Ken Stewart shows how GISS adjusts temperature records in two adjacent sites in Australia
This issue was also recently covered on the Climategate blog here
Introduction
Despite its assurances, GISS has adjusted the temperature records of two sites at Mackay to reverse a cooling trend in one and increase a warming trend in another. This study presents evidence that this is not supportable and is in fact an instance of manipulation of data.
I decided to have a look at the temperature records of the weather stations closest to where I live, near Mackay in North Queensland. The Bureau of Meteorology lists 3 current stations: Mackay MO, Mackay Aero, and Te Kowai Exp Station, plus the closed station Mackay Post Office. GISS has a list of nearby stations. One is “Mackay Sugar Mill Station”. I had never heard of it. Te Kowai Exp Station, only a few kilometres from Mackay, is in fact at the same co-ordinates as Mackay Sugar Mill. I checked on AIS for the GHCN site, and there is Mackay Sugar Mill on the map. The co-ordinates given by GHCN put it in the middle of a cane paddock 600m to the south of Te Kowai Sugar Experiment Station, so that’s definitely it! (If not, it’s identical in every other way!) And that is the closest weather station to my home, so I became even more interested.
Te Kowai is an experimental farm for developing new varieties of sugar cane, run by scientists and technicians since 1889. It has a temperature record of over 100 years with only a couple of gaps. So in fact it’s an ideal rural station for referencing a nearby urban station, as it should have a similar climate.
Analysis
I plotted data from BOM for maxima and minima and obtained the means for Te Kowai, all Mackay city stations, all GHCN stations in our 5 x 5 grid, and several other towns and cities with long records (Te Kowai’s starts at 1908). This is because “ In our analysis, we can only use stations with reasonably long, consistently measured time records.”
GISS combines GHCN data from all urban stations at the same location, and then homogenises this with data from neighbouring rural stations. So I then plotted the same-location data and the post-homogenisation data.
A problem that appeared immediately is that the GISS annual mean runs from December to November, while BOM’s raw data is for calendar years. Most of the time it matches pretty well, but there are several examples of poor quality data. Another problem is that BOM does not compute a mean for any year with even one month of data missing, while GISS tolerates several missing months.
Here are graphs of the results.
Read his entire post here
Nothing unexpected here. Has anyone asked GISS how they justify this data manipulation?
So whats to believe anymore? It becomes more and more apparent that the entire temperature record worldwide will need a major rework. I would not trust those agencies to do it either.
I think we need to extend Anthony’s surfacestations to Australia. Volunteers? I can help with Sydney based ones?
What is shocking to me is the unmitigated gall that must be in place to assume that no one would actually look at their “adjustments”. I learned as a child that when you tell a lie you have to tell ten lies to cover up that one lie, and so on. Did it not occur to GISS that people might eventually look at these “adjustments” and start piecing together what was done? I would not want my children and grandchildren to be faced with what “daddy” did to the data, as time would eventually reveal the fabrication. What a legacy to leave behind.
Many Aussies I blog with about temperature data manipulation don’t appear to be too concerned about the fact the data is fabricated as they believe in MMCC, and “something” has to be done, not for us but for our children.
Go figure!
Sadly, if an expected result requires that data be “massaged” so that the “correct” conclusion can be reached, it is hard not to “search” for the means to represent the “truth”.
As we are seeing, a lot of “truth” was being found with ever-greater certainty.
Fortunately, reality intruded just in time.
This is a definite “smoking gun”.
A quick précis for those who haven’t clicked through and read to the end:
The nearest rural station is not used in the adjustment of the urban readings for Mackay (pop 35,000). If it were, the trend for Mackay would be substantially reduced. The reason for not using it is that it is also classified as urban – despite being in the middle of sugar cane fields.
The smoking gun is that the record for that station was ended in 1992 – when records for many other rural stations ceased. So, it seems it was once classified as rural and mysteriously reclassified as urban. Convenient.
Great post.
GISS now has to realize that the blogosphere is going eventually look at virtually all of their data treatments for temperature sensing locations . . . . . . the bias in their treatments is being revealed. It is hard not to conclude, as we get more and more of these posts, that they manipulated the data to show it is warmer. At the same time they advocate in support of an AGW agenda. tic, toc, tic, toc . . . . blog post by blog post . . .showing the biased GISS data treatment.
John
Do they also extrapolate the McKay temps to the south island of New Zealand? OK just being flipant now 😉
Great piece of work Ken which shows GISS messing with the data again. Seems every time someone makes the effort to see what’s happening in their area, upwards adjustments are found.
The CAGW is being hit hard by the high impact Climategate and IPCC revelations of fraud – now it’s suffering the death of a thousand cuts from concerned people across the world.
How long do we have to wait before those responsible are charged with fraud and if found guilty are put behind bars? Someone must be brought to account. Otherwise this sort of data manipulation will continue unabated.
I was interested to note this post as I too have been puzzled by GISS population estimates for the sites used in its data set. I know Warwick Hughes (http://www.warwickhughes.com/blog/) has done some excellent work in this area.
I have only examined the population estimates of a few GISS sites but some were only half the recent census population estimates for the same areas.
Suspicions aroused I tried to see if the same applied to CRU data. I corresponded with Phil Jones who was both polite and prompt in his response. He referred me to the Brohan et al (2006) paper. http://www.cru.uea.ac.uk/cru/data/temperature/HadCRUT3_accepted.pdf
Populations were not included in CRU data for reasons explained in that 2001 paper. Rather, Jones (and his CRU colleagues) appears to accept the Folland et al (2001) assumption of a 0.0055C/decade global temperature increase due to urbanisation. In our email exchange Jones confirmed this corresponded to an increase in global 20th temperatures increase of 0.055C: I would suggest of statistically no importance.
