Today I’m going to discuss another Russian gridcell 62.5N; 77.5E, which is one of the gridcells that was identified by IPCC as having a particularly strong trend . Warwick Hughes previously analyzed this cell because of this here, with this map highlighting the location of the Tarko-Sale gridcell in the top left corner of the map.
The following analysis is based on the GHCN station Tarko-Sale (23552), a town with a population of 18,500 founded in 1932, about 560 km to the south-east of Salekhard. Anorther GHCN, Aleksandrovskoe, is in the gridcell and is discussed by Warwick, but not discussed here. I may return to it on a future occasion.
We’re getting to gulag country here and the date of the establishment of Tarko-Sale seems gulag-esque. In browsing information on the area, I noticed some interesting local iore, including the use of max-min thermometers by criminals as a murder weapon. So we’d all better be careful not to rile the meteorologists.
In the early 1950s, Stalin decided to extend the Russian railway system from Salekhard to Igarsk using gulag labor. The work was abandoned, leaving little modern trace. An interesting account here describes the construction camps, mentioning in passing that:
Criminals could pour mercury from a thermometer into the ear of a sleeping man; in the morning he would simply not wake up.
Who knew that thermometers could be such a deadly weapon? A new answer to the Clue board game – Dr Jones in the library with a thermometer.
Anyway, back to statistics. My emulation of the HAdCRU3 gridcell using the Tarko-Sale GHCN v2 data is pretty close. The periods of coverage are almost identical. In the figure below, I’ve illustrated three data sources:
1. HadCRU3 gridcell 62N; 77E (annualized) 1936-2006
2. GHCN v2. This has 3 versions which cover 1937-2006. I’ve used the average of all three versions, which slightly overlap. I don’t know where the 1936 value in HadCRU comes from – maybe there’s another station in play.
3. GHCN daily data from 1995-2006 from which I calculated monthly and annual averages.
A few obvious conclusions from this emulation exercise. First, I’m able to calculate something that looks a lot like the HadCRU3 gridcell using third-party data. Second, HadCRU3 values in the 1930s and early 1940s are 0.5-1 deg C colder than the corresponding (unadjusted) GHCN v2 versions. So far I’ve not assessed whether GHCN adjusted this particular series nor why they did so, if they did. Third, and this is interesting, while the HadCRU3 gridcell values in the 1990s and 2000s are close to the GHCN v2 values, both run consistently warmer than my calculations from GSN daily data.
Top: HadCRU3, GHCN v2 and GSN Daily versions; middle HadCRU3 minus GHCNv2; bottom – HadCRU3 – GSN Daily.
Finally, for what it’s worth, regardless of version, this particular gridcell does not have give me the impression of a statistically significant “trend”. There are a couple of warm episodes in the latter part (seemingly somewhat enhanced by the GHCN and CRU “adjustments”), but the graph itself looks stochastic and ends on a low note. If this your mutual fund value, you would probably not be impressed by your salesman telling you that it demonstrated consistent growth.
Update:
Here’s the picture from IPCC (2.5 vintage) showing the elevated trend in this gridcell.
Warwick Hughes said that this graphic was based on Jones 1994, for which data is available. Warwick reported here that:
The Jones 1994 data for Tarko Sale extends for only 25 years — from 1967 to 1992 — and has gaps totalling 56% of the record. It is not apparent why the thirty years of data prior to 1967 was not used. The years that have been selected result in a warming trend which would not have existed if the full length of Tarko Sale data had been used.
You can see the validity of Warwick’s comment by inspecting the above graphic. What makes the Jones exclusion in the earlier data base even more puzzling is that the earlier data was available in NDP048 (although I’ve not checked GHCN v1 yet.)
Climate Audit 
25 Comments
GHCN does have adjusted mean monthly temps for Tarko-Sale.
It does not have monthly min/max temps.
