High-resolution precipitation reanalysis over France through offline data assimilation in a downscalled ensemble meteorological reconstruction

Réanalyse haute résolution des précipitations sur la France en utilisant l'assimilation de données offline dans des reconstructions ensemblistes métrologiques provenant d'une descente d'échelle

Devers, A. ; Vidal, J.P. ; Lauvernet, C. ; Graff, B.

Type de document
Poster
Langue
Anglais
Affiliation de l'auteur
IRSTEA LYON UR RIVERLY FRA ; IRSTEA LYON UR RIVERLY FRA ; IRSTEA LYON UR RIVERLY FRA ; CNR LYON FRA
Année
2018
Résumé / Abstract
This study considers an offline data assimilation method using the Ensemble Kalman Filter to build a precipitation reanalysis over France. The method is here applied for reconstructing the 2009-2012 period, using past observation density of 1871, 1900 and 1950. The methodology allows taking two main features of precipitation into account: (1) an anisotropic localization matrix based on the climatological background information, (2) a Gaussian transformation applied to daily precipitation. Results show a reduced error and a reduced uncertainty compared to background reconstructions, even with few observations, thus demonstrating the added value of data assimilation.
Congrès
EGU General Assembly 2018, 08/04/2018 - 13/04/2018, Vienna, AUT

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