Guest essay by Frank Lansner
Presentation of the Original Temperatures project.
Contents:
1. Introduction
2. Methods
3. Adjustments of temperature data
3.1. Adjustments: HISTALP – by the Austrian ZAMG
3.2. Adjustments: ECA&D – by the Dutch KNMI
3.3. Adjustments: The BEST project
3.3.1 BEST / Austria
3.3.2 BEST / Denmark
3.3.3 BEST / Hungary
3.3.4 BEST / UHI
3.3.5 BEST prefer unadjusted data
4. Results from original temperature data
1. Introduction
The number of adjustments of temperature data appears overwhelming and often undocumented. Are we facing homogenization of temperature data? Or is it “pasteurization” (= warm treatment) of temperature data?
As a sceptic it is my opinion that we need to know for sure. I therefore started out 18 months ago collecting original temperature data and now I have started presenting the results on www.hidethedecline.eu
I experienced a lack of will from the national meteorological institutes to freely share the tax paid data I asked for. I even had assistance from a large Danish Newspaper to ask the questions for me, send mails etc. I asked for raw data from datasets beginning before 1950, especially the non-coastal stations:
In my analysis of the Czech Republic today I use around 50 stations. The national Czech meteorological institute wanted 3450 EUR for 10 longer datasets (just yearly values).
Data sources: Meteorological yearbooks, statistical yearbooks, World Weather Records, national archives, books, different databases (NACD, NORDKLIM etc.), web sites Tutiempo and more.
The number of existing longer temperature series is large. Even smaller European countries often has around 50-70 longer datasets available. And for example already in 1945 Spain collected temperatures from 500 stations.
In the following I will try to answer these questions:
1) What does original temperature data tell about the climate now?
2) What does original temperature data tell about adjustments in climate science?
Fig 2: You will need some patience if you want to collect original temperature data.
2. Methods
OAS and OAA locations – how geography determines temperature trends.
For all areas analysed (almost 20 countries by now) we see a large group of stations with warm temperatures trends after 1930 (“OAA” stations) but also a large group of stations with very little or no warm trend after around 1930 (“OAS” stations).
The classification of OAA versus OAS simply depends on geographical surroundings.
Fig 3
In the writing “RUTI Coastal stations” (based on GHCN V2 raw) I found that Non-coastal temperatures (blue graph) were much more cold trended from around 1930 than the Coastal trends (red). http://hidethedecline.eu/pages/ruti/coastal-temperature-stations.php
Fig 4
But Non-coastal stations can be divided further into Ocean Air Affected stations (“OAA”, marked yellow) and then Ocean Air Shelter stations (“OAS”, marked blue).
OAS areas thus have some similarities with valleys in general, but as illustrated above, the OAS areas cover a slightly different area than the valleys.
In general I have aimed to find average OAA temperature trends and average OAS temperature trends for the areas analysed. For each country analysed I have made comparison between national temperature trends as published by the “BEST” project and then the OAA and OAS temperature trends from original data. I want to know if BEST data use both the warm trended OAA data and the more cold trended OAS data. In addition, I have made comparisons of ECA&D data versus original for many countries and also HISTALP data versus original.
More info can be found on:
http://hidethedecline.eu/pages/posts/original-temperatures-introduction-267.php
3. Results: Adjustments of temperature data
3.1. Adjustments: HISTALP – by the Austrian ZAMG
Fig 5 The Austrian ZAMG website “HISTALPS” (http://www.zamg.ac.at/histalp) presents their versions of Alpine temperature data online for Austria and several nearby areas. All datasets seem to show a clear warming trend.
Fig6
However, the valley stations in best possible shelter against ocean air (OAS) have all been adjusted by ZAMG to show warm temperature trends.
From Original data we can see, that the cold trended stations (OAS) are in fact in a comfortable majority in the Alpine area and I believe ZAMG should explain themselves.
More examples of HISTALP/ZAMG adjustments from many countries:
http://hidethedecline.eu/pages/posts/original-temperatures-histalp-264.php
More on original Alpine temperature data:
http://hidethedecline.eu/pages/posts/original-temperatures-the-alps-273.php
3.2. Adjustments: ECA&D – by the Dutch KNMI
To evaluate ECA&D temperature data I have so far mostly studied the differences between temperature data from Tutiempo and ECA&D. Tutiempo do not change data after they first publish it. I have this from mail correspondence.
