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.
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Wow, amazing job digging up, compiling, and analyzing all this data.
“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.”
BEST uses the same method to mutilate our local region as well. All stations in the region show the double hump, with the 30’s warmer than ca. 2000. BEST then adjusts them to match the “Regional Expectation”- creating a hockey stick.
The peak of the recent warming was about 2002, since when we have seen a considerable drop.
Your OAA/OAS thesis is further corroborated by a recently published paper on the snow pack here. Snow plots and stream flows broke into 2 categories, the divisor being 8500ft altitude on the western side of the Sierra Nevada crest. The lower maritime set showed decreasing snowpacks with earlier stream flows…the continental side showing increasing, later peaking snowpacks and later, higher streamflows.
An interesting exception is Yosemite Park Headquarters, which shows a temperature record matching the Eastern Sierra/Great Basin although it is located on the western side in Yosemite Valley.
I think TonyB may have most of the UK as well, but I am not sure.
more soylent green! wrote, “Should I be bothered that BEST doesn’t know the difference between “extend” and “extent?” Don’t they proofread their own website?”
That’s not actually on the BEST web site. That bit in the red box is somebody’s joke.
Tonyb is or was here
http://climatereason.wordpress.com/
Re: Lansner 9:56 am: We may have such an issue with some of the Dutch stations and therefore i have used averages of 8,14,19 hour reading all the way, exactly to avoid this rare TOBS issue.
There you go, Thrasher. A prime dataset to evaluate just how much difference a theoretical TOBS adjustment will make to daily min-max records. Personally, I think it is lost in the noise.
Lansner (main post): Are we facing homogenization of temperature data? Or is it “pasteurization” (= warm treatment) of temperature data?
Excellent turn of phrase. Worth remembering in any open debate or peer review.
And the summary?
I starting reading this and was trying to read the whole thing, but I did yearn for a summary, the bottom line(s). Can we in a few sentences and a link in our blog posts or comments make it clear that the alarmist scare mongers have made a mockery of the truth and adjusted their way to give the false appearance of hockey stick warming? Or not? And yes, in summary, hiding the data is not good.
What gets me is it seems that every single adjustment, whether “justified” or not, is always made to the benefit of the warmist case. When it’s 1000-1 or 1000-0 as far as pro-warmist adjustments, we can a smell a rat.
” Sadly, it falls in practice because it is the publically available data that has been manipulated and the originals (if they have not be “lost”) are only given to people who can be trusted to “say the right thing” or “help the cause”. ”
Exactly, already manipulated.
I can not applaud this approach enough Frank! It is what has been needed for so long, lurking in the background.
As for the TOB “adjustments” (the time that max/min diurnal readings are observed), just try to get the code that all publically available records are first put through the ringer, good luck, I had little of it. If anyone does have the code (any language) for the TOB adjustments, I would appreciate a link to it. I think TOB at best is a strawman argument along with the WWII SST bucket adjustments but those are great cubbyholes to hide untraceable adjustments.
Great effort Franc. huge piece of worK. Oh and it’s “pasteurization”
Excellent post, Frank. Diligent, thorough, outstanding.
My understanding is that the TOBS corrections were accomplished with model algorithms, resulting in corrections where in some cases none were needed.
From this graph (the 2nd graph here), it appears that for the U.S. Surface Temperature data, TOBS added 0.34 °F = 0.19 °C. That’s out of a total of 0.6454 °C of warming which they added to 1998 relative to 1934, between the 1999 and current versions of their data.
1999 version 2013 version 1934 1.46 1.2217 °C 1998 0.92 1.3271 °C -------- -------- 0.54 -0.1054 °CMost of the adjustments are unexplained. I tried to get an explanation of the adjustments from the CSRRT, but they didn’t know.
Paul Homewood wrote, “This only has relevance in the USA, where most stations moved from afternoon to morning recording as a matter of policy.”
Really? Didn’t they use Six’s registering thermometers for recording daily highs and lows? If so, the time of observation would not be very important, most days.
Bill Yarber says:
January 6, 2014 at 9:49 am
[…]
NASA/NOA “time of day” adjustment is simply a fudge factor to get the desired final result
[…]
Reminds me of the ‘daylight savings’ scheme. According to http://de.wikipedia.org/wiki/Wetterstation, in Germany the ‘part time’ weather stations do the readings at 0700, 1400 and 2100.
