Altering the weather data 17

JN reports another study confirming the finding that alterations to Australian raw weather data have increased the official trend by over 30%.

A recent submission to the arXiv archive suggests that altering the data to “inflate and dramatize weather conditions” may have a long tradition.

The Weather and its Role in Captain Robert F. Scott and his Companions’ Deaths by Krzysztof Sienicki

Abstract: A long debate has ensued about the relationship of weather conditions and Antarctic exploration. In no place on Earth is exploration, human existence, and scientific research so weather dependent. By using an artificial neural network simulation, historical (Heroic Age) and modern weather data from manned and automated stations, placed at different locations of the Ross Ice Shelf, and the Ross Island, I have examined minimum near surface air temperatures. All modern meteorological data, as well as historical data of Cherry-Garrard, high correlations between temperatures at different locations, and artificial neural network retrodiction of modern and historical temperature data, point out the oddity of Captain Scott’s temperature recordings from February 27 – March 19, 1912. I was able to show that in this period the actual minimum near surface air temperature was on the average about 13F(7C) above that reported by Captain Scott and his party. On the basis of the mentioned evidence I concluded that the real minimum near surface air temperature data was altered by Lt. Bowers and Captain Scott to inflate and dramatize the weather conditions.

And check out CA’s magnificent series on Phil Jones and the China Network.

  • Alex Harvey
  • Sherro1

    The main conclusions of the Sienicki paper seem plausible, if regrettable. However, there is possibly devil in the detail, starting with their figure captioned “Figure 3. The minimum daily near surface temperature averaged
    (the arithmetic mean) from the 1985-2009 McMurdo,
    Schwerdtfeger and 1993-2009 Elaine weather stations”.

    The detail that bothers me is the pattern match between the stations on a daily basis. For example, 25-26-27 Feb shows a low-high-low pattern of Tmin at 3 widely separated stations averaged over a couple of decades. The more you look, the more you see short sequences in lockstep. It is not plausible to postulate that 26 Feb was a hotter day than usual in more of these 20 years, at each of 3 stations.

    There seems to be an old friend at work, being the adjustment of AWS data for reasons unstated here. I can think of no other explanation apart from very long odds of probability, which you mathematical types could probably express numerically.

    However, this is a side issue to the main thesis. It’s just getting to be discouraging that the closer one looks at historical temperature data, the more unexplained oddities there are. Climate data do not have the same “feel” or “texture” as the data I was used to.

    My down mood might spin off from a few days of digging into the Chinese data of the Jones 1980 Nature letter. Different versions of the short data base (about 85 stations) have many errors, even of assignment of WMO numbers to places.

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