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Grid box-level evaluation of IMERG over Brazil at various space and time scales

  • Rainfall data from the Global Precipitation Measurement (GPM) mission provide a new source of information with high spatiotemporal resolution that overcomes the limitations of ground-based rainfall information worldwide. This study evaluates the performance of the Integrated multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite productRainfall data from the Global Precipitation Measurement (GPM) mission provide a new source of information with high spatiotemporal resolution that overcomes the limitations of ground-based rainfall information worldwide. This study evaluates the performance of the Integrated multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the North-east region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studiedshow moreshow less

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Author details:André N. GadêlhaORCiD, Victor Hugo R. Coelho, Alexandre C. Xavier, Luís Romero BarbosaORCiDGND, Davi C. D. Melo, Yunqing XuanORCiD, George J. Huffman, Walt A. Petersen, Cristiano das Neves AlmeidaORCiD
DOI:https://doi.org/10.1016/j.atmosres.2018.12.001
ISSN:0169-8095
ISSN:1873-2895
Title of parent work (English):Atmospheric Research
Publisher:Elsevier
Place of publishing:New York
Publication type:Article
Language:English
Date of first publication:2018/12/12
Publication year:2018
Release date:2021/03/12
Tag:Final run; Global precipitation measurement; Gridded rainfall; Performance
Volume:218
Number of pages:14
First page:231
Last Page:244
Funding institution:FINEP (Brazilian Innovation Agency)Ciencia Tecnologia e Inovacao (FINEP) [557/2013]; Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)CAPES [001]; Brazilian National Council for Scientific and Technological Development (CNPq)National Council for Scientific and Technological Development (CNPq); Paraiba Research Foundation (FAPESQ-PB); Sao Paulo Research Foundation (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2016/23546-7]; Precipitation Measurement Missions and Global Precipitation Measurement (GPM) mission projects
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 50 Naturwissenschaften / 500 Naturwissenschaften und Mathematik
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
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