On the other hand, ECA&D frequently adjust their datasets and thus normally, ECA&D represents newer versions than Tutiempo. Therefore the difference ECA&D minus Tutiempo often tells us about the adjustments done lately to the data represented by ECA&D:
Fig 7
ECA&D temperature versions versus Tutiempo versions averaged for each nation.
For most countries analysed, ECA&D temperature data versions have warmer values for temperatures than Tutiempo in recent years. Especially for the years 2010-2012 ECA&D seems to add a lot of heat to data when they adjust.
I will ask some of you to download ECA data from these locations:
http://eca.knmi.nl/indicesextremes/customquerytimeseriesplots.php
http://www.tutiempo.net/en/Climate/europe.htm
Online data can change or disappear any minute…
More on the ECA&D adjusted data:
http://hidethedecline.eu/pages/posts/original-temperatures-ecad-263.php
3.3 Adjustments: The BEST project
The BEST project collects data from different sources often already related to NOAA and NCDC. BEST often present multiple versions/copies of the same longer datasets already used repeatedly in climate science. BEST have not required the large bulk of existing temperature data from the national Meteorological institutes.
Fig 8
For all countries analysed so far, the BEST national data is nearly identical with the coastal trends and the Ocean Air Affected (“OAA”) locations. The data from the Ocean Air Shelter (“OAS”) stations appears to be completely ignored by the BEST project country after country after country. Just as we saw for HISTALP.
3.3.1 BEST / AUSTRIA
Fig 9
Also for Austria BEST closely follow the OAA area station temperature trends; it’s impossible to see that the majority of Austrian stations – the OAS valley stations – have had any impact on the national result from BEST.
3.3.2 BEST / DENMARK
Fig 10 Danish temperature stations used in the “Original Temperatures” analysis.
Red arrows: The BEST project only use longer data series from coastal stations.
In fact, DMI (the Danish meteorological institute) will not share any other long temperature sets with even the Danish population, and DMI claimed not to have the older data we asked for on digital format. I had to dig data up myself. (So now i hold tonnes of Danish climate data in digital format that DMI dont have?)
Blue areas on the graphic above are best sheltered against the dominating western winds of ocean air and they are labelled “OAS” below.
Fig 11
Average of Danish coastal temperature series from original data and then the 5 longer temperature series made available by DMI for the public and climate science including BEST. The blue graph is an average of all Danish OAS areas (all blue areas in fig 9) created from original data.
More on Denmark and South Sweden:
http://hidethedecline.eu/pages/posts/original-temperatures-denmark-and-south-sweden-270.php
3.3.3 BEST / HUNGARY
Fig 12
For the Hungarian Valley (one of the largest OAS area in Europe), the BEST team has used an OAS temperature station “Pecs”. Above, the Pecs temperature trend is shown together with other Hungarian stations. These original data do seem rather homogenous?
Fig 13
None the less, the BEST team adds around 0.7 K of warming to the Pecs data. BEST use a so called “Regional Expectation” for all countries i have analysed, and change original data so they approach these expectations. Best also claim that Hungary as a nation has experienced this warming trend.
More examples of how data from OAS stations has been avoided by BEST, see for example from fig 22 and onwards for German OAS stations:
Erfurt, Halle, Fulda, Kassel, Kaiserslautern, Mannheim, Bamberg, Hamburg, Kiel, Lubeck, Magdeburg, Nurnberg, Ulm, Augsburg, Leipzig, Arnsburg, Torgau, Bayreuth, Brausnchweig, Regenburg, Stuttgart and Darmstadt. (Ok, Hamburg is not an OAS station, but BEST can change data from these too…)
http://hidethedecline.eu/pages/posts/original-temperatures-germany-276.php
I cannot document the fate of all temperature stations used by BEST and this is why I primarily aim to document the adjustments country for country, see more:
http://hidethedecline.eu/pages/posts/original-temperatures-best-265.php
3.3.4 BEST / UHI:
Best claim that UHI plays no role. But remember results for all 11 countries analysed; First BEST first avoids the cold trended stations (by deselecting or warm-adjusting OAS stations) and THEN they compare the remaining warm trended OAA stations with city stations. It is on this basis that BEST concludes that UHI is not an issue in climate data.
