Guest Post by Willis Eschenbach
Recapping the story begun at WUWT here and continued at WUWT here, data from the temperature station Darwin Zero in northern Australia was found to be radically adjusted and showing huge warming (red line, adjusted temperature) compared to the unadjusted data (blue line). The unadjusted data showed that Darwin Zero was actually cooling over the period of the record. Here is the adjustment to Darwin Zero:
Figure 1. The GHCN adjustments to the Darwin Zero temperature record.
Many people have written in with questions about my analysis. I thank everyone for their interest. I’m answering them as fast as I can. I cannot answer them all, so I am trying to pick the relevant ones. This post is to answer a few.
• First, there has been some confusion about the data. I am using solely GHCN numbers and methods. They will not match the GISS or the CRU or the HadCRUT numbers.
• Next, some people have said that these are not separate temperature stations. However, GHCN adjusts them and uses them as separate temperature stations, so you’ll have to take that question up with GHCN.
• Next, a number of people have claimed that the reason for the Darwin adjustment was that it is simply the result of the standard homogenization done by GHCN based on comparison with other neighboring station records. This homogenization procedure is described here (PDF).
While it sounds plausible that Darwin was adjusted as the GHCN claims, if that were the case the GHCN algorithm would have adjusted all five of the Darwin records in the same way. Instead they have adjusted them differently (see below). This argues strongly that they were not done by the listed GHCN homogenization process. Any process that changed one of them would change all of them in the same way, as they are nearly identical.
• Next, there are no “neighboring records” for a number of the Darwin adjustments simply because in the early part of the century there were no suitable neighboring stations. It’s not enough to have a random reference station somewhere a thousand km away from Darwin in the middle of the desert. You can’t adjust Darwin based on that. The GHCN homogenization method requires five well correlated neighboring “reference stations” to work.
From the reference cited above:
“In creating each year’s first difference reference series, we used the five most highly correlated neighboring stations that had enough data to accurately model the candidate station.”
and “Also, not all stations could be adjusted. Remote stations for which we could not produce an adequate reference series (the correlation between first-difference station time series and its reference time series must be 0.80 or greater) were not adjusted.”
As I mentioned in my original article, the hard part is not to find five neighboring stations, particularly if you consider a station 1,500 km away as “neighboring”. The hard part is to find similar stations within that distance. We need those stations whose first difference has an 0.80 correlation with the Darwin station first difference.
(A “first difference” is a list of the changes from year to year of the data. For example, if the data is “31, 32, 33, 35, 34”, the first differences are “1, 1, 2, -1”. It is often useful to examine first differences rather than the actual data. See Peterson (PDF) for a discussion of the use of the “first-difference method” in climate science.)
Accordingly, I’ve been looking at the candidate stations. For the 1920 adjustment we need stations starting in 1915 or earlier. Here are all of the candidate stations within 1,500 km of Darwin that start in 1915 or before, along with the correlation of their first difference with the Darwin first difference:
WYNDHAM_(WYNDHAM_PORT) = -0.14
DERBY = -0.10
BURKETOWN = -0.40
CAMOOWEAL = -0.21
NORMANTON = 0.35
DONORS_HILL = 0.35
MT_ISA_AIRPORT = -0.20
ALICE_SPRINGS = 0.06
COEN_(POST_OFFICE) = -0.01
CROYDON = -0.23
CLONCURRY = -0.2
MUSGRAVE_STATION = -0.43
FAIRVIEW = -0.29
As you can see, not one of them is even remotely like Darwin. None of them are adequate for inclusion in a “first-difference reference time series” according to the GHCN. The Economist excoriated me for not including Wyndham in the “neighboring stations” (I had overlooked it in the list). However, the problem is that even if we include Wyndham, Derby, and every other station out to 1,500 km, we still don’t have a single station with a high enough correlation to use the GHCN method for the 1920 adjustment.
Now I suppose you could argue that you can adjust 1920 Darwin records based on stations 2,000 km away, but even 1,500 km seems too far away to do a reliable job. So while it is theoretically possible that the GHCN described method was used on Darwin, you’ll be a long, long ways from Darwin before you find your five candidates.
• Next, the GHCN does use a good method to detect inhomogeneities. Here’s their description of their method.
To look for such a change point, a simple linear regression was fitted to the part of the difference series before the year being tested and another after the year being tested. This test is repeated for all years of the time series (with a minimum of 5 yr in each section), and the year with the lowest residual sum of the squares was considered the year with a potential discontinuity.
This is a valid method, so I applied it to the Darwin data itself. Here’s that result:
Figure 2. Possible inhomogeneities in the Darwin Zero record, as indicated by the GHCN algorithm.
