We’ve seen examples time and again of the cooling of the past via homogenization that goes on with GISS, HadCRUT, and other temperature data sets. By cooling the data from the past, the trend/slope of the temperature for the last 100 years increases.

This time, the realization comes from an unlikely source, Dr. Jeff Masters of Weather Underground via contributor Christopher C. Burt. An excerpt of the story is below:

Inconsistencies in NCDC Historical Temperature Analysis

Jeff Masters and I recently received an interesting email from Ken Towe who has been researching the NCDC historical temperature database and came across what appeared to be some startling inconsistencies. Namely that the average state temperature records used in the current trends analysis by the NCDC (National Climate Data Center) do not reflect the actual published records of such as they appeared in the Monthly Weather Reviews and Climatological Data Summaries of years past. Here is why.

An Example of the Inconsistency

Here is a typical example of what Ken uncovered. Below is a copy of the national weather data summary for February 1934. If we look at, say Arizona, for the month we see that the state average temperature for that month was 52.0°F.

The state-by-state climate summary for the U.S. in February 1934. It may be hard to read, but the average temperature for the state of Arizona is listed as 52.0°F From Monthly Weather Review.

However, if we look at the current NCDC temperature analysis (which runs from 1895-present) we see that for Arizona in February 1934 they have a state average of 48.9°F, not the 52.0°F that was originally published:

Here we see a screen capture of the current NCDC long-term temperature analysis for Arizona during Februaries. Note in the bar at the bottom that for 1934 they use a figure of 48.9°.

Ken looked at entire years of data from the 1920s and 1930s for numerous different states and found that this ‘cooling’ of the old data was fairly consistent across the board. In fact he produced some charts showing such. Here is an example for the entire year of 1934 for Arizona:

The chart above shows how many degrees cooler each monthly average temperature for the entire state of Arizona for each month in 1934 was compared to the current NCDC database (i.e. versus what the actual monthly temperatures were in the original Climatological Data Summaries published in 1934 by the USWB (U.S. Weather Bureau). Note, for instance, how February is 3.1°F cooler in the current database compared to the historical record. Table created by Ken Towe.

Read the entire story here: Inconsistencies in NCDC Historical Temperature Analysis

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The explanation given is that they changed from the ‘Traditional Climate Division Data Set’ (TCDD) to a new ‘Gridded Divisional Dataset’ (GrDD) that takes into account inconsistencies in the TCDD. “.

Yet as we have seen time and time again, with the exception of a -0.05°C cooling applied for UHI (which is woefully under-represented) all “adjustments, improvements, and fiddlings” to data applied by NCDC and other organizations always seem to result in an increased warming trend.

Is this purposeful mendacity, or just another example of confirmation bias at work? Either way, I don’t think private citizen observers of NOAA’s Cooperative Observer Program who gave their time and efforts every day for years really appreciate that their hard work is tossed into a climate data soup then seasoned to create a new reality that is different from the actual observations they made. In the case of Arizona and changing the CLimate Divisions, it would be the equivalent of changing state borders as saying less people lived in Arizona in 1934 because we changed the borders today. That wouldn’t fly, so why should this?

Sure there are all sorts of “justifications” for these things published by NCDC and others, but the bottom line is that they are not representative of true reality, but of a processed reality.

h/t to Dr. Ryan Maue.

UPDATE: Here’s a graph showing cumulative adjustments to the USHCN subset of the entire US COOP surface temperature network done by Zeke Hausfather and posted recently on Lucia’s Blackboard:

This is calculated by taking USHCN adjusted temperature data and subtracting USHCN raw temperature data on a yearly basis. The TOBS adjustment is the lion’s share.

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