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Detection and correction of artificial shifts in climate series
Authors:Henri Caussinus   Olivier Mestre
Affiliation:1UniversitéPaul Sabatier, Toulouse, France;2Ecole Nationale de la Météorologie, Toulouse, France
Abstract:Summary.  Many long instrumental climate records are available and might provide useful information in climate research. These series are usually affected by artificial shifts, due to changes in the conditions of measurement and various kinds of spurious data. A comparison with surrounding weather-stations by means of a suitable two-factor model allows us to check the reliability of the series. An adapted penalized log-likelihood procedure is used to detect an unknown number of breaks and outliers. An example concerning temperature series from France confirms that a systematic comparison of the series together is valuable and allows us to correct the data even when no reliable series can be taken as a reference.
Keywords:Changepoints    Climate series    Linear model    Model choice    Outliers    Penalized likelihood
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