Here is how UHI affects “climate” data in real life:
Fig 14. Some Rhein-Ruhr stations illustrated together with some nearby stations. Base period 1900-1920. What flavour of Urban heat warm trend do we want?
3.3.5 BEST prefer unadjusted data
BEST also claim that they prefer unadjusted data over adjusted. So why did they not require the large bulk of unadjusted longer datasets from national meteorological institutes and year books like I did?
Fig15. From the BEST FAQ web site.
BEST adjustments leads to the ignoring of the cold trended stations, the stations from valleys (OAS areas). So is it true when BEST claim not to use adjusted data? The red box above is my suggestion to an update of their FAQ-text. See more in “Original temperature: BEST”.
4. RESULTS FROM ORIGINAL DATA
Fig16
Observed original temperature trends from some stronger European OAS areas. The areas in shelter of ocean air show little or no heating I Europe from around 1940.
Fig 17
By using base period 1961-1990, we see that the OAS temperature datasets shown in fig 16 from different countries in Europe are in fact rather similar. That is, valleys not disturbed much by ocean air winds in different areas of Europe show almost the same signal, the same story.
In general, the warmer years in recent decades appear to have temperatures that resemble the warmer years before 1962.
Fig 18
Recent decades of coastal areas are 0,5-1 K warmer than the 1920-50 warm period.
Fig 19
European Coastal trends versus Land trend from Ocean Shelter Areas.
Fig 20. Land stations in shelter against ocean air show that the warming 1930-60 was rather similar to the warming 1990-2010.
What does the missing warming of areas not much affected by ocean air temperature trends indicate?
My thoughts:
Or alternatively, perhaps the CO2-theory suggests a pattern where land areas with little noise from ocean air trends show no heating after around 1930? Or can the climate “science” very fast produce a paper with such a conclusion?
Fig 21
In the writing “Original temperatures: The Hungarian Valley”, the area in the red circle above was examined. This area is one of the largest and best Ocean Air Shelter areas in Europe. For Astronomic purposes you would put your antenna on a mountain peak, but for observing climate signals as pure and strong as possible you should consider using the valleys or “Ocean Air Shelter” areas to get the strongest and purest climate signal.
Let’s take a look at similar areas in other areas of the world:
Fig 22
In all cases GHCN raw V2 temperature data (shown in RUTI articles) do not show recent temperatures warmer than for example the 1930´ies. In all cases these specific areas represents some of the most cold-trended areas of the respective continents.
For the US MIDWEST, the air masses from the Pacific first have to pass more than a thousand kilometres of mountains and thus the temperature trends in the US Midwest have unusually little noise from ocean air temperature trends.
Fig23
From RUTI USA: The number in each 5×5 grid tells how much warmer or colder the decade 1998-2008 is compared to 1930-40. In many cases, the recent decade is half a Kelvin colder than the 1930´ies.
This illustration is taken from “RUTI: USA”.
http://hidethedecline.eu/pages/ruti/north-america/usa-part-1.php
http://hidethedecline.eu/pages/ruti/south-america.php
http://hidethedecline.eu/pages/ruti/australia.php
I think all in all on the described basis it is fair to conclude that the missing warming in areas in shelter of ocean air is likely to be a global phenomenon. Any protests?
Is it fair then to call the missing warming after around 1930-1940 of areas in shelter of ocean air a global problem for the CO2-theory?
Or do CO2-theory explain why temperature stations in best possible shelter against ocean air winds cannot really show warming after 1930-40?
PS: Please let me know if you have access to original temperature data, we need to expand the database of original temperature data.
Frank Lanser:
Happy to see others interested in exposing the difference between corrupted and/or manufactured data and that which is the product of pristine measurements. The problems ecountered in digging out the latter are not just the usual ones of historical research or of bureaucratic inertia; they seem to be matters of political warfare. Keep up the good work!
Although I have not done an exhaustive review of the literature, only TOBS error means appaear to have been studied/modeled/adjusted. No one, to my knowledge, has ever looked at TOBS error variances. While an adjustment of the mean may seem a logical way to correct for biases, it does not correct nor have any effect on variances. If the TOBS error introduces enough uncertainty, then a trend may not be statistically significant, even if there is a bias correction.
