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USHCN Estimated Data Shows Greater Warming Trend

July 8, 2014

By Paul Homewood 


Sunshine Hours has a post, which analyses the difference in trends between Estimated and Non-Estimated data on the USHCN Final dataset. He finds that the warming trend for the Estimated data  since 1895 is consistently greater than the Non Estimated. For instance, December:






You can see the graphs clearer at his blog, but the red line is the plot of Estimated data, and the blue is Non Estimated. Remember that the Non Estimated is adjusted and not raw data.

Of course, it may just be the case that all of the stations, where data has to be estimated, just happen to be in parts of the country where warming has been greatest.

And, of course, it is also possible that fairies live at the bottom of my garden.

  1. July 8, 2014 11:22 am

    It is a conclusion chasing data. They estimate a warming trend because they expect to find one. And that in itself is enough to invalidate their entire thesis.

    If the conclusion was justified, they would not need to create estimated data to validate it – the raw data would do that.

  2. July 8, 2014 11:38 am

    Reblogged this on the WeatherAction Blog.

  3. July 9, 2014 4:56 am

    This is the same faulty method that Steve Goddard uses. The population of estimated stations changes from year to year. So if those happen to be warmer places, average estimated will rise, but it’s nothing to do with estimation. I show that here. I plot the difference between the average climatology of estimated minus non-estimated. It is very similar. It’s the change of stations in the sample, not the arithmetic of estimation, that you are seeing.

  4. Green Sand permalink
    July 9, 2014 8:22 am

    Paul, comment of the day?

    ” JJ says:
    July 8, 2014 at 9:31 pm

    Richard Day says:

    Germany demolished Brazil 7-1 today in the World Cup.

    I’m sorry, but that is not correct.

    Your problem is, you are using the raw score. When the proper pairwise homogenization algorithm is applied, comparison to similar soccer games played within a 1500 km radius flags the score 7-1 as a soccer score discontinuity. To correct this obvious error, the anomalous values are replaced with regional average scores. After adjustment, Brazil won 3-2..”

  5. Brian H permalink
    July 11, 2014 7:11 am

    JJ is clearly Nick’s star pupil.

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