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Temperature Adjustments Around The World

January 29, 2015

By Paul Homewood





As well as the well documented adjustments to past temperatures in Paraguay, it is worth remembering just how widespread this practice is.  



















None of these are isolated instances, and there are other similar adjustments at other stations in these countries. You might also note that these are all  long running and complete, or near complete, records.


It is often claimed that these adjustments are needed to “correct” errors in the historic record, or compensate for station moves. All of which makes the adjustment at Valentia Observatory even more nonsensical.




Valentia Observatory, situated in SW Ireland, is regarded as one of the highest quality meteorological stations in the world, located at the same site since 1892, well away from any urban or other non climatic biases. The Irish Met Office say this:-


Since the setting up of the Irish Meteorological Service, the work programme of the Observatory has greatly expanded and it has always been equipped with the most technologically advanced equipment and instrumentation. The Observatory is well known and very highly regarded by the scientific community. As well as fulfilling its national and international role within Met Éireann it is involved in many projects with other scientific bodies both in Ireland and abroad.


If we cannot get accurate temperature trends in Valentia, we cannot get them anywhere. Yet the GHCN algorithm decides that the actual temperatures measured there do not look right, and lops 0.4C off temperatures before 1967.

Worse still, the algorithm uses a bunch of hopelessly unreliable urban sites, as far away as Paris, to decide upon the “correct temperature”, as Ronan Connolly illustrated.





If you wanted to find a way to fraudulently alter the global temperature record upwards, you would be hard put to find a better way than this.


Note that this post can be found under the “Temperature Adjustments” tag, for future reference.




Raw data from GISS, up to 2011.


Adjusted data (GHCN V3)

  1. January 29, 2015 4:26 pm

    Thanks for posting this information.

    It really doesn’t matter how many new lies they tell now. Despite all their struggles, Big Brother is going down now!

    Our challenge today is to:

    1. Retain the benefits* of, and
    2. Eliminate the deception in

    The Great Social Experiment of 1945-2015

    Click to access Social_Experiment.pdf

    We must not get side-tracked trying to punish those who used grant funds to deceive the public for the past seventy years.

    *Benefits: Increased awareness of the interdependence of nations. Reduced nationalism, racism, sexism, xenophobia, etc.

  2. A C Osborn permalink
    January 29, 2015 5:00 pm

    Paul, as you say it is endemic to the GHCN & GISS data, plus we have had alterations to the UK data via the new versions.
    As Steve Goddard has shown each version of the data shows more perversion and then they have their monthly adjustments as well.
    But you can see how much resistance there is to this becoming public knowledge by the lack of reaction to Chris Booker’s piece.
    You would have thought every real Investigative Reporter would be searching for more such data, but it does not happen. The lid is being firmly clamped on this.

  3. January 29, 2015 5:44 pm

    Connolly’s map shows the fallacy of regional expectations. Valentia Obse is a crystal clear example. Another is BEST station 166900, Amundsen Scott at the South Pole. BEST rejected 26 months of record cold ‘outliers’. The nearest station is McMurdo, 1300 km away and 2700 meters lower on the coast.
    For many additional examples of algorithmically manufactured warming, see essay When Data Isnt in ebook Blowing Smoke.

    • A C Osborn permalink
      January 29, 2015 5:49 pm

      Rud, is that the one where we got Mosher on Climate Etc to admit that their Final temps are “what they think ut should be according to the model”?

      • January 29, 2015 8:20 pm

        Yes, it is. He had no other choice, because the problem is so glaringly obvious. That, and Menne stitching, are the two logical flaws I have been able to identify so far in homogenization algorithms.

      • AndyG55 permalink
        January 29, 2015 9:51 pm

        Hi AC, Do you have a specific link for that Mosher comment?

        Would be nice to see it in full . 🙂


      • A C Osborn permalink
        January 29, 2015 11:26 pm

        Here is the actual statement, I will try and find a link

        Steven Mosher | July 2, 2014 at 11:59 am |

        “However, after adjustments done by BEST Amundsen shows a rising trend of 0.1C/decade.

        Amundsen is a smoking gun as far as I’m concerned. Follow the satellite data and eschew the non-satellite instrument record before 1979.”

        BEST does no ADJUSTMENT to the data.

        All the data is used to create an ESTIMATE, a PREDICTION

        “At the end of the analysis process,
        % the “adjusted” data is created as an estimate of what the weather at
        % this location might have looked like after removing apparent biases.
        % This “adjusted” data will generally to be free from quality control
        % issues and be regionally homogeneous. Some users may find this
        % “adjusted” data that attempts to remove apparent biases more
        % suitable for their needs, while other users may prefer to work
        % with raw values.”

        With Amundsen if your interest is looking at the exact conditions recorded, USE THE RAW DATA.
        If your interest is creating the best PREDICTION for that site given ALL the data and the given model of climate, then use “adjusted” data.

        See the scare quotes?

        The approach is fundamentally different that adjusting series and then calculating an average of adjusted series.

        in stead we use all raw data. And then we we build a model to predict
        the temperature.

        At the local level this PREDICTION will deviate from the local raw values.
        it has to.

      • AndyG55 permalink
        January 30, 2015 4:15 am

        Wow, this is truly climate non-science at its BEST !!! roflmao !!

  4. January 29, 2015 8:59 pm

    Reblogged this on Power To The People and commented:
    Can’t See Any #Climate Change? No Problem Just Adjust World Temperatures & Abracadabra Now You See It

  5. Paul permalink
    January 30, 2015 8:54 am

    A fairly damming summary of the present state of modern Climate ‘Science’

    If moving gifs are to be used can we have identical scales, min and max, rather than those that shift?

