Change-Point Detection in Meteorological Measurement

Abstract

Statistical methods of change-point detection can be useful for discovering inhomogeneities in precipitation, air pressure, or temperature time series caused by a change in the measurement process such as a relocation of a gauge. The method is based on a second correlated series that can be relied on to be correct, following the approach suggested by Potter. A summary of the latest methods is given, and the necessary tests and their critical values are provided. An application to air pressure series measured at three Swiss meteorological stations is presented.