if you mentally start with two identical places, then imagine one begins to experience population growth. The temperature trend in it will be greater in the place with population growth.
I should add that I believe there is ample evidence that there is a strong warming bias in most surface temperature (ST) datasets.
Perhaps someone else would be kind enough to provide all the references. From memory:
Anthony Watts surface stations work
Michaels and McKitrick paper
Roy Spencer paper(s)
etc.
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http://wattsupwiththat.com/2009/02/05/fear-and-loathing-for-california/#comment-82352
Please look at the first graph ( to mid-2008) at:
http://www.iberica2000.org/Es/Articulo.asp?Id=3774
This graph suggests there has been no net global warming since 1940, despite an ~800% increase in humanmade CO2 emissions.
I used Hadcrut3 ST from 1940 (despite of its warming bias), and UAH LT thereafter.
This is the result when one plots the FULL PDO cycle, instead of attempting to extrapolate the WARMING HALF-CYCLE, as many warmists do.
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In 2003 I wrote that global cooling would soon recur. Bundle up!