Jerry, there are daily max-min values for Tarko-Sale for the limited period 1995-2006 here http://www1.ncdc.noaa.gov/pub/data/ghcn/daily/gsn
RE: GHCN v2
The ~ 60 year quasi sinusoidal “signal” recently noted by Zhin et al seems to be reflected here. Apparent peak in the early 40s, and maybe we have just passed another one in the early 00’s.
Steve,
Yes re the recent daily data. I mentioned the lack of monthly
min/max in GHCN partly as a suggestion that the monthly mean
temps in GHCN for that location may not be (min+max)/2, as
is the case with most, but not all, stations for which GHCN
has all three sets of numbers.
Re #4 ambiguous wording check:
for most, but not all, locations for which GHCN has monthly
mean, min, and max, temps, the means are (min+max)/2.
Steve,
with data like that who needs enemies? I’m starting to think that — despite the obvious limitations — tree rings might be better thermometers than actual thermometers in places like Russia/USSR. At least trees can be sampled in truly rural areas.
Onar, wait till you see the data for 57.N 77.5E if you want to see a real mess.
RE: #71 – Is that Warwick’s station 21 according to his scheme, right at the edge of Sverdlovsk? 😉
I wonder if this is not just a “rural myth,” since you can eat mercury without harm.
I read Warwick’s articles that Steve M linked in the first paragraph. Great stuff! Anyone who reads this and doesn’t question Jones’ methods and results has to have some kind of blinders (political lenses?) on.
With so much “rigging” going on with the GAT data, no wonder the correlations with solar phenomena have “fallen off” in recent years.
I wonder if this is not just a “rural myth,” since you can eat mercury without harm.
I really don’t see how this would not wake the victim up…I guess a good test would be to try it on your spouse with water…if you don’t see divorce papers within a week…it is plausible.
First time poster.
First, thanks for incredible informative web site.
Tarko-Sale:
I visited Tarko-Sale couple of times as member of environmental assessment expedition.
If viewed from the air, terrain in the region is flat, covered with tundra vegetation named yagel, intermittent with shallow lakes and swamps. Not the case with Tarko-Sale. It is wide grayish sand area with one-store baraq-style buildings, surrounded by about kilometer of bare exposed sand. Wheeled and tracked vehicles damage delicate yagel vegetation, and once disturbed yagel dies. It is, actually, good for inhabitants: dead surroundings keep mosquito and bugs count in the city at bearable level. Local airfield has compacted sand runways and sand belt around too. It was always chilling experience to land in AN-24 prop on sand runway.
What I am saying, the UHI effect in this place should be HUGE.
Steve …
When are some of these re-evaluations going to hit the press??
It seems there is some pretty shoddy science underlying many of these key grid cells that contribute to the published temp evaluations that point to Global Warming. It would seem mountains of disinformation could be erased with newer analyses using better methodology and more complete records.
#14. Personally I have no doubt that the late 20th century is warmer than the early 20th century or 19th century. Aside from the temperature records, the proxy evidence (e.g. from glacier recession) is quite convincing.
These notes are by no means “proof” that the overall temperature estimates are substantially wrong and it’s quite possible that the estimates are reasonable even if oversold. So cool your jets on this.
Actually, to really understand this data, my time would probably be better spent analyzing SST data rather than land data, but I sort of like looking at the local geography and local color and I don’t know the SST data right now.
I, too, think there was warming in the 20th century. I just don’t think it was so hockey-stick shaped.
#15
What goes on my nerves is all that hype about “we can do something about the warming and we must do it before we (deservedly) perish” – taking into account that all man-made GHG make 0.3% of all GHG’s in the atmosphere. What about getting accustomed to changes of climate, because that’s what the Earth always did?
Steve, did you look at some other Russian stations from the “heated” gridcells?
Re your #15 Steve,
Because so few USSR stations have decent data back 100 years and they would be mainly urban, I think an important issue is whether the recent climate is warmer than the 1940’s.
Post 15
Steve .. I don’t doubt the temperature changes either. However, I think you would agree that more accurate temperature assessments would be instrumental in better determining processes and causes.
