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Intercomparison of homogenization techniques for precipitation data continued: Comparison of two recent Bayesian change point models.

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Beaulieu, Claudie; Seidou, Ousmane; Ouarda, Taha B. M. J.; Zhang, Xuebin (2009). Intercomparison of homogenization techniques for precipitation data continued: Comparison of two recent Bayesian change point models. Water Resources Research , vol. 45 , nº 8. W08410. DOI: 10.1029/2008WR007501.

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Résumé

In this paper, two new Bayesian change point techniques are described and compared to eight other techniques presented in previous work to detect inhomogeneities in climatic series. An inhomogeneity can be defined as a change point (a time point in a series such that the observations have a different distribution before and after this time) in the data series induced from changes in measurement conditions at a given station. It is important to be able to detect and correct an inhomogeneity, as it can interfere with the real climate change signal. The first technique is a Bayesian method of multiple change point detection in a multiple linear regression. The second one allows the detection of a single change point in a multiple linear regression. These two techniques have never been used for homogenization purposes. The ability of the two techniques to discriminate homogeneous and inhomogeneous series was evaluated using simulated data series. Various sets of synthetic series (homogeneous, with a single shift, and with multiple shifts) representing the typical total annual precipitation observed in the southern and central parts of the province of Quebec, Canada, and nearby areas were generated for the purpose of this study. The two techniques gave small false detection rates on the homogeneous series. Furthermore, the two techniques proved to be efficient for the detection of a single shift in a series. For the series with multiple shifts, the Bayesian method of multiple change point detection performed better. An application to a real data set is also provided and validated with the available metadata.

Type de document: Article
Mots-clés libres: homogenization; Bayesian multiple linear regression; multiple shifts; precipitation series; change point
Centre: Centre Eau Terre Environnement
Date de dépôt: 29 nov. 2019 14:50
Dernière modification: 29 nov. 2019 14:50
URI: http://espace.inrs.ca/id/eprint/9503

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