How NASA GISS inserts warming into USA rural T data

Trawling through files from 2001 I came across this rare example of an email from Dr Jim Hansen that actually gives an insight into what GISS does with temperature data.
For background I have my page commenting on Jones et al use of Miami.
Then my page on the five degree grid cell covering much of Florida and commenting on Jones 1994 additions.
Then this page commenting on GISS data which inserts warming into rural data west of Miami.

It is indeed fascinating to ponder Dr Jim Hansen’s emails below from July 2001, I think the bottom one was first.
Consider that the IPCC draws faith in Jones et al warming trends from the point that GISS and GHCN produce similar results to Jones.

Date: Mon, 16 Jul 2001 17:54:27 -0400
To: W   Hughes <>
From: James Hansen <>
Subject: Fwd: Re: Florida Rurals


The adjustments to these two stations seem questionable.  Of course that is
true for almost all stations [see the last paragraph in section 5.2 of our
paper (still!) in press at JGR, which begins: "We reiterate a caveat that
we have discussed elsewhere — the smoothing introduced in
homogeneity-adjusted data may make the result less appropriate than the
unadjusted data for local studies….].  The reasons for this are obvious,
adjustments based on only a small number of stations, etc., so the
expectation is only that on large area average, including global average,
the adjustment does more good than harm.  On the large area average the
adjusments make the estimated temperature trend have less warming.  In
these two cases it makes for slight warming in one case and larger warming
in the other.  Both of these stations are "rural" in GHCN’s population
category, so they would not have been adjusted in the old GISS analysis,
but they are "dim" or "peri-urban" as seen by the satellite, so they are
adjusted in the new analysis.  You could argue that it might be better to
leave them unadjusted, but it’s really not kosher to go in on a case by
case basis.  Our approach is to set up an objective scheme and then let the
computer and the satellite make the decision – its not necessarily the best
way, but its objective, even though, as our caveat states, it is going to
give "bad" results at some individual stations.

If I remember right, when we looked at the satellite night lights map,
Florida was very unusual – perhaps it was that almost no "dark" sites
remained – so it may be statistics of very small numbers – I will check
with Makiko – also Florida is much harder than other places in the U.S.,
since most of it is bordered by water, so no stations there – also
meteorology is very different and small scale – lot’s of problems – but I
would not be surprised if its climate trends were quite different than the
"mainland" Southeast U.S., parts of it are in a different climate zone –
will get back to you.
Jim Hansen

16 thoughts on “How NASA GISS inserts warming into USA rural T data”

  1. No Ender, it is Dr Jim Hansen by his own words casting any doubt going around. And not all of us are so blind as to think that I just stumbled across the only errors of that type. JH makes the point that the GISS approach is to set up an objective scheme and then let the computer and the satellite make the decision. So similar errors will be present right through GISS data. If I had 1% of the GISS budget to fund an audit on their data I could soon nail down all their errors. Imagine for a moment if a Sceptic group produced a study and errors were found. I can hear the uproar from Perth. The whole study would be condemned. Before I go, you owe me some examples of where I cherrypick. Remember ? C’mon, surely you and your mates can come up with a few examples.

  2. Warwick – well is this not such an example. You are assuming that similar errors exist from one or 2 data points and then claim you do not have the budget to examine them. ” If I had 1% of the GISS budget to fund an audit on their data I could soon nail down all their errors.” Surely such an analysis could be carried out on a PC with suitable programming though it may take quite a while – as all the data is publically available. Also there are several avenues open to you for small research grants.

    As far as I can see Dr Hansen’s reply is entirely reasonable as independant studies confirm his data “Jones et al warming trends from the point that GISS and GHCN produce similar results to Jones.” by your own admission. If there was a systemic fault in the analysis it would produce different results.

    Are you implying that all the studies are biased. What about the sea surface temperatures that are rising? Also the satellite data, as short as it is, seems to confirm the idea that the globe is warming. None of this data is urban contaminated.

  3. There remains a consistent ignorance of what data is publicly available. Raw data is sensu strictu max and min temperatures assigned to a particular day of the year, with a lat and long for position. These data are not available.

    What is available on the BOM’site, for example, are temperature anomalies based on 1961-1990 and these data are clearly processed and adjusted.

    Warwick and I want the original raw data before post collection adjustments are made.

    RAW DATA in other words.

    We have no difficulty asking for and getting it in the mining business. Why is it so difficult to get if off publicly funded organisations?

  4. Raw wind data is not raw temperature data Ender. I am surprised if it is that easy you yourself would have obtained the temperature data.

  5. Loius – that is because I asked for wind data. If I had asked for temperature data that is what I would have got. Why don’t you try it – the person I spoke to was very helpful. For 20 or 30 dollars you can settle it. Just get the raw temperature data for one station and post it.

  6. No kidding? Can government agencies in Oz copyright data gathered with public funds? FWIW, I don’t think that’s the case in the U.S.

  7. I downloaded data from quite a few stations in the GISS data base. These were monthly temperatures, not daily. The home page for the data shows that many stations have been closed since 1970. From the graph, it would seem that we have less than half the number of stations today that we did in 1970. Although I did not do a detailed analysis of the stations which closed, it certainly seemed as if many of the closures were in areas designated as rural. As I searched through the dataset, I found it difficult, in some parts of the world, to find rural stations which were open after 1990. On the other hand, there were many urban sites with long records of temperature collection. It appeared to me that there has been an increase in the percentage of urban stations in the GISS dataset over the past 20 to 30 years. If my observations are correct, then I am worried that grids, like those used by Jones, show increasing temperatures largely because they are becoming more urban. I believe that claims of UHI adjustment must be questioned not only as to whether they are large enough to compensate for local urban increases, but also whether these adjustments adequately compensate for the growing urban character of many grids. It is disturbing to discover that the satellite data has been modified, particularly upward.

  8. Brooks and Warwick, It would be useful to see a list of stations that are used each year along with their populations. Then it be revealing to see a plot of the mean population of all the sites from 1880 to present. I would expect to see a strong upward trend. Peterson a few years ago said the number of rural sites (population of less than 10,000) had dropped to 8% of the stations although it was 22% sometime earlier. What percentage of the stations have populations less than 1000 and are really rural? You would think scientists would release these numbers.

  9. Steve, It is actually the biggest bottlenecks in data release. WMO resolution 40 prohibits free dissemination of licensed data.

  10. First time I’ve seen that Hansen email. When he says you need a pretty large area before these adjustments become a “good” rather than a “bad”, wouldn’t that imply that there ought to be plenty of cases in the record where the adjustments are going the other way, introducing cooling rather than warming?

    If so, why don’t we ever see them held up for examination? Is the skeptic community a litle too focused on finding the ugly examples in one direction and not showing the others (aka cherry picking)? Or do the others not exist?

  11. I am not aware of any going “the other way”. I do not agree with this notion of Jim’s that you can have a scheme that gives a great result globally but when you put a microscope on it, you will find errors in adjustments at the station level. I would say if you want to use GW to affect global policy then your scheme must stand up to local scrutiny. Errors is errors and should be rooted out. Simple – science 101. Jones had a similarly pliant attitude to obvious errors, when I quizzed him post his 1994 update – about still including Atlanta or LA or Sydney for example, he would just say, “..but we included new stations from less populated places”. OK Phil – so the Atlanta error is still in there !! Along with circa 1,000 others from cities.

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