The daily accumulated precipitation from two widely used satellite products, the Africa Rainfall Climatology version 2 (ARC2) and TRMM-Multi Precipitation Analysis (TMPA) 3B42 version 7, are exploited to extract the spatial variability and temporal evolution of precipitation over East Africa (EA, - 5°S-20°N, 28°E-52°E) at 0.25° spatial resolution during the last decades. Time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml) precipitation indices (RX1day, RX5day, CDD, CWD, SDII, PRCPTOT, R10, R20, etc.) are computed starting from the daily precipitation data sets at each 0.25° grid cell. Such time series are analysed to identify spatial patterns of rainfall variability and the inter-annual variation of precipitation, identifying single years characterized by extreme events (drought and flood) and extracting rainfall temporal variation by the trend analysis. Preliminary results concerning the EA rainfall variability and the connections with sea surface temperature (SST) and soil moisture are shown, focusing on the short-rain (October-November-December, OND) season.
Characterization of the precipitation from satellite over East Africa during last decades
E Cattani;C Wenhaji Ndomeni;V Levizzani
2015
Abstract
The daily accumulated precipitation from two widely used satellite products, the Africa Rainfall Climatology version 2 (ARC2) and TRMM-Multi Precipitation Analysis (TMPA) 3B42 version 7, are exploited to extract the spatial variability and temporal evolution of precipitation over East Africa (EA, - 5°S-20°N, 28°E-52°E) at 0.25° spatial resolution during the last decades. Time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml) precipitation indices (RX1day, RX5day, CDD, CWD, SDII, PRCPTOT, R10, R20, etc.) are computed starting from the daily precipitation data sets at each 0.25° grid cell. Such time series are analysed to identify spatial patterns of rainfall variability and the inter-annual variation of precipitation, identifying single years characterized by extreme events (drought and flood) and extracting rainfall temporal variation by the trend analysis. Preliminary results concerning the EA rainfall variability and the connections with sea surface temperature (SST) and soil moisture are shown, focusing on the short-rain (October-November-December, OND) season.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.