Statistical reanalysis of precipitation fields based on ground network data and weather patterns: Application over French mountains

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• 作者：Fré ; dé ; ric Gottardi^a ; ^{frederic.gottardi@edf.fr} ; Charles Obled^b ; Joë ; l Gailhard^a ; Emmanuel Paquet^a
• 关键词：Precipitation ; Weather patterns ; Orographical effect ; Mountainous areas ; Guess field ; Spatialisation
• 刊名：Journal of Hydrology
• 出版年：2012
• 期刊代码：68_00221694
• 类别：abs
• 出版时间：11 April, 2012
• 卷：432-433
• 期：Complete
• 页码：154-167
• 文件大小：4259 K

摘要

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Summary

The estimation of daily precipitation and snow water equivalent in mountainous watersheds is essential for water resources management. In upper catchments, it still remains subject to considerable uncertainties. Based on statistical methods, this work aims at developing tools for robust interpolations based on ground networks, in order to provide a reliable estimate of daily precipitation at any point in mountainous areas. Since the orographic effect is dominant in the explanation of precipitations in mountains, a linear relationship is considered for each pixel to connect precipitation to elevation. However, it is recognized that the relationship between precipitation and elevation is complex and depends on the time scale (day, month, yearldots) and even more on the exposure to the atmospheric flows. This is why a classification into weather pattern is used, to evaluate the atmospheric flow of the day, and better characterize the orographic effect induced by this circulation.

This method named SPAZM is applied over the main French mountainous areas, where a very large database has been collected. Results are presented on a 1 脳 1 km² grid and cross validation allows evaluation of the model for the Alps, the Pyrenees, and the Massif Central. The results are then compared to those obtained by other methods of the literature. The comparison concludes on the good results of the SPAZM method compared to others, and underlines the limitation of the cross validation for the evaluation of the method over non-gauged areas.