If they actually measure temperature at 0800, 1500 and 2200 in summer, I think that might lead to
a slight increase in measured summer temperatures.
Eric Simpson says:
January 6, 2014 at 10:12 am
“And the summary?”
Basic summary.
Many places refuse to turn over climate data,
BEST adjusted and cherry picked much of the data they used,
Coastal areas appear to be heavily effected by coastal winds that are likely very very poorly documented,
Non-coastal wind effected areas seem to have little to no warming,
“Free”/online unadjusted data appears to be mostly at or near satellite data start thus provides little extra info about the past,
Looking for help from anyone who has Europe based original data outside of the “taxpayer funded yet refuse to turn over data to the public/taxpayer groups”.
I love the “magic” areas which have no noticeable trend over 100 years. Makes one rather SUSPICIOUS of “instrument artifacts” (i.e., see http://www.surfacestations.org) as the source of the “GLOBAL warming” seen by these observing stations. That would lead to the strong conclusion that with a COMPLETE LACK OF QUALITY CONTROL the data may be “statistically” meaningless.
You know what, even if the Arctic and Antarctic were melting away to
nothingto much less, it wouldn’t prove anything, other than that we have had some (probably natural) warming and / or cyclical phenomena. But that’s not happening. This year we have record levels of Arctic ice growth, and record Antarctic sea ice. And it just doesn’t feel any hotter, any different, than it did decades ago. And we got record cold all over the place, with right now, after noon, Chicago is experiencing windchills of -41°F. And why was the world record hot temperature set way back in 1913? Certainly a century of runaway warming would have broken that record somewhere, but, alas, the 1913 record still stands! Something is fishy. A lot of people suggest the 1930s were hotter than today. That’s why this work on the “adjustments” made to the temperature record is so important.And another thing, when we look at the past 100+ years of temperature change, even when we have to try to peer through grossly mis-adjusted warmist data and a growing urban heat island effect, we see little discernible changes in the rate of early 20th century (low CO2) and later 20th century (higher CO2) change. It suggest NO signal from CO2. And we also know that the original IPPC contention that there was a causal relationship between CO2 and temperature was clearly rebutted in 1999, yet the ipcc fought this tooth and nail until 2003 when they finally conceded, and yet in 2005 Al Gore still deceptively put forward the discredited points about CO2 in his movie (yes, see what I’m talking about regarding Al Gore & CO2 in this key 3 1/2 minute video). Look, throughout history you cannot ferret out ANY effect of CO2. You can say that maybe there’s been an effect, or that
ourtheir theory suggests an effect, but data doesn’t show it. And the fact that we’ve had this 15 year temperature stall out, and that the warmist adjusted 20th century temperature record appears to have had only mild (NOT hockey stick style!) warming, and before that, going back hundreds of thousands of years and even hundreds of millions of years, there’s no evidence at all of CO2’s effect, all this suggests that the IPCC is plain wrong on CO2.RE Caption to Fig. 15:
Fig15. From the BEST FAQ web site.
I suggest it be modified to:
Fig15. From the BEST FAQ web site (with my suggested update.)
Mr. Burton: As the saying goes, SHIRELY YOU JEST!
“Really? Didn’t they use Six’s registering thermometers for recording daily highs and lows? If so, the time of observation would not be very important, most days.” Just because an old journal publishes an article on something which could give a better temperature record, DOES NOT MEAN THAT IT WAS USED from that time or anything of the like. This is ‘backwards fantasy” from a forwards perspective. Check out surface stations.org, and other resources. The gathering of PEAK and LOW temperatures prior to WWII around the world, was more of a matter of “by guess and by golly. THE INORDINATELY low temperature from the DEW line had to do with people feeling it was TOO COLD TO GO OUT and so they Guessed or exaggerated for the entertainment of the Russians.
Sorry, again, the older the measurement, the LESS likely to meet any modern “quality control” standard. That is the primary reason that 1 to 2 to 3 degree variations (degrees C) in averages are suspect if not meaningless.
