Gosset Marielle, Alcoba Matias, Roca R., Cloche S., Urbani G. (2018). Evaluation of TAPEER daily estimates and other GPM-era products against dense gauge networks in West Africa, analysing ground reference uncertainty. Quarterly Journal of the Royal Meteorological Society, 144 (1), p. 255-269. ISSN 0035-9009.
Titre du document
Evaluation of TAPEER daily estimates and other GPM-era products against dense gauge networks in West Africa, analysing ground reference uncertainty
Gosset Marielle, Alcoba Matias, Roca R., Cloche S., Urbani G.
Source
Quarterly Journal of the Royal Meteorological Society, 2018,
144 (1), p. 255-269 ISSN 0035-9009
A series of multi-platform rainfall estimates is evaluated at the daily 1 degrees resolution over three dense rain-gauge networks in West Africa, in Niger, Burkina Faso and Benin, for the period 2012-2016. The quality of the ground reference, its dependence on the number of gauges and the consequences on the validation are discussed. The primary objective of this work is the evaluation of the newly released Tropical Analysis of Precipitation with an Estimation of Errors (TAPEER) daily one-degree rainfall accumulation from the Megha-Tropiques mission. Several other multi-platform products, GSMAP, CMORPH, PERSIANN, TMPA and IMERG, are also evaluated over the same area to put TAPEER performance into perspective. For each product only the version that uses solely satellite information (no gauge adjustment) is used. The analysis concentrates on the heart of the rainy season in West Africa, from June to September. TAPEER exhibits good skill over the region, with a high correlation and a good reproduction of the frequency distribution of the rain rates, especially in the Sahelian region - Niger and Burkina Faso - where the biases are close to zero. The bias is stronger (and negative) in Benin. This overall good performance is stable from year to year. The other products exhibit less bias in Benin and more in the Sahel. CMORPH stands out with relatively good correlations, GSMAP slightly less and PERSIANN has a very strong bias in the Sahel. IMERG, analysed over a shorter period, is also promising.