As you can see by the upper thin red line, the method indicates a possible discontinuity centered at 1939. However, once that discontinuity is removed, the rest of the record does not indicate any discontinuity (thick red line). By contrast, the GHCN adjusted data (see Fig. 1 above) do not find any discontinuity in 1941. Instead, they claim that there are discontinuities around 1920, 1930, 1950, 1960, and 1980 … doubtful.
• Finally, the main recurring question is, why do I think the adjustments were made manually rather than by the procedure described by the GHCN? There are a number of totally independent lines of evidence that all lead to my conclusion:
1. It is highly improbability that a station would suddenly start warming at 6 C per century for fifty years, no matter what legitimate adjustment method were used (see Fig. 1).
2. There are no neighboring stations that are sufficiently similar to the Darwin station to be used in the listed GHCN homogenization procedure (see above).
3. The Darwin Zero raw data does not contain visible inhomogeneities (as determined by the GHCN’s own algorithm) other than the 1936-1941 drop (see Fig. 2).
4. There are a number of adjustments to individual years. The listed GHCN method does not make individual year adjustments (see Fig. 1).
5. The “Before” and “After” pictures of the adjustment don’t make any sense at all. Here are those pictures:
Figure 3. Darwin station data before and after GHCN adjustments. Upper panel shows unadjusted Darwin data, lower panel shows the same data after adjustments.
Before the adjustments we had the station Darwin Zero (blue line line with diamonds), along with four other nearby temperature records from Darwin. They all agreed with each other quite closely. Hardly a whisper of dissent among them, only small differences.
While GHCN were making the adjustment, two stations (Unadj 3 and 4, green and purple) vanished. I don’t know why. GHCN says they don’t use records under 20 years in length, which applies to Darwin 4, but Darwin 3 is twenty years in length. In any case, after removing those two series, the remaining three temperature records were then adjusted into submission.
In the “after” picture, Darwin Zero looks like it was adjusted with Sildenafil. Darwin 2 gets bent down almost to match Darwin Zero. Strangely, Darwin 1 is mostly untouched. It loses the low 1967 temperature, which seems odd, and the central section is moved up a little.
Call me crazy, but from where I stand, that looks like an un-adjustment of the data. They take five very similar datasets, throw two away, wrench the remainder apart, and then average them to get back to the “adjusted” value? Seems to me you’d be better off picking any one of the originals, because they all agree with each other.
The reason you adjust is because records don’t agree, not to make them disagree. And in particular, if you apply an adjustment algorithm to nearly identical datasets, the results should be nearly identical as well.
So that’s why I don’t believe the Darwin records were adjusted in the way that GHCN claims. I’m happy to be proven wrong, and I hope that someone from the GHCN shows up to post whatever method that they actually used, the method that could produce such an unusual result.
Until someone can point out that mystery method, however, I maintain that the Darwin Zero record was adjusted manually, and that it is not a coincidence that it shows (highly improbable) warming.
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If the nation was not led down the path of global warming alarmism, but rather given a warning of a fierce winter season based on true science, perhaps the retailers and cleanup crews could have been put in place to deal with the mess in order to help improve customer traffic and boost Christmas sales. Too bad, many retailers will be going out of business due to the nation not being prepaired.
US Blizzard Puts Crimp in Holiday Sales, Travel
http://au.news.yahoo.com/a/-/world/6608283/us-blizzard-puts-crimp-in-holiday-sales-travel/
Willis, great work!
minor points;
– third para .. too many ‘independent’s?
– re tthe 1500km limit, they wouldn’t have used data from sites further north would they? (i.e. not in Australia)
Beautiful pictures in this article, like postcard pictures.
Think we have it bad? Try Washington for a whole winter’s snow in one day
http://www.dailymail.co.uk/news/worldnews/article-1237351/Think-bad-Try-Washington-winters-snow-day.html
The reason they brought out the heavy fire from The Economist (which by the way, is also very wrong on our ailing economy) is that they are running scared. This gig is up. The public no longer buys the MSM orchestrated AGW scare story.
Panic time. Yell. Scream. Discredit. Ad Hominem.
I wonder how average temperatures are calculated. It’s not even ingenious let alone scientific. Why don’t we measure those average temperatures directly? Here is how it would work:
Rock is a very good medium to use so drill a horizontal hole into a mountain. Start at one meter or maybe two. Place a temperature sensor at the end and isolate the hole as good as you can. Wait a week. Measure. Repeat for another depth. The age of the averaged temperature should be proportional to the depth. I guess exponential. We would have to calibrate the depth/age relation according to the property of the material like say, Rock Rings.