  6. Bloke down the pub permalink
    January 30, 2015 11:47 am

    When trying to explain these adjustments to the man in the street, their usual response is ‘but what motive have they got to fiddle the results?’ It’s difficult getting some people out of their comfort zone, to believe that not everyone in a white lab coat is totally honest.

  7. Bill Illis permalink
    January 30, 2015 12:25 pm

    Check out Reyjavik Iceland temperature adjustments from the NCDC’s GHCN-M3.22.

    They have taken the fully quality controlled station trend showing +0.2C of warming since 1900, and made it +2.3C of warming.

    January 29, 2015 outline, the top left panel is the quality controlled raw data, the middle left is the NCDC’s adjusted and the bottom left is the adjustments applied to each year.

    On January 17, 2015, the adjusted data only showed +2.0C of warming.

    On February 21, 2014, it was only +1.4C in the adjusted. They don’t stop. They are continually adjusting the records every few weeks.

    • Phil permalink
      February 1, 2015 7:14 am

      Using the new HadISD database, I plotted the temps for Reykjavik. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000010049779498 .

      Here is the plot:

      • Phil permalink
        February 1, 2015 7:17 am

        That would be from 1973 to 2013.

  8. Bill Illis permalink
    January 30, 2015 12:47 pm

    Sorry, I meant “right” side of the graphics, not left.

  9. January 31, 2015 4:09 pm

    1/ A definitive study would be to count the number of stations wherein the temperature adjustments increase, decrease, or leave unchanged the slope of the temperature time series. If all the slopes increase, then that is evidence of a systematic bias in the data processing
    Then divide the set into two: rural and urban stations. Due to the UHI, one would expect the slopes at the urban stations to decrease. If they do not, then something is wrong.

    2/ These adjustments are a source of systematic error [bias] on the order of +/- 1C.
    It should be propagated and included in the final graph of the mean global temperature time series.
    If so, then why are the final errors quoted as being on the order of +/- 0.02C

    3/ The rationale for using a station in Paris to correct for a station in Ireland is that while the changes in absolute temperature are not correlated over large spatial distances, the changes in the temperature are correlated. This is another claim that has, to my knowledge, never been thoroughly investigated.

    • A C Osborn permalink
      January 31, 2015 5:58 pm

      I can assure you that it is total bullsh!t. Just compare the West of the UK with the East fo the UK, it is about 2 degrees C warmer on the west coast because the temperature is buffered by Atlantic and the South Westerly winds whereas Paris is much further in land.

      Take today, 5 degrees in Valentia Obse and 3 degrees in Paris.
      It can then easily reverse if Paris get warm air coming up from the South.
      To compare the 2 is nonsense.

      • January 31, 2015 9:39 pm

        Yes, post-1945 government science is mostly BS, carefully designed to hide the source of energy that destroyed Hiroshima and Nagasaki – NEUTRON REPULSION !

        Billions of federal funds have been spent to keep the public from knowing neutron repulsion is often the most important source of energy in atoms, planets, stars and galaxies heavier than 150 astronomical units (amu)

        Climategate was only one unintended consequence.

    • February 2, 2015 12:16 pm

      you forgot to mention the change in the vertical scale in most of those graphs.

      Currently, for most of the graphs it’s apples and oranges since the temperatures on the vertical axis aren’t equal.

      • February 2, 2015 5:09 pm

        Unfortunately that is how GISS present them.

        Nevertheless the difference in trends is obvious

  10. Phil permalink
    February 1, 2015 7:18 am

    Using the new HadISD database, I plotted the temps for Valentia Observatory for 1973 to 2013. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000004580205849.

    Here is the plot:

  11. toadboy65 permalink
    February 4, 2015 4:10 am

    I have an observation- I am a maritime officer, and one thing I know is that on ships,we take exhaustive weather observations, and have done so at least for the last century. We take these measurements using calibrated and certified instruments, and do so many times a day. Although this data will tell you nothing of trends in Kansas, it certainly could be used to show long-term global trends. The NWS has all this data. Has anyone brought out this data set to see how it reflects long term global temperature change?

  12. Austin permalink
    February 23, 2015 11:32 am

    These anecdotal examples are all very disturbing, but continual recourse to them opens up sceptics to the charge of cherry-picking.

    What I’d like to see – and I don’t know if anyone has done this – is a slightly more complete analysis over all weather stations, comparing raw and adjusted values. Something like this.

    For each year
    – take all weather stations with good records in that year
    – could refine by excluding any series shorter than 5 years, say, if we’re worried about outliers
    – compare raw and adjusted values of annual mean temperature
    – plot the distribution of the adjustments in that year
    and then stack all of those plots so you get a 3d surface where the x coordinate is year, the y is adjustment and the z is frequency.

    If no adjustments had been made ever, this would be a straight ridge of height 1 and thickness zero along the x axis. How far the observed plot deviates from that, and in what way, would show us what we are dealing with.

    Does such a plot exist? If not, does anyone have the data to hand to create one?

    It could then be broken down by region, latitude zone, urban/rural classification, etc., to categorize what’s been going on.

    Further, it could be repeated on older versions of adjusted data, to see how the picture has changed over time.

    • February 23, 2015 12:13 pm

      Of course, skeptics identify specific examples of data tampering. To call that “cherry picking” is disingenuous.

      CONCLUSION: The AGW debate ended and specific examples of data manipulation were identified. If world leaders admit and accept the Sun’s core is a pulsar they cannot predict or control – A Higher Power Than World Leaders – true world peace will again be possible


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