Evaluation of Rain Estimates from Several Ground-Based Radar Networks and Satellite Products for Two Cases Observed over France in 2022

Author:

Causse Antoine12,Planche Céline13ORCID,Buisson Emmanuel2,Baray Jean-Luc1

Affiliation:

1. Université Clermont Auvergne, Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Physique, UMR 6105, F63000 Clermont-Ferrand, France

2. Weather-Measures, F63000 Clermont-Ferrand, France

3. Institut Universitaire de France (IUF)

Abstract

The recent development of satellite products for observing precipitation based on different technologies (microwaves, infrared, etc.) allows for near-real-time meteorological studies. The purpose of this article is to evaluate 11 satellite products (GHE, PDIR, IMERG-Early v6, IMERG-Late v6, CMORPH v0.x, CMORPH-RT v0.x, GSMaP-NRT v7, GSMaP-NRT-GC v7, GSMaP-NOW v7, GSMaP-NOW-GC v7, and DATABOURG) currently available and compare them to 2 ground-based radar networks (PANTHERE and OPERA) and the French rain-gauge network RADOME. Two case studies of intense precipitation over France (22 to 25 April 2022 and 24 to 29 June 2022) were selected. The radar estimations are closer to the RADOME observations than the satellite-based estimations, which tend to globally underestimate the precipitation amounts over the areas of interest while OPERA tends to strongly overestimate precipitation amounts during the June case study. The PANTHERE radar product and the carrier-to-noise product DATABOURG shows promising results. Near-real-time satellite products tend to have closer precipitation amounts to the reference dataset than satellite products with a shorter latency. The use of these datasets for nowcasting developments is plausible but further analyses must be conducted beforehand.

Funder

French Research Agency

Weather-Measures

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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