I have spent several years looking at TOBS in the hope to someday publish something, but, for several reasons, it doesn’t look like I will be able to do so by myself at this time. The chart below is an example of some of my research. It shows the “Confidence Interval” due to TOBS adjustments. This is calculated as follows.
Using hourly data, I calculated an “actual mean” as of midnight each day. Although there are several ways to approximate the “actual mean” in this manner (I looked at the rectangular approximation, the trapezoidal approximation and Simpson’s Rule), the differences are not very large. For simplicity, I used the rectangular approximation (i.e. adding the 24 hourly temperatures and dividing by 24). Then, I computed a maximum and a minimum for the previous 24 hrs, using the highest hourly number as the maximum and the lowest hourly number as the minimum.* I then repeated this for each “time of observation”, by sliding the 24 hour window one hour at a time for each of the 24 hours. A TOBS “error” was then calculated for each hour by taking the difference between the maxmin mean and the “actual mean” for the 24 different “times of observation.” I then calculated the standard deviation of the errors for each hour of each day over a one year period. The chart below was calculated using hourly data for Fort Smith Municipal Airport, Arkansas for 1984. It appears to be typical.
The “confidence interval” is calculated by taking the standard deviation of the temperature in Fahrenheit, converting it to Celsius, multiplying by 1.96 (2 sigmas) and then dividing by two to obtain a plus and minus “X” pseudo confidence interval. This purports to show the variance of the TOBS error due purely to a change in the time of observation using actual data.
The implication of this seem obvious. Since the rate of warming is supposedly about 1°C per century, it would seem that any trend based on afternoon observations, where the TOBS error appears to create an additional ±2.5°C uncertainty (for 5:00 P.M.), would not be statistically significant. Maybe a claim can be made that this uncertainty is reduced by appealing to various statistical miracles, but, at first sight, this would seem to be a significant hurdle to overcome.
Preliminarily, I would submit, therefore, that no conclusions regarding long-term trends can reasonably be made based on stations with afternoon observation times. Conclusions regarding long-term trends based on stations with morning observation times have a much smaller TOBS uncertainty (±1.5°C for 7:00 A.M.), but this is still large. I would say that this analysis of the apparently large uncertainties created by TOBS errors cannot be used either to prove or disprove (C)AGW or any other theory. Instead, it would appear to highlight serious problems with the available data that preclude any strong conclusions. Likewise, I think this analysis calls into question the validity of any TOBS adjustments.
It would appear that there is enough variability in the shape of the daily temperature curve that an adjustment of the mean cannot produce a bias correction within an uncertainty that is useful for estimating temperature trends. I would also say that, although TOBS corrections are not done for all global data, the TOBS error uncertainty shown in this chart is probably present in most global data, as probably relatively few stations have an effective observation time of midnight.
Since I still have some hope to publish this someday, I hereby claim copyright, and everything else I can to preserve whatever I can for as long as I can.
*Karl et al., 1986 has a discussion beginning on page 7 of the pdf (pg 151 of the published paper) of the differences between the actual maximum and minimum and the hourly max and min. Please refer to Table 3 in that publication for specifics, but these differences appear to be an order of magnitude smaller than the calculated TOBS error uncertainties.
P.S. Several different people have posted comments at WUWT under the handle “Phil,” so please keep that in mind when searching prior posts.
Here is the chart referenced in my previous comment. The image did not post.
Wow! Eye Candy! Love the work you have put into doing this! If it weren’t for the fact that I have been blessed to find a most wonderful boyfriend, I would be all twitterpated over you instead of him!
!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!
LANSER’S ARTICLE SHOULD BE A WUWT PERMANENT FEATURE
!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!
Mr. Lanser! Magnificent!
Thank you, so much, for sharing all your hard work and fine analysis with us. When one thinks, really stops and THINKS, of all the hours you have put into this project….. one is stunned that there is someone out there as dedicated to truth as you (and, yes, along with Tony B and many, many others equally as dedicated, whose efforts are truly heroic).
How delightful to know that there are lots of little “Franks” (btw, what a perfect name for a truth-teller) growing up (that little girl is darling — hard to stick to the ol’ grindstone with that little sweetie pie calling your name in a sad little voice, “But, Daaaadddeeee, I’m missing you….”, no doubt.). There is hope for the world, yet.
!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!*!
