Please use this identifier to cite or link to this item:
Title: Evaluation of the WRF ability to represent the precipitation in the amazon using a different scales
Other Titles: Avaliação da habilidade do modelo WRF em representar a precipitação na amazônia usando diferentes escalas
Authors: Sousa, Jeanne Moreira de
Cândido, Luiz Antônio
Silva, Júlio Tóta da
Andreoli, Rita Valéria
Kayano, Mary Toshie
Manzi, Antônio Ocimar
Souza, Rodrigo Augusto Ferreira de
Souza, Everaldo Barreiros de
Vieira, Samuel de Oliveira
Issue Date: 2019
metadata.dc.publisher.journal: Revista Brasileira de Meteorologia
metadata.dc.relation.ispartof: Volume 34, Número 2, Pags. 255-273
Abstract: Precipitation over the northern Amazon during the austral summer and autumn seasons of the 1988-1999 was simulated using the Regional Weather Research and Forecasting (WRF) model, with downscaling approach with nested domains of 45 and 15 km. The boundary and initial conditions were obtained from the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP). The model skill was tested using different rea-nalyzed precipitation datasets that represent different space scales. The bias of the model shows seasonal and spatial dependences, with positive bias in southwestern Brazilian Amazon during summer and in northwestern South America during autumn. The downscaling was needed to reproduce the surface influences on the regional and local systems that affect the rainfall distribution in the region. The WRF model, in general, reproduces the main observed precipitation patterns, without the dry bias, typical of general circulation models (GCM). The results indicate that the dynamic downscaling technique improves the WRF model performance for the seasonal climate forecast in the Amazon region. © 2019, Sociedade Brasileira de Meteorologia. All rights reserved.
metadata.dc.identifier.doi: 10.1590/0102-77863340029
Appears in Collections:Artigos

Files in This Item:
File Description SizeFormat 
artigo-inpa.pdf7,87 MBAdobe PDFThumbnail

This item is licensed under a Creative Commons License Creative Commons