Skip navigation
Use este identificador para citar ou linkar para este item: http://repositorio.unb.br/handle/10482/36921
Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
ARTIGO_SeasonalEffectSpatial.pdf2,46 MBAdobe PDFVisualizar/Abrir
Título: Seasonal effect on spatial and temporal consistency of the new GPM-based IMERG-v5 and GSMaP-v7 satellite precipitation estimates in Brazil’s Central Plateau Region
Autor(es): Salles, Leandro de Almeida
Satgé, Frédéric
Roig, Henrique Llacer
Almeida, Tati
Olivetti, Diogo
Ferreira, Welber
ORCID: https://orcid.org/0000-0002-6056-7055
Assunto: Precipitação (Meteorologia)
Satélites artificiais
Cerrados
Data de publicação: 2019
Editora: MDPI
Referência: SALLES, Leandro et al. Seasonal effect on spatial and temporal consistency of the new GPM-based IMERG-v5 and GSMaP-v7 satellite precipitation estimates in Brazil’s Central Plateau Region. Water, v. 11, n. 4, 668, 2019. DOI: https://doi.org/10.3390/w11040668. Disponível em: https://www.mdpi.com/2073-4441/11/4/668. Acesso em: 18 fev. 2020.
Abstract: This study assesses the performance of the new Global Precipitation Measurement (GPM)-based satellite precipitation estimates (SPEs) datasets in the Brazilian Central Plateau and compares it with the previous Tropical Rainfall Measurement Mission (TRMM)-era datasets. To do so, the Integrated Multi-satellitE Retrievals for GPM (IMERG)-v5 and the Global Satellite Mapping of Precipitation (GSMaP)-v7 were evaluated at their original 0.1 spatial resolution and for a 0.25 grid for comparison with TRMM Multi-satellite Precipitation Analysis (TMPA). The assessment was made on an annual, monthly, and daily basis for both wet and dry seasons. Overall, IMERG presents the best annual and monthly results. In both time steps, IMERG’s precipitation estimations present bias with lower magnitudes and smaller root-mean-square error. However, GSMaP performs slightly better for the daily time step based on categorical and quantitative statistical analysis. Both IMERG and GSMaP estimates are seasonally influenced, with the highest difficulty in estimating precipitation occurring during the dry season. Additionally, the study indicates that GPM-based SPEs products are capable of continuing TRMM-based precipitation monitoring with similar or even better accuracy than obtained previously with the widely used TMPA product.
Unidade Acadêmica: Instituto de Geociências (IG)
Licença: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
DOI: https://doi.org/10.3390/w11040668
Aparece nas coleções:Artigos publicados em periódicos e afins

Mostrar registro completo do item Visualizar estatísticas



Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.