“For all areas analysed (almost 20 countries by now) we see a large group of stations with warm temperatures trends after 1930 (“OAA” {Ocean Air Affected} stations)… .”
+
“For all countries analysed so far, the BEST national data is nearly identical with the coastal trends and the Ocean Air Affected (‘OAA’) locations.”
{emphasis mine}
=
There is no heat hiding in the ocean (else no warmed OAA stations).
So, at the very least, BEST shoots Climate Clown Trenberth in the foot, there.
*******************************************************
BEST is either run by a bunch of crooks or by non-scientists or both.
***********************************************************************
Someone commenting above (who shall remain nameless…) said, perhaps only in jest, that pasteurized “data” may prove AGW fairies DO exist.
Wrong. AGW is dead.
Bottom line: CO2 UP. WARMING STOPPED.
Pamela Gray!!! re: Mister Wonderful — I AM SO HAPPY FOR YOU! After learning what I know of your life, I have been hoping so much that that would happen for you!! (Ievenprayed). I was hoping you’d find someone who likes to fly fish — does he? LOL, if he doesn’t, he’ll learn, huh? He’d better also be VERY intelligent — or he won’t last long… .
That was the happiest post I’ve read here in the entire 9 months I’ve been on WUWT. Thanks, so much, for letting us know.
Smile, smile, and double smile. #(:))
Best wishes, Phil (NOT the DOT — smile) — I sure hope that publishing you wrote of happens much sooner than you expect. No doubt Mr. Lanser will respond to you (I think it was about 2:30am, now, 5:30am, where the roof is that covers that data-covered desk and the pillows on which he and his big family lay their heads at night).
(and Phil in California is yet another goodguy Phil, for everyone’s information)
Heh, heh. I just checked back to see if Pamela Gray responded to my 8:21pm post. LOL, what was I thinking? As if! His gain is our loss. Do drag yourself away once in awhile, though, Pamela, and give us a wave (or one of your blistering, devastatingly accurate, refutations of some of the nonsense that appears from time to time).
OK. So people like Turney and (thousands?) other scientists have millions of dollars for research at their disposal and they can’t think through this like an individual on his own …. Amazing. Great example of scientific mass hysteria and finding what is expected to be found rather than analyzing information to see what interesting things can be found. The hammer and nail dilemma.
Frank, the more I look at your site and work the more I am impressed. Yours is not only the best, but the only coherent explanation I have ever come across explaining why most rural stations in Nebraska, Arkansas, Texas, Oklahoma, Missouri to name a few, your dotted area of this effect in the US, all show nearly flat records, some even negative, from 1895 onward. I look forward to absorbing some more as I get more time (broken pipes put a bit of kink in that). You seem to be on to it.
TB says:
Just 2 mins of looking and I have data from the station I worked at in 1987 – going back to 1930.
Yes, there is a whole bunch of monthly station data available from Met Office, this is what Euan and Clive Best used for their recent article on sun-hours.
However, they seem to keep the daily data under wraps. One or two of the longer stations want to change something silly the 350 GBP to give you the daily data.
If you have any means to access daily data it would be interesting to see, because crude monthly averages are a very poor way to analyse a system which is heavily influenced by a massive satellite with orbital parameters of 27.3 27.55 and 29.5 days !!
TB says:
January 6, 2014 at 3:28 pm
Very good points to raise about linkage with SST. The coastal affected vs non coastal area distinction that Frank is looking at is interesting but needs to taken in context of known meteorology without being too simplistic.
There are all sorts of known phenomena which will affect cloud cover as air comes in land and rises over mountains. It takes very little change in cloud cover to make the tenth of degree scale changes everyone wants to get excited about.
I think the truely alpine stations of the HISTALP project may be informative if we can obtain the “ORI” data before they added 1 degree warming to the data.
Yes, yes, blank Jim, I HEAR YOU YELLING (all the way from Texas — they can yell MIGHTY BIG, down there, heh). Lansner. Please pardon my careless mistake, Mr. Lansner.
Frank Lansner says:
Greg, i have only a link to what i used from HISTALP/ZAMG, the homogenized data:
http://www.zamg.ac.at/histalp/Statmod_AT_T01.html , see the ZIP files in the bottum, here fore Austria.
My original files has not been put online. At some point this is of course the goal but i dont want to face legal problems, so im not sure i can put these data in digital format online.
