Avaliação de Indicadores Atmosféricos Utilizando o Modelo Numérico WRF em Eventos de Chuva na Cidade do Rio de Janeiro

Fabricio Polifke da Silva, Maria Gertrudes Alvarez Justi da Silva, Wallace Figueiredo Menezes, Vinícius Albuquerque de Almeida


The improvement in the forecast of extreme rainfall events contributes significantly the effectiveness of environmental monitoring performed routinely by operational centers. Therefore, in this study it was aimed to evaluate the performance of atmospheric indicators in rain events that occurred in the city of Rio de Janeiro, between 1997-2012, in order to identify which of them have higher reliability in identifying the favorable weather characteristics to the occurrence of severe rainfall. Using outputs from WRF model, thresholds were established for each of the atmospheric indicators analyzed in this paper, as well as the calculation of the probability of detection (POD) and false alarm ratio (FAR) of these indicators for days occurrence of severe rainfall and the days there was the presence of the same weather systems giving rise to severe rain events, but, however, these did not occur. With POD and RAF values obtained, we also sought to determine the most efficient indicators in the characterization of different atmospheric conditions between rainfall events analyzed. The results showed that the divergence of the wind in 300 hPa, specific humidity at 850 hPa, total energy of severe storm and precipitable water were the most efficient indicators in the identification of favorable atmospheric condition to the occurrence of severe rainfall in Rio de Janeiro the study period.


Severe rainfall; Numerical modeling; Atmospheric indicators

DOI: https://doi.org/10.11137/2015_2_81_90


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexadores e Bases BibliográficasRedes Sociais
SCImago Journal & Country Rank
22nd percentile
Powered by  Scopus
Google Scholar
 Except where otherwise noted, content on this site is licensed under a Creative Commons Attribution 4.0 International license.