If this sea-air vs. sheltered air difference in temperature trends is borne out, it is really a huge discovery. History will be curious: did it just jump right out, or did Frank have to follow some serendipitous path of intuition and trial and error before he happened onto it?
If it is borne out one of the biggest implications will be for model testing. It will have implications for the sequence of air/land vs ocean warming. CO2 driven models have the air warm first. Cloud modulated models have the oceans warm first.
But what does it all MEAN Basil? Personally, I can’t begin to fathom how there could be decadal persistence of inland-coastal temperature differences when the air circulates in days. How to get a persistent difference? Were the 1930’s a period of relative cloudlessness over the oceans and relative cloudiness over the land? Is that even a possible pattern? Or does cloudlessness over the land cause nighttime temperatures to fall by more than it causes daytime temperatures to rise?
That might be something to look into: do daytime vs nighttime temperatures suggest a possible role of coudiness in the difference between coastal and inland temperatures in the 1930s?
Bill Yarber says:
January 6, 2014 at 9:49 am
“Excellent start to uncovering the adjustments (i.e. lies). Historical data should NEVER be changed.”
Thank you so much, it was exactly my wish that this was some kind “start”, hopefully a snowball that could get the process started, get many people to collect even more data, make peoble contact their governments if the meteorological institutes refuses to deliver tax paid results to the public.
Frank Lansner says:
Greg, you ask if i have the original Austrian data?
Yes indeed !
They are hard to find –
====
Great. However, my question was not just curisosity. Let me be more specific:
could you please provide a link to the “ORI” data files from HISTALP?
Thanks.
Eric Simpson says:
January 6, 2014 at 10:12 am
And the summary?….
>>>>>>>>>>>>>>
English is not Frank Lansner’s native language.
Not only has Frank done the enormous amount of digging and organizing for this data, he is reporting it in a language he is not really comfortable with. (His English has improved quite a bit since the first I read an essay of his.)
I thank Frank for his great effort.
Alec Rawls says:
January 6, 2014 at 11:08 am
“If this sea-air vs. sheltered air difference in temperature trends is borne out, it is really a huge discovery. History will be curious: did it just jump right out…”
First my only aim was to find areas of similar temperature trend. This is very important if you want to easily pinpoint outliers and adjusted material. And if you want to stitch two datasets its gets very noisy if they have quite different kind of trends.
I have seen in my “RUTI CHINA” analysis some examples where HadCRU use OAA for early years and then OAS for later years for calculating some grids. The reduces heat in the past and promotes heat in recent years. Therefore I had to identify areas of similar trends, also to avoid the possibility of too-short datasets to be misleading. If you have area of similar trend, it cannot give big errors to stitch sets.
I wonder if this whole OAA and OAS thing is just a proxy for urban heat island?
It seems to me that coastal areas tend to be (in general) more likely to be urbanized than non-coastal areas. People just like to live on the coast. Also, people will probably be more likely to want to live in the yellow areas (from fig 4) than the blue areas, so again, maybe this signal is just an indirect measurement of land-use and urban heat island. Just a thought.
@ur momisugly Frank Lansner- I understand that in many places in the world, observation time has long been standardized, so that is probably correct for the most part. As I understand it, however, the place where TOBS adjustment is mostly made is the US, where we *don’t* have standardized time of observation.
@ur momisugly Steven Mosher it is commendable to want to achieve a result that can be checked so focus on publicly available data. What you say does raise the question though: Why does BEST get about the same answer using only publicly available data, as Jones does using non publicly available data, and why do *different people* who have jumped through the difficult hoops to get non publicly available data, *not* get Jones’ results?
It seems to me that the best fight to have, is a fight to free the non publicly available data, to make it publicly available. That way, we can see if using it in an analysis would alter the results, *and* that result would be publicly checkable.
Until then it appears that non public data either disagrees with BEST (Lansner) or agrees with BEST (CRU) depending on what you do with it. This strikes me as kind of interesting, don’t you agree?
” And if you want to stitch two datasets its gets very noisy if they have quite different kind of trends.”
I was quite curious as to why the “HISTALP” site contains data from a couple of sites such a Paris which are hardly “ALP” , much nearer the coast and a major metropolis. Not surprisingly the data have significant difference in form.
The motivation for including such records in HISTALP is not made clear.