But I would like to hear opinions on this.
=====
Thanks for the clarification. HISTALP claim on their site that ‘original’ data is available but that does not seem to be true. My guess is that it was included at some time in the past but has now been hidden from sight. They have not removed the text where they claim it is available.
If you read the Boehm 2009 paper that shows the flawed and speculative adjustments that they have derived from Hohenpissenberg 😉 and applied to all other stations. Equally the hourly data and documentation of the changes does not even appear to be in peer reviewed literature. Simply some “conference proceedings” document which is not even linked anywhere.
http://i43.tinypic.com/x41aoo.png
You can see in the original data that 1780 was warmer than 1950 ! Most of 19th and first half of 20thc gets cooled by almost a full degree. Then we start to worry about almost a degree of global warming.
It’s also interesting that this record bottoms out around 1880 unlike the usual SST records that are coldest around 1918 and still quite warm in 1880.
wayne says:
January 6, 2014 at 9:00 pm
“Frank, the more I look at your site and work the more I am impressed. Yours is not only the best, but the only coherent explanation I have ever come across explaining why most rural stations in Nebraska, Arkansas, Texas, Oklahoma, Missouri to name a few, your dotted area of this effect in the US, all show nearly flat records, some even negative, from 1895 onward.”
Its kind of funny, also i have heard “climate scientist” say : “We dont know why Turkey has not been warming much”..
Well… one look at Turkey on a map explains it. Its full of mountains almost out to the shores, and therefore most of the country is valleys, OAS. Bingo.
See “Original Temperatures: Turkey”:
http://hidethedecline.eu/pages/posts/original-temperatures-turkey-269.php
Thank you so much for comments ALL!!!!
Greg Goodman says:
“Yes, there is a whole bunch of monthly station data available from Met Office, this is what Euan and Clive Best used for their recent article on sun-hours.
However, they seem to keep the daily data under wraps. ”
If you adjust data, normaly you fiddle with the yearly data. You dont adjust every hourly reading or so, and yes, hiding daily data does smell a little. Especially when we talk about climate data.
TB and others!
Thankyou for sending links to (hopefully) original temperature data!
TB: For UK I do have something too, actually rather fine stuff, but what strikes me is: How come I have had no luck finding meteorological year books for the UK? A country with 55 million people, there should be plenty of this stuff out there. Perhaps i just have not had the luck with Uk… or the market somehow has been vacuum cleaned for meteorologicla year books.
Still: I live in Denmark, and A LOT of material is fully available in libraries of other countries, especially the USA!!!! If anyone out there is just as nerdy as me, and actually look up this stuff, takes photographs of all pages with yearly data in meteorological year books it would be fantastic. But lets coordinate what material is in fact missing. Hope to hear from “a crazy bugger” like me…
Frank
As you know my particular interest is in historic temperatures prior to 1850, as there was generally greater variability and lows and highs of temperatures and weather extremes then. (see my link at 1.17 above)
I visit the Met Office library frequently. I know there are original copies of the US Monthly weather report back to around 1870. I will call in to the library this week if I can and see if it contains original information that might be useful to you on the US
TB has pointed out various sources in the UK. I tend to concentrate on CET, and as you know there are two major data sets based on it. There is monthly data compiled by Gordon Manley to 1659 and the record back to1772 compiled by David Parker who I met up with a couple of weeks ago. He is interested in my project to extend CET to 1250AD.
The 1772 record is the one mainly used by the Met office but it does not include the very intriguing uptick in temperatures during the first three decades of the 1700’s which caused Phil Jones to write a paper in which he queried whether natural variability was greater than he thought, as the temperatures in the 1730’s were only fractionally below that of our warmest decade in the 1990’s and is by far the biggest ‘hockey stick’ in the long record.
David’s article on how he compiled 1772 is I think included in my article ‘the long slow thaw’. You must know however that CET has been constantly adjusted so the only original data is likely to be in David’s original paper .
As regards longer records that have been adjusted it is worth looking up the ‘improve’ project funded by the EU in which seven long temperature records were examined and adjusted. This contains references to original data primarily in Italy
http://www.isac.cnr.it/~microcl/climatologia/improveb.php
Data is routinely adjusted and I think it would be helpful if the reasons for it could be explored as there MIGHT be a valid reason. Personally I become bemused when temperatures from say the 1930’s are adjusted 70 years after the event.
