Temporal and Spatial Assessment of Four Satellite Rainfall Estimates over French Guiana and North Brazil

• Published in: Remote sensing (Basel, Switzerland) Vol. 7; no. 12; pp. 16441 - 16459
• Main Authors: Ringard, Justine, Becker, Melanie, Seyler, Frederique, Linguet, Laurent
• Format: Journal Article
• Language: English
• Published: MDPI 01-12-2015; MDPI AG
• Series: Satellite Climate Data Records and Applications
• Subjects: CMORPH; Engineering Sciences; Environmental Sciences; Guiana Shield; PERSIANN; Physics; rainfall estimates; satellite observations; TRMM; satellite observations; rainfall estimates; TRMM; CMORPH; PERSIANN; Guiana Shield
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs71215831

Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis) V7 (Version 7) and RT (real time), CMORPH (Climate Prediction Center (CPC) MORPHing technique) and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network), for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error) and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio). Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and PERSIANN show the same performance.