Daily Rainfall Detection and Estimation over Land Using Microwave Surface Emissivities

Author:

Birman Camille1,Karbou Fatima1,Mahfouf Jean-François2

Affiliation:

1. CNRM/GAME, UMR 3589, CNRS/Météo-France, Saint Martin d’Hères, France

2. CNRM/GAME, UMR 3589, CNRS/Météo-France, Toulouse, France

Abstract

AbstractSurface emissivities computed at 89 GHz from AMSU-A, AMSU-B, and SSMI/S instruments are used to detect rain events and to estimate a daily precipitation rate over land surfaces. This new retrieval algorithm, called the emissivity rainfall retrieval (EMIRR) algorithm, is evaluated over France and compared with several other precipitation products. The precipitation detection is performed using temporal changes in daily surface emissivities. A statistical fit, derived from a rainfall analysis product using rain gauge and radar data, is devised to estimate a daily precipitation rate from surface emissivities. Rain retrievals are evaluated over a 1-yr period in 2010 against other precipitation products, including rain gauge measurements. The EMIRR algorithm allows a reasonable detection of rainy events from daily surface emissivities. The number of rainy days and the daily rainfall rates compare well to estimates from other precipitation products. However, the algorithm tends to overestimate low precipitation amounts and to underestimate higher ones, with reduced performances in the presence of snow. Despite such limitations, this new method is very promising and provides a demonstration of the potential use of the 89-GHz surface emissivities to infer relevant information (occurrence and amounts) related to daily precipitation over land surfaces.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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