As I understand it, the primary line of reasoning used to implicate Anthropogenic causes involves model results that show that the current temperature warming is beyond what could be accounted for by natural variation. I can believe that anthropogenic forcing is playing a role, but I’m not sold on the claim that it is the primary driving force, or even a major amplifier. A net decrease in the warming over the last century of even 0.1 or 0.2 C could have a profound impact on the interpretation of the model forcings.
Would you agree?
#2
Steve,
Are the Russian data summaries or raw data? I’ve started collecting temperature data at 1 minute intervals and it’s an interesting experiment.
From a geophysical perspective these data are very, very non-linear and anyone who derives classical stats from these data has to be regarded as clueless.
Little wonder global climate models can’t model the real world.
Steve:
You said, “Personally I have no doubt that the late 20th century is warmer than the early 20th century or 19th century. Aside from the temperature records, the proxy evidence (e.g. from glacier recession) is quite convincing.”
My recollection is that in earlier posts on other threads dicussing glacial recession that there was a “concensus” of a 100 to 300 year time lag in glacial response to temperature changes. And I inferred that late 20th century glacial recession is more likely the effect of warming since the LIA. That’s not your take?
Sorry if I digress too much?
Thanks
19
It appears that one big problem with climate models is that the modelers don’t really know what “natural variation” is. The link to Lindzen on the Water Vapor and Cloud Feedback thread does a good job in explaining the circular reasoning used by the modelers. I sure would like to see a response from one of the model experts to Lindzen’s criticisms.
Re #20,
Louis,
Raw.
From ndp040.txt:
“⟄aily mean, minimum, and maximum temperatures are available (to the
nearest tenth of a degree Celsius) for each station. Temperature
observations were taken eight times a day from 1966-89, four times a day
from 1936-65, and three times a day from 1881-1935. Daily mean
temperature is defined as the average of all observations for each
calendar day.”
See Table 1 in ndp040.txt for more details at
ftp://cdiac.esd.ornl.gov/pub/ndp040/ndp040.txt
I looked over the information on Mr. Warwick Hughes’ website and am quite surprised at the physical locations of the stations chosen for many of these climate studies. The examples given on the main climate page for the area around Chicago (Peoria is given as one example) where more rural stations give a completely different result than the chosen, more urban stations, gave me an idea. Part of what has caused all of this controversy over the warming issue seems to come from a lack of transparency in the data used and what has been done with it. Add to that the fact that stations from areas that could be expected to cause a warming result were selected and use to somehow “prove” that the climate was generally warming sows the seeds of skecpticism and distrust.
Maybe there should be an open effort to get data from as many rural US stations as possible and community effort made to see if there is warming or not. If wouldn’t be so important that every station had every reading for every day over a period of say, the last 50 years. If there is a lack of data from this or that station for some period, overall these dropouts should be random and their loss swamped by a hopefully large number of stations where data are available. This doesn’t need to be global in scope or go back a hundred years. I have a feeling that getting data from as many stations as possible outside of major UHI impacted areas for the past 50 years would show very clearly, openly, and without much room for dispute that the rate of climate change is nowhere near that proposed by the sensationalists.
Why is it so hard to simply get data unpolluted by UHI from as many different points as possible, run the data and produce a result? Even if it isn’t global, at least it would show for North America if the sensationalist view of runaway global greenhouse warming is true or not.
I just recorded the last two days of hourly temperatures here in my area, then averaged them as described in the paragraph by JerryB #23.
…………………………………………………….Day 1/Day 2
Avg using all 24 hours:………………… 50.7/44.5
Avg using 1881-1935 method:……. 50.0/45.3
Avg using 1936-1965 method: …… 49.8/43.5
Avg using 1966-1989 method: …… 50.5/44.3
I know this is a gross simplification, but the 1936-1965 method introduced a low bias of 0.9 to 1.0 degrees as compared to using all 24 hours. I think I understand the time of observation adjustments now.