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A close review of NOAA’s historic temperature data for New York shows that the agency appears to have been adjusting its records to cool past records or warm recent ones, without any explanation.
The author took a look at NOAA’s graph this year showing New York’s average January temperatures going back to 1890, and noticed that, according to that graph, 1943 was 0.9 degrees Fahrenheit warmer than 2014. Yet, a close look at the actual data from 1943 strongly suggested that 1943 was actually 2.7F warmer, not 0.9F. Somehow, NOAA had adjusted the numbers, either in 1943 or in 2014, to make the present warmer or the past colder. Further analysis, removing the one station that appears to have experienced the most heat island influence, thus distorting its long term record, suggested the adjustments might actually be worse.
These results, while certainly not covering all weather stations and years, are still consistent with every other close look at NOAA’s adjustments. Those adjustments always cool the past and warm the present, so as to provide confirmation of the theory of global warming. More important, there is never any explanation for those adjustments.
Of the seven sites, six have remained at the same locations, within a few yards. The station at Auburn has moved by a couple of miles, but is still in similar terrain.
There is no reason then why any major adjustments should have been required at any site.
Apologists for temperature tampering usually say it is all due to TOBS (Time of Observation). Yet the station at Ithaca, based at Cornell University, has used morning readings throughout. With a temperature difference of 2.9C, this is typical of the other sites, suggesting that any bias from TOBS is minor.
Either there is outright fraud going on here in the climate divisions at NOAA, or they are entirely blind to their own confirmation bias. Either way, this data once again illustrates why there is great distrust in their results. Global warming might be happening, and human activity might be causing it, but these strange adjustments in the data leave many in doubt.