GISS Does It Again at The Isa
Ken Stewart, March 2010
Mount Isa is a hot and dusty mining town in the remote north west of Queensland. It’s famous for its mine, producing vast amounts of copper, lead, and zinc, it’s candy-striped smokestack and taller new one, and arguably the best rodeo in Australia. The Isa is surrounded by grass, rocks, trees, large cattle stations, and a few isolated mines, aboriginal communities, and outback towns. The nearest “urban” site is Alice Springs 674 km away. The nearest weather station is 106km away at Cloncurry, home of the Flying Doctor and Australia’s (unofficial) highest recorded temperature, 53.3°C (128°F) on 16/1/1889.
By now being awake up to GISS, the Goddard Institute of Space Studies, I should have known better. However, they still manage to surprise me.
The good folk at GISS once again have seen fit to adjust the data, more than doubling the warming. The adjusted data implies a warming trend nearly double that of surrounding rural stations. There is a pattern emerging to which I will devote a future post.
I used the same methodology as in previous studies. I downloaded Bureau of Meteorology and GISS data for Mt Isa and nearby rural sites. I plotted this data and applied trendlines. I then compared GISS before and after, and BOM.
Here are the results: (Click on the graphs for a larger view).
Mount Isa (Post Office, Airport, and Mine):
BOM:
GISS wisely stick to the Airport:-
But they increase the slope of the trendline from less than 0.5 to more than1.1 degrees Celsius per 102 years, by lowering the earlier data by 0.3C. They say they do this because they homogenise urban data for discontinuities caused by station shifts, Urban Heat Island (UHI) etc, by their stated method: “…urban stations are adjusted so that their long-term trend matches that of the mean of neighboring rural stations. Urban stations without nearby rural stations are dropped.” ( http://data.giss.nasa.gov/gistemp/)
So let’s follow that worthy line and see if they do as they say. We’ll visit the rural sites listed by GISS in turn. (The graphs and discussion of them is in the Appendix, below.) I have left out Julia Creek because its data record is very short and patchy, and no trend should be inferred.
First, Cloncurry: How disappointing- absolutely flat, a trend of maybe 0.05C per 102 years.
Next, 160km south, Urandangie: 1.4C. Ah, that’s better. But the running average becomes… 0.73 degrees- still short.
Third, Camooweal, 165km northwest: 1.2C, makes the average 0.88 degrees- getting closer!
Fourth, Donors Hill, 244km north east: dead flat at 0 degrees trend! Average now 0.66C.
Fifth, 254km south to Boulia: 0.6 C, makes the average trend 0.65 degrees per 102 years!
Now you can keep on going through the next 5 closest stations, Burketown, Normanton, Richmond, Croydon, and Winton, 414km away, but it only gets worse (for GISS). The average trend of the rural sites is 0.635 degrees Celsius per the 102 years of my study. No combination of nearest long term stations puts the trend above 0.88 degrees, let alone 1.1. Even BOM’s longer records of these 10 stations produce a trend of 0.82 degrees.
There cannot be any justification for the adjustment made to the temperature data at Mount Isa. There can be no excuse- not incomplete data, sloppy entry, or even incompetence. The GISS temperature record is false.
Appendix
Cloncurry: I spliced Post Office and earlier aerodrome data as it was very close. Trend is dead flat. Is that a 33 year cycle?
Urandangie: 1.4C per Century.
Camooweal, 165km northwest: 1.2C
Donors Hill, 244km north east: dead flat at 0 degrees trend!
254km south to Boulia: 0.6 C
Julia Creek 234km east: insufficient data
Burketown 327km north east: less than 1.4C, but 20 years cooling.
Normanton 374km north east: 0.7C, 20 years cooling. 30 year cycle?
Richmond 380km east: 0.25C
Croydon, 398 km north east: -0.45C
Winton, 414km south east. GISS 1.2, BOM 2 degrees C. 30 years data missing.
There is no clear picture: some sites show warming, some show cooling, some show nothing much at all.
Trends:
References
http://data.giss.nasa.gov/gistemp/station_data/
http://www.bom.gov.au/climate/data/weather-data.shtml
http://www.bom.gov.au/other/disclaimer.shtml
http://www.bom.gov.au/other/copyright.shtml#acknowledgements
http://www.appinsys.com/GlobalWarming/climap.aspx?area=australia
kenskingdom 
March 13, 2010 at 7:04 am
[…] Data corruption goes on and on and on, GISS falsifies record at Mount Isa, […]
March 14, 2010 at 12:41 am
Ken,
Thanks for your work. I see you’ve found the post and discussion of the Mt Isa figures here:
http://joannenova.com.au/2010/03/is-there-any-unmassaged-data-out-there/
Including Bernd Felsche:
March 13th, 2010 at 9:57 pm
The data from a nearby Ag research station appears unmolested. Haven’t the time to investigate others. (All Sites)
No warming from 1995 (start of automatic data) to present.
