Sampling Theory Applied to Measurement and Analysis of Temperature for Climate Studies

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.