Multiregional satellite precipitation products evaluation over complex terrain

An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are c...

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Bibliographic Details
Authors: Derin, Y., Anagnostou, E., Berne, A., Borga, M., Boudevillain, Brice, Buytaert, W., Chang, Che-Hao, Delrieu, Guy, Hong, Yang, Chia Hsu, Yung, Lavado-Casimiro, W., Manz, Bastian, Moges, Semu, Nikolopoulos, Efthymios I., Sahlu, Dejene, Salerno, Franco, Rodríguez-Sánchez, Juan-Pablo, Vergara, Humberto J., Yilmaz, Koray K..
Format: article
Status:Versión aceptada para publicación
Publication Date:2016
Country:Perú
Institution:Servicio Nacional de Meteorología e Hidrología del Perú
Repository:SENAMHI-Institucional
Language:English
OAI Identifier:oai:repositorio.senamhi.gob.pe:20.500.12542/298
Online Access:https://hdl.handle.net/20.500.12542/298
https://doi.org/10.1175/JHM-D-15-0197.1
Access Level:Open access
Keyword:Satélite
Precipitación
Lluvia
Climatología
Hidrometeorología
https://purl.org/pe-repo/ocde/ford#1.05.10
precipitacion - Clima y Eventos Naturales
Description
Summary:An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network.

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