My interpretation of this is simple: CRU data dismisses urbanisation as having any influence on 20th century global temperatures. This premise stands or falls on the Folland et al (2001) paper. Am I correct in saying that if new research concludes that urbanisation had a positive 0.055C/decade effect on global temperatures, equating to 0.55C for the 20th century, then the idea of 20th century global warming virtually collapses?
As it stands, the theory of 20th global warming rests on the validity of the Folland et al (2001) paper. Is this a correct deduction or am I missing something?
How GISS calculate a station’s temperature increase.
Think of a number;
Add 0.8;
Take away the number you first thought of;
Surprise, surprise you end up with 0.8
Errata:
Apologies for a typo in the post above. It should read:
“Populations were not included in CRU data for reasons explained in that 2006 paper.”
Apologies for the confusion.
I am in Taiwan and will see if I can get some of my Taiwan national associates to do a little investigative work on GISS treatments for temperature sensing locations here. : ) It gives me something to do during the upcoming Chinese Lunar New Year holiday week except shooting off fireworks and drinking Kinmen guaolian (phonetics are mine).
John
I read the guest blog post at this site, where professor Ravetz made a razor sharp analysis of why it could go so wrong. Link here. He described the extended peer communityas the driving force from the blogosphere as the only force that could correct science that had been so corrupted as the current climate science. (It is very much worth reading if you haven’t.)
It is just amazing to see how this extended peer community works. The example in this post is another of noone knows how many errors that are exposed that otherwise had gone unnoticed. Good work!
The link in my previous post should be this one. :-/
There is a choice on the GISS graphing site that lets you change the year to be a calendar year. It is at the very top of the ‘drop down’ menu (that for me in fact opens upward… a ‘drop up’? 😉 making the option very easy to not notice)
FWIW, GISS never justifies their changes. GIStemp has a process built into it, so no human chooses the changes. All you will get are pointers to published papers that claim the method is fine…. (“The Reference Station Method). But it does an odd thing where all the stations averaged together to make the ‘reference’ have their “bias removed” by having their data shifted to keep their mean matching the very first station (that is not so moved). It just looks to me like the first station is allowed to SET the bias, then the others are conformed to it. Unfortunately, I’ve not had time to work over that bit of code enough to assure if it is or isn’t a bug…
Bulldust (01:59:40) : Do they also extrapolate the McKay temps to the south island of New Zealand? OK just being flipant now 😉
Well, a single thermometer can look up to 1000 km away to get missing values ‘filled in’. It can then in the UHI section use data from up to 1000 km away to adjust the UHI of a station. AND that data used may have been filled in in the prior step. Now I doubt that it happens very often, but it is POSSIBLE for that 1000 km UHI “reach” to be picking up a 1000 km “fill in” reach.
But wait, there’s more…
In the Grid / Box step that ‘homogenized and UHI adjusted’ thermometer can fill in a Grid Box up to 1200 km away… So… It’s theoretically possible (though IMHO unlikely) for a 1200 km grid reach from a 1000 km UHI reach from a 1000 km fill in reach to put some impact from a thermometer 3200 km away into a grid box. (There are 80 “grids” of 100 “boxes” each on the planet).
Now it will be all nicely averaged in with loads of other thermometer data, so it would not be standing out there all naked on it’s own (most of the time…) but with less than 1500 thermometers in GHCN for the world and with 8000 grid boxes there are going to be some boxes with only one thermometer doing the work…
And that is why Madagascar has temperature anomalies reported even though their last thermometer record was from 2005 and the few years before that had holes in the data. It’s also why both Panama and Bolivia have nice red patches of anomaly over them even though they have not reported temperatures since 1980…
After all, you don’t really need temperatures. Just anomalies. And both can be filled in if you really need some… after all, there’s got to be a thermometer or two within a couple of thousand kilometers somewhere we can use…
This is interesting…
http://www.forbes.com/2010/02/09/global-warming-minnesota-technology-ecotech-forest.html?partner=technology_newsletter
I don’t know why they bother with heaters. Why don’t they just let the CO2 forcing and water vapor feedback increase the heat by up to 9 degrees. Oops, was that catty?
OT.
Is anybody familiar with this? http://www.examiner.com/examiner/x-7715-Portland-Civil-Rights-Examiner~y2010m1d12-Hungarian-Physicist-Dr-Ferenc-Miskolczi-proves-CO2-emissions-irrelevant-in-Earths-Climate
Great post. There are very many examples of GISS doing a ‘wrong way’ correction for UHI, adjusting rural stations etc. Having a pair of stations like this is really valuable but it takes local knowledge. We need more example like this.
Do they also extrapolate the McKay temps to the south island of New Zealand? OK just being flipant now 😉
There is a New Zealand connection here somewhere.
The name of the station (Te Kowai) is very obviously from New Zealand Maori, Te Kowhai, which means “yellow.” Kowhai is a New Zealand tree with yellow flowers.
Someone up Mackay way must have been in New Zealand when that locale was named.
Ken Coffman (02:35:02) :
It’s called a Greenhouse! LOL
David Ball (01:23:01) :
What is shocking to me is the unmitigated gall that must be in place to assume that no one would actually look at their “adjustments”.
Well I was kind of thinking that if I had done it and I had been getting away with something for twenty years, and if it seemed like I was on a good thing … why would I change?
Mr. Ball, Perhaps you just can’t help letting your integrity get in the way….. not your fault at all…. I’m guessing you were either born or brought up that way.
And more credit to you.
Somewhat O/T. This story reminded of a funny article I read a couple years ago about that very same sugar mill.
http://thedailywtf.com/Articles/Cursed-and-ReCursed.aspx