Évaluation des données TAMSAT d'estimation des précipitations dans la partie septentrionale du Cameroun

Due to the lack of adequate ground rainfall data for adaptation to climate variability, satellite imagery has been used for some decades in highlighting the rainfall-generating clouds. Among the most common products of this type are TAMSAT data (Tropical Applications in Meteorology using SATellite d...

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Bibliographic Details
Main Authors: Collins Étienne Kana, Marlyse Nankap Djangue
Format: Article
Language:English
Published: Physio-Géo
Series:Physio-Géo
Subjects:
Online Access:https://journals.openedition.org/physio-geo/15221
Description
Summary:Due to the lack of adequate ground rainfall data for adaptation to climate variability, satellite imagery has been used for some decades in highlighting the rainfall-generating clouds. Among the most common products of this type are TAMSAT data (Tropical Applications in Meteorology using SATellite data) for the precipitation estimates by a thresholding of cold-top clouds in the thermal infrared channel. Doubts persist, however, about the ability of these data to faithfully reproduce rainfall events in the sudano-sahelian zone particularly exposed to rainfall hazards. It therefore becomes necessary to evaluate them using the available ground observations. The objective of this contribution is therefore to validate the TAMSAT estimates in the northern Cameroon using the 24 ground stations for which continuous recorded data on precipitation are available between 2001 and 2011. Data processing includes the production of monthly and annual averages and various techniques of spatial analysis (spatial interpolation of point data and arithmetic operations on raster files).The results indicate that TAMSAT satellite products can partly fill in the deficiency of ground data, due to their ability to reproduce the main characteristics (monthly, interannual and spatial) of rainfall in the northern Cameroon. But the calibration of TAMSAT generally leads to biases: dry in the Sudanian zone and humid in the Sahelian zone. These biases can cause differences of 25 % from the total amount of rainfall.
ISSN:1958-573X