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L'article du mois (février 2013)

Spatial coherence and potential predictability assessment of intraseasonal statistics of wet and dry spells over Equatorial Eastern Africa.

by  Gitau W., Ogallo L.J., Camberlin P., Okoola R., International Journal of Climatology, DOI: 10.1002/joc.3620
 

The aim of this study was to derive components of the intraseasonal rainfall variations from the daily rainfall in the Equatorial Eastern Africa region and assess their spatial coherence, a pointer to their potential predictability. Daily rainfall observations from 36 stations distributed over Equatorial Eastern Africa and extending from 1962 to 2000 were used. The March to May and October to December periods commonly referred to as the long and short rainfall seasons respectively were considered.

Seasonal and intraseasonal statistics at the local (station) level were first defined. The stations were also grouped into near-homogeneous (sub-regional) zones based on daily rainfall. Similarly, seasonal and intraseasonal statistics were then derived at sub-regional level using three different approaches. Inter-station correlation coefficients of the intraseasonal statistics at local levels were finally computed and plotted as box-plots.

For the two rainfall seasons, the two statistics showing the highest spatial coherence were the seasonal rainfall totals and the number of the wet days at sub-regional level. The local variance explained for these two variables, as an average over all the sub-regions, was more than 40%. At the bottom of the hierarchy were the mean rainfall intensity and frequency of dry spells of 5 days or more which showed the least coherence, with the local variance explained being less than 10% in each season. For each of the intraseasonal components of daily rainfall considered, the short rainfall season statistics were more coherent compared to the long rainfall season. Lag-correlations with key indices depicting sea-surface temperatures in the Pacific and Indian Oceans showed that the hierarchy between the rainfall statistics in the strength of the teleconnections reflected that of spatial coherence.Copyright © 2012 Royal Meteorological Society

Présentation rapide

Le Centre de Recherches de Climatologie (CRC) est une équipe de recherche de l'UMR6282 Biogéosciences (CNRS / Université de Bourgogne). Le CRC travaille sur la détection, l'attribution et la prévision du signal climatique et de ses impacts dans l'actuel et le futur. Ses activités sont centrées autour de la régionalisation du climat observé et simulé.

Le CRC est structuré en deux axes thématiques qui mettent en œuvre des méthodes permettant de passer de l'information large échelle (objet des travaux de l'équipe « Dynamique du Climat ») à une information d'échelle plus fine permettant d'évaluer les impacts (équipe « Impacts Climatiques »). Cette méthodologie relève de la statistique (méthodes statistico-dynamiques sur les sorties de modèles; statistiques spatiales;  désagrégation), de l'analyse spatiale (SIG opérateurs d'analyse spatiale vecteur et raster; interpolation spatiale mécaniste ou statistique), ou de la modélisation numérique du climat (modèles régionaux MM5 et WRF, modèle global Arpege-Climat).

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