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East Africa Rainfall Trends and Variability 1983-2015 Using Three Long-Term Satellite Products

Academic Article
Publication Date:
2018
abstract:
Daily time series from the Climate Prediction Center (CPC) Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Tropical Applications of Meteorology using SATellite (TAMSAT) African Rainfall Climatology And Time series version 2 (TARCAT) high-resolution long-term satellite rainfall products are exploited to study the spatial and temporal variability of East Africa (EA, 5S-20N, 28-52E) rainfall between 1983 and 2015. Time series of selected rainfall indices from the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices are computed at yearly and seasonal scales. Rainfall climatology and spatial patterns of variability are extracted via the analysis of the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitating days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of very heavy precipitating days (R20). Our results show that the spatial patterns of such trends depend on the selected rainfall product, as much as on the geographic areas characterized by statistically significant trends for a specific rainfall index. Nevertheless, indications of rainfall trends were extracted especially at the seasonal scale. Increasing trends were identified for the October-November-December PRCPTOT, R1, and SDII indices over eastern EA, with the exception of Kenya. In March-April-May, rainfall is decreasing over a large part of EA, as demonstrated by negative trends of PRCPTOT, R1, CWD, and R20, even if a complete convergence of all satellite products is not achieved.
Iris type:
01.01 Articolo in rivista
Keywords:
satellite; precipitation; droughts; East Africa
List of contributors:
Cattani, Elsa; Levizzani, Vincenzo
Authors of the University:
CATTANI ELSA
LEVIZZANI VINCENZO
Handle:
https://iris.cnr.it/handle/20.500.14243/343551
Published in:
REMOTE SENSING (BASEL)
Journal
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URL

http://www.mdpi.com/2072-4292/10/6/931
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