Temperature tracks insolation linearly with R^2 > 0.8, when temperatures from a month after the insolation are used. There are minor, roughly-periodic signals (of as yet undetermined nature) in the deviation from that trendline.
——-
I’ll be very interested in the meta analysis at the end of how many stations were adjusted up vs down. That could turn out to be an incisive figure.
Cheers!
Jo
March 14, 2010 at 1:18 am
This is easily explained. If you look at the GISS source code you can see that they take a linear average of the urban station with the nearby rural stations.
So.
Mt Isa: 0.5
Cloncurry: 0.05
Camooweal: 1.2
Urandangle: 1.4
Average 1.05. Round according to convention = 1.1C
The other stations quoted by Ken to arrive at his figure are further away and unless he starts to weight them I don’t see why they should be included.
Goddard have come up with a way to handle the urban heat island effect. It’s crude, but as a first order approximation appears to be effective.
If Ken wants to come up with an alternative procedure he’s quite welcome to do so, but he will then have to apply it across the globe. Such a step has implications that he may not have considered.
Here we have an example of an urban station showing a smaller increase than neighbouring rural stations despite the UHI and yet he wants special treatment for it.
I want to see him do it with his alternative procedure – which seems to be “use the 10 neighbouring stations” – and apply it to the whole globe.
March 14, 2010 at 11:00 am
Good morning JM
This is new and very interesting. Can you please give a reference for this method of arriving at the urban adjustment? I have been using the metyhodology straight off their website, quote:
“The GHCN/USHCN/SCAR data are modified in two steps to obtain station data from which our tables, graphs, and maps are constructed. In step 1, if there are multiple records at a given location, these are combined into one record; in step 2, the urban and peri-urban (i.e., other than rural) stations are adjusted so that their long-term trend matches that of the mean of neighboring rural stations. Urban stations without nearby rural stations are dropped. ”
They don’t mention averaging the urban with the rural- is this new? Where did you find this?
As well, GISS are more than happy to use data from stations up to 1200km away, apparently without weighting. I agree with you, they should only use “nearby” stations. I only used 5 and 10 stations to illustrate that no collection of closest rural sites will give you an average trend that will justify the adjustment to Mt Isa.
So in short, my procedure is not alternative at all. I don’t want special treatment for Mt Isa at all- I want its data left alone instead of being adjusted to show increased warming.
I look forward to hearing more from you as the method you mention will have major implications for analysing station data in the future. In the meantime, I’ll stick with the method GISS say they use.
March 14, 2010 at 9:32 pm
They don’t mention averaging the urban with the rural- is this new? Where did you find this?
From reading their description of what they are doing and confirming it with the source code.
You seem to have done the same thing but mistakenly interpreted it as meaning “use the 10 nearest stations and average them”. They average the nearest stations while you average the 10 nearest. Where did you get the idea to do that as the basis of your criticism? Thin air? No, Ken you’re not being honest here.
You’ve created your own similar method, but your only complaint is that Goddard have not used the method you prefer.
It’s a bogus complaint.
And this post is just noise. At least until you implement your alternative method, apply it to the whole globe and show that you get substantially different results from Goddard. I doubt you will.
Until you do that, your comments don’t even rise the to level of nitpicking.
March 15, 2010 at 7:24 am
Good morning again JM,
So please give your source: “from reading their description of what they are doing” . I’ve given my reference- the GisTemp homepage http://data.giss.nasa.gov/gistemp/ What’s yours? Or maybe you have inside information that is not made public knowledge? You see that is just my point- what they say they do publicly is not what they do in practice. And what’s the difference between ” average the nearest stations” and ” average the nearest 10 stations” ? By the way, the number doesn’t matter, it won’t work for any number. So it’s not an alternative method, and yours doesn’t work either- how’s your GISS calculator?
March 14, 2010 at 11:27 pm
Great work! Came here via JoNova. Thanks for setting the record straight. I will also add your post to my Data Visualisation Examples making science and economics transparent.
March 15, 2010 at 2:05 am
Linear Average?
1.4 + 1.2 +0.5 + 0.05 = 3.15 and divide by 4 = 0.79 average
Do Giss issue special calculators?
March 15, 2010 at 7:00 am
Thanks Jo
I didn’t pick up on that! Maybe JM has one! Sort of digs a hole doesn’t he (she).
March 15, 2010 at 2:08 pm
I missed a step there, Cloncurry will be dropped as it closed in 1991 and there have been no records since 1991. Recalculate and you can see how they’ve got the value they have.
