Abstract

Of all the errors discussed in climatology literature, aliasing errors caused by undersampling of unsmoothed or improperly smoothed temperature data seem to be completely overlooked. This is a serious oversight in view of long-term trends of 1 K or less. Adequate sampling of properly smoothed data is demonstrated with a Hamming digital filter. It is also demonstrated that hourly temperatures daily averages, and annual averages free of aliasing errors can be obtained by use of a microprocessor added to standard weather sensors and recorders.

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