The nearer you get to the surface the lesser the attenuation will work and you may see the annual, later dayly temperature oscillation. There you may measure in fixed intervals and integrate numerically.
Stevenson screens, pah.
“It is entirely fallacious to modify Darwin temperatures using stations around it, especially those even a short distance inland from the city.”
This might be true, but as I understand it, not for the reasons you give.
If two points have a strong correlation, then it doesn’t matter that they are actually 6° different on any one day, or year, or whatever. An analogy: my sister and I never are the same age, but our ages correlate very strongly. I am prepared to bet she will be 45 when I turn 50.)
I would bet that in the short term a station a short distance inland of Darwin correlates very strongly with Darwin. I think a long term bet on that might fail, due to UHI or other effects.
Nick – most general adjustments are justified to account for the UHI effect. I know of no general reason to say why adjustments should be made the other way. Do you?
If most adjustments are required to reduce the impact of the UHI, then the overall trend in the adjustments should be largely negative.
The fact it is positive is completely bizarre and needs a lot of explaining.
I found this. I haven’t had time to explore further yet.
A change in the type of thermometer shelter used at many Australian observation sites in the early 20th century resulted in a sudden drop in recorded temperatures which is entirely spurious.
http://www.bom.gov.au/climate/change/datasets/datasets.shtml
There is a PDF on the same page that says.
other known data problems. Such discontinuities can be as large, or larger than, real temperature changes (eg. the approximate 1°C drop in maximum temperatures associated with the switch to Stevenson screen exposure) and consequently confound the true long-term trend. Generally the high-quality records were homogenised from 1910, by which time most stations are believed to have been equipped with the current standard instrument shelter. 224 temperature records were reconstructed to an acceptable standard, 181 of which were identified as being non-urban.
Go Willis.
I am starting to think that one should never adjust station records (i.e. the real observed data) and continue to call them by the same name as the raw data station. For example, if an “adjusted” Darwin0 is required for some purpose – then the resulting series – homogenized, stretched, smeared or tilted should always be called by a name that identifies it as such. For example, DarwinHSST023, where such name can be looked up and shown to represent Darwin Homogenized Stretched Smeared Tilted algorithm 023. Thus, whereas Darwin 0 represents a particular station at a particular location between two dates, and never changes (it is after all – within other constraints – real data), the DarwinHSST023 might (say) represent some sort of area algorithm incorporating data from station thousand(s) of km away. This is possibly acceptable if you state its method and use. What is not acceptable is to pretend (by same-name retention) that some HSST actually IS the correct temperature picture of Darwin – rather than what we know was the actually measured temperature. I don’t know why we let them get away with it.
S.1733 Cap-and-Tax Energy Inflation bill text: http://www.opencongress.org/bill/111-s1733/text articles, blog, and can comment on the text of the bill line by line.
AGW proponents have to make a decision now that all the evidence they used to support their case has been discredited and debunked. Either they keep on with the mantra without any evidence in which case they are simply acting like clueless children, or they admit they have very likely got it wrong and they have to go back to square one and try to find evidence to support their case. If you are one of them, which one is it for you?
Has anyone wondered if the 1908 Tunguska comet explosion in Siberia could have effected measurements in some way. This article mentions the comet creating Noctilucent clouds forming a day later thousands of miles away.
http://insciences.org/article.php?article_id=5899
A few posters have pointed out that the scam will be self defeating over time once it becomes evident that the scare mongering projections have not come to pass. However, I doubt things will turn out that way.
In ten or twenty years, or whenever the evidence of our own eyes refutes the warmists prophecies, the world will be a different place. The UN will have set up its monitoring, tax collection, and enforcement regime, or as I like to think of it “Proto-world government”, the MSM will have moved on, climate scientists will have learned their lessons (no more stray emails/more cunningly fudged data), and very frustrated and angry ruling elites will have neutered the internet.
Our only hope is to kill all of this today before it becomes entrenched.
Following weather undeground, Darwin is about to smash its previous record temperature for December (the previous record dates back to 2001).
Is weather undeground also adjusting its values?
Nick Stokes (22:46:31) : on 20/12
GG’s near-symmetric sort of Poisson distribution:
The weakesses with this study are several fold. One is evident from a station in an older city with UHI. In Melbourne for example, various comparisons with other sites show it likely that UHI ‘maxed out’ at Melbourne Central some time before 1950. That is, from humble beginnings, the temperature from UHI rose steadily to (say) the 1930s and then remained about constant because nothing was explainable or available to push the UHI much higher. So Melbourne would be one of the stations in an 80-year plot that whould be near the median, despite having UHI (from studies already referenced) of up to 10 deg C.