Regardless, my original explanation stands:-
a.) the GISS code performs a process that compensates for the UHI effect
b.) you have proposed a process that is different from that of Goddard.
c.) if you think your alternative process is better that’s fine, but it doesn’t make Goddard wrong.
It is pointless to complain that you get different results. You’re using a different technique.
It is downright shabby to accuse them of “falsification”. That’s actionable in some countries.
BTW – please don’t moderate (or edit) my comments.
March 15, 2010 at 3:43 pm
Point 1: Oh dear- still no reference for your claim of the way GISS homogenise.
Point 2: GISS dropped all of them except Mt Isa in 1991 and 1992! So what? No need to recalculate unless you wish to cherry pick.
Point 3: When have your comments been edited? Never. But I do reserve the right to moderate or edit as I see fit… or perhaps just ignore if you can’t come up with something more substantive, such as that elusive reference to GISS procedure that conflicts with their stated method.
March 15, 2010 at 7:10 pm
[snip] Sorry jm, but you’ve wasted my time enough. All you can come up with is “Goddards site.” Your claim bizarrely backs mine- that what GISS do is different from what they say publicly. And actually, I agree with you- “The Earth is warming.” We disagree on amount, places, and causes.
And no, I’m not dishonest, but I enjoy reading Jo’s comments much more than yours, so I read (and approved) hers first!
“I also note that you don’t actually have a commenting policy that defines “objectionable”. ” Didn’t know I had to. But I do now, and it includes timewasting. My blog, my editorial rights.
Goodbye.
Ken
March 17, 2010 at 9:26 pm
My first visit to this site and I am also wondering why JM is not giving a link to his references.
The AGW discussion (pro and con) suffers from unsourced statements (JM) and exaggerations (Al Gore’s “millions of degrees” at the Earth’s centre) that do nothing to move us forward.
Kenskingdom – could you do some analysis of Australia’s rainfall given that all we hear is that it is getting drier all over. The BOM graphs (http://reg.bom.gov.au/cgi-bin/silo/reg/cli_chg/trendmaps.cgi?variable=rain®ion=aus&season=0112&period=1910) for rainfall trends show the majority of Australia with a POSITIVE rainfall trend.
Being from SA, I hear lots about the River Murray drying due to drought but the Murray Darling Basin annual rainfall trends UP since 1900 (http://reg.bom.gov.au/cgi-bin/silo/reg/cli_chg/timeseries.cgi?variable=rain®ion=mdb&season=0112). There is a disconnect, in my opinion, between the reality (the data) and the commentary (by both politicians and scientists from organisations such as the CSIRO).
March 20, 2010 at 4:22 pm
Hi John
Post coming this pm I hope.
Ken
March 18, 2010 at 7:47 am
John Trigge
Yes, I’ll try to do a piece on “The Great Climate Shift of March 2010” as soon as I can, but I have work and family commitments, and Cyclone Ilui approaching so this may be held up.. Many CSIRO and BOM assertions from the other day need checking- the easiest being rainfall.
We need to request all original data, details of Torok’s corrections and methodology he used, and details of exactly which station data the assertions are based on.
March 18, 2010 at 7:43 pm
Ken, Mt Isa is interesting because in its geographic isolation and with a high stack with plenty of SO2, they were able to measure the downwind air plumes for some distance. I have asked if I can obtain results, but got no answer. There is some quite valuable data on gas mixing and transport if it can be winkled out.
March 20, 2010 at 4:19 pm
Hi geoff
Wondered about that! I hope you can dig up some data.
March 29, 2010 at 11:45 pm
Hi All – As a ‘first timer’ here but more than a little interested in the topic/debate, grateful if someone could please clarify the maths above re ‘linear average’.
JM’s Post of Mar 14 followed by Jo Nova’s Post Mar 15 refer.
Seems to me the average should read..
1.4 + 1.2 +0.5 + 0.05 = 3.6 and divide by 4 = 0.9 average ??
March 30, 2010 at 8:27 am
Sorry Marathon, but the calculation gives 3.15/4 = 0.7875.
That’s not the point- JM got it wrong, urban centres are not included when averaging rural sites.
Ken
March 30, 2010 at 10:29 am
Ahhh – You’re indeed correct. Thx. I totally miss read the last number as 0.5 V’s 0.05! Thought I was going crazy. Your more important point re averaging temps at urban V’s rural noted & agreed. Appears JM’s lost interest.. Look forward to sighting more critique of recent CSIRO/BOM Snapshop paper.
[Actually, I lost interest in his circular arguments that were going nowhere. I might relent one day. Ken]
March 31, 2010 at 9:21 am
[…] GISS Falsifies Record at Mount Isa « kenskingdom […]