Skip navigation
Veuillez utiliser cette adresse pour citer ce document : http://repositorio.unb.br/handle/10482/36921
Fichier(s) constituant ce document :
Fichier Description TailleFormat 
ARTIGO_SeasonalEffectSpatial.pdf2,46 MBAdobe PDFVoir/Ouvrir
Titre: 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
Auteur(s): Salles, Leandro de Almeida
Satgé, Frédéric
Roig, Henrique Llacer
Almeida, Tati
Olivetti, Diogo
Ferreira, Welber
metadata.dc.identifier.orcid: https://orcid.org/0000-0002-6056-7055
Assunto:: Precipitação (Meteorologia)
Satélites artificiais
Cerrados
Date de publication: 2019
Editeur: MDPI
Référence bibliographique: 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.
metadata.dc.description.unidade: 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
Collection(s) :Artigos publicados em periódicos e afins

Affichage détaillé " class="statisticsLink btn btn-primary" href="/jspui/handle/10482/36921/statistics">



Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.