Depending on the geographic location of the thermometer with respect to development around it, there must be a host of other cities in the gg data set that show that same “false” response. That is, one part of the comparison between adjusted and unadjusted is incomplete.
I take you pount that one swallow does not make a Spring – but I am using a town familiar to me to reduce the likelihood of spurious effects unknown to me. I would strongly suspect that Adelaide and Sydney have the same problem. Even a 100-year analysis might fail to pick up the main part of UHI.
One swallow might make a tablet go down better.
Your accurate analysis has been invalidated by governement computer models and a global consensus, therefore your work remains accurate but unacceptable.
Is it possible to incorrect something to make it ‘correct’? In anycase make sure you continue not doing this, but I apologise that this is simply not acceptable!
Good work Willis (the unacceptable)
Dr David Bellamy, well known BBC presenter (who no longer seems to appear on the BBC) has written to the Daily Telegraph thus…
SIR – The only good news to come out of Copenhagen is that, in the words of Greenpeace: “There are no targets for carbon cuts and no agreement on a legally binding treaty.”
Hooray! Along with tens of thousands of global-warming sceptics, the world can now breathe a sigh of relief and return to the sanity of real science, which counsels that carbon dioxide is not a poison, let alone likely to cause a heat-driven Armageddon.
We can now burn non-sulphurous coal again to ameliorate the effects of the colder climate that has already been with us for the past decade and is likely to stay for the next 30 years.
Dr David Bellamy
Bedburn, Co Durham
http://www.telegraph.co.uk/comment/letters/6851649/After-a-decade-of-global-cooling-we-should-sigh-with-relief-at-Copenhagens-failure.html
Michael (00:47:30) :
An excellent case example of the end result of AGW driving public policy the wrong way on the freeway. The MSM is glued to the Agenda of pumping as much Global Warming through Going Green advertising to an obsession with “Scientists find more evidence of Global Warming”. What the MSM should be reporting is the increasing cold & snows of Southern and Northern Hemisphere winters.
i.e. – the MSM should be focused on what is going on rather than what is being wrongly predicted year after year after year.
Willis Eschenbach (23:51:16) :
The reason why I believe that GG’s histogram is highly relevant goes back to your reaffirmed statement
You can’t change the global record by changing one station. If the adjustment moves trends up and down almost equally, they won’t reinforce anyone’s preconception.
Anyway, I’ve collected the argument in a post on my blog site. I’ve also calculated the statistics of trends since 1940, to show that Darwin’s post-adjustment trend is in the upper tail, but not extreme. And it would not stand out among the unadjusted station data either.
pete m (01:25:23) :
GHCN homogenization does not adjust for UHI. It corrects for discrete events that it detects by time series analysis. Things like station moves, equipment changes, MMTS introduction. There’s no particular reason to expect those to go up or down on balance, but no reason not to either.
Someone mentioned Bethell’s paper upthread, in which he said back in the ’70’s that some noted NZ stations had decaying Stevenson screens. Well, those would have been replaced in the years since. Each replacement would have caused an adjustment. It would say that there was spurious warming in the past (screen decay), and push the readings down. etc
O/T: Mayon looking ominous, raised to alert level 4 yesterday.
Volcano Live
Guardian
Times
ABC News
Carrick (23:45:16) :
Check the comments at Romanm’s blog for discussion of his diagram. The pattern that he shows is what you expect, because if plots the cumulative effect of adjustments as you go back in time. And the slope is about equal to the 0.0175 C/decade of GG. As I said there, they represent two different variable plots of the same data. If you take trends over time, and look at the distribution over stations, you get GG’s. If you average over stations and plot over time, you get Roman’s. The trend of Roman’s is equal to (approx) the average of GG’s.
Michael R (23:33:12) :
I am unsure of the point you are trying to make? Are you saying that because others adjust downward then the total effect cancels out and therefore the temp record is reliable? In what way, does showing that adjustments were made to other data nulify the fact that there are issues with this station?
No. I think that the adjustments are made for a good reason. I’m answering the suspicion that they are done to deliberately enhance warming. The fact that the nett trend is small means that they don’t have that effect (or only to a small extent). Crudely, if someone was trying to rig the effect, they aren’t doing very well.
Did the Met office ever release the global datasets of raw temperature?
It’s actually quite simple if you stop and think about it.
Darwin is in Australia. Things are reversed here. Christmas is in midsummer. It gets cooler as you go South. The water goes down the toilet in the opposite direction.
So when the raw data show temperature going down, the graph should be inverted to match Northern Hemisphere norms.
Isn’t that standard practice for climate scientists?