Performance of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Model in the Northeast Region of Brazil

Study is presented on the potential for using the tools contained in the Google Earth Engine (GEE) geospatial data processing and analysis platform in climatological studies in the Northeast Region of Brazil (NEB), in particular the validation of estimates of total annual rainfall obtained by the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) model in seven homogeneous regions of the NEB. This data is made up of various sources of meteorological information, including information from satellites, numerical models and observations at weather stations in operational and research centers across the globe. The performance of the CHIRPS model was assessed using climatological data obtained from the National Meteorological Institute's (INMET) meteorological database, metrics and statistical tests. The results showed that the CHIRPS model has potential for use in six of the seven regions studied, with low errors and strong statistical correlation, and limitations in one of these regions. The conclusion is that this technological tool, which has a low operating cost and is free of charge, can be used to assist in climatological studies, planning and the development of strategies for mitigation, adaptation and coexistence with the dry periods observed in the sub-regions of the NEB, especially in regions that are in a situation of socio-economic vulnerability, as is the case in the semi-arid region of the NEB.

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Publication Details

Journal
Revista Brasileira de Geografia Física
Published
2024-10-07
DOI
https://doi.org/10.26848/rbgf.v17.6.p4396-4408
Citations
3
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
1.13
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article

Performance of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Model in the Northeast Region of Brazil

Madson Tavares Silva, Emerson Mariano da Silva, João Hugo Baracuy da Cunha Campos, Vicente de Paulo Rodrigues da Silva et al.
3 citations
Revista Brasileira de Geografia Física
Precipitation Measurement and Analysis
1.13
article

Performance of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Model in the Northeast Region of Brazil

Madson Tavares Silva, Emerson Mariano da Silva, João Hugo Baracuy da Cunha Campos, Vicente de Paulo Rodrigues da Silva, Gabio Stalin Soares
article en
3 citations

Abstract

Study is presented on the potential for using the tools contained in the Google Earth Engine (GEE) geospatial data processing and analysis platform in climatological studies in the Northeast Region of Brazil (NEB), in particular the validation of estimates of total annual rainfall obtained by the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) model in seven homogeneous regions of the NEB. This data is made up of various sources of meteorological information, including information from satellites, numerical models and observations at weather stations in operational and research centers across the globe. The performance of the CHIRPS model was assessed using climatological data obtained from the National Meteorological Institute's (INMET) meteorological database, metrics and statistical tests. The results showed that the CHIRPS model has potential for use in six of the seven regions studied, with low errors and strong statistical correlation, and limitations in one of these regions. The conclusion is that this technological tool, which has a low operating cost and is free of charge, can be used to assist in climatological studies, planning and the development of strategies for mitigation, adaptation and coexistence with the dry periods observed in the sub-regions of the NEB, especially in regions that are in a situation of socio-economic vulnerability, as is the case in the semi-arid region of the NEB.

Revista Brasileira de Geografia FísicaVol. 17(6)
Universidade Estadual do Ceará (BR), Universidade Estadual da Paraíba (BR), Universidade Federal de Campina Grande (BR)
Climate action
Openalex Percentile: Top 24%
Precipitation Measurement and Analysis
1.13
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