Will let you know what I find at the Met Office library regarding the US record. Is there anything else that I could specifically look for whilst there?
all the best
Tonyb
Good job. Other people keep trying to find “good” temperature data to test the “mainstream” claims, such as BEST. The Surfacestations site for example is important.
Seven rural temps in western europe with long term temperature records show zero warming.
http://hidethedecline.eu/pages/ruti/europe/western-europe-rural-temperature-trend.php
Another place with well maintained surface temperature records over less time (since 1958) is Antarctica.
Amundsen-Scott, Halley, Davis and Vostok stations show zero warming since 1958.
Original temperature data for the south pole station are maintained at the Univ. of Wisconsin.
Frank, congratulations on a really impressive piece of work!
Here’s something I just discussed on the topic of Norwegian temperatures that might interest you: We’ve just had the rainiest snowless Christmas for years, and today there’s around +7C outside, not the typical January temperatures. Of course, some alarmist are seizing this opportunity to sell the idea of “No more White Christmas”, despite several recent Decembers having been extremely cold (which also was blamed on “climate change”, of course).
So I had a look at the official Norwegian December record – and it actually shows that the Decembers of the thirties were slightly warmer: http://eklima.met.no/metno/trend/TAMA_G0_12_1000_NO.jpg
However, the current warm period is wetter:
http://eklima.met.no/metno/trend/RRA_G0_0_1000_NO.jpg
It’s interesting to see that the “great European climate step change” which seems to have occurred around 1987-1989 isn’t very visible in Norwegian temperatures (at least compared to some of your records above, where it is easily visible), but it’s clearly visible in the precipitation record. I guess a warmer Atlantic may give a wetter Norway?
In any case, has anybody been able to give a good explanation of what really happened in the 1987-1989 European climate shift?
This is the Most important post of 2014 deserving a sticky.
tonyb says:
January 7, 2014 at 1:32 am
“As you know my particular interest is in historic temperatures prior to 1850, as there was generally greater variability and lows and highs of temperatures and weather extremes then. (see my link at 1.17 above)
I visit the Met Office library frequently.
”
Hi Tony my good old friend 🙂
Again thankyou for all your intense studies year after year!!!
Now… What does it take for me to make you go to that library, take photos of UK meteorological year books, the summaried for the stations???
If it is of any comfort, I have taken 42.000 pictures of handwritten sheets in the Danish National archives… he he… And the meteorological year books will be done within a few days….. notch notch notch??
I can offer champaigne and whatever it takes-…!
All the best to you too, always cosy to hear from you!
K.R. Frank
Espen!
Thank you su much for the comment!
And ou know what?? Norway is the country im working on right now, it is SO interesting work because Norway “HAS IT ALL” !
Norway has Coast line, HIGH mountains, and THEN THEN THEN, Norway have deep valley, umm what a yummi.
And on top, Norway has so many many long temperature stations, fantastic. I am working with i guess around 100 long Norwegian stations, so it will take some time.
And, in all the coutnry articles i add all kinds of observations, so if you come up with something Norwegian maybe we can fill it in. Im ready with my stuff in a week i think.
K.R. Frank
About “sticky post” etc: Thank you for the kind words.
But see this from Anthonys side: The truth is, that this work is done without the power af a large organization. This means that the risk of “something wrong” is there although i think my findings are solid.
If Anthony makes too much out of this and then “something is wrong” its a blow to the credebility of his site and nobody wants that.
Instead, check out how many articles are coming out on WUWT now, and notice that Anthony none the less took the time to publish this large writing. For this im grateful.
Perhaps when all are sure this is solid it will be taken to a higher level.
What an ambitious project.
Just thinking out loud here.
I’ve thought about going to the public library and requesting the original hard copy temp records being kept. Several years ago I looked up the temps on my date of birth throughout Colorado. Just for fun.
Instead of sitting down and transcribing all those tables by hand, error prone and tiresome, why not develop a phone app designed to do two things:
1) save the image for documentation,
2) covert the tables into spreadsheets.
Simple no? Already done on PCs: http://www.minipdf.com/scan-to-excel/picture-to-excel-spreadsheet.html
So take pictures of original hardcopy. Convert to spreadsheets.
Import spreadsheets and images into database.
Done.