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Assessment of WRF numerical model forecasts using different lead time initializations during extreme precipitation events over Macaé city, Rio de Janeiro (Brazil)

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Abstract

The ability to forecast extreme precipitation events has become increasingly important over the last decades due to their significant impacts on society and properties. In this context, the reliability degree related to the warnings issues and a possible natural hazard is relevant. Thus, research aimed to evaluate the strengths and weaknesses of numerical forecasts can also be addressed as prevention measures. In this context, first, this study endeavored to identify the extreme precipitation events in Macaé city, Brazil. Secondly, evaluate the precipitation forecast using the Weather Research and Forecasting (WRF) model using different lead time initialization and three grids domain (27, 09, and 03 km); and investigate the thermodynamic and dynamic physical processes related to the extreme events found. From the qualitative and quantitative evaluation of the precipitation forecast, it was possible to verify that the 24 h lead time initialization presented the best performance compared to the other ones. The third domain also presented the statistical results of the precipitation forecasts, suggesting that the increased horizontal resolution enabled the model to represent mesoscale physical processes and better use high-resolution input data, such as the mountainous region of Macaé city. It was possible to verify the importance of conditional atmospheric instability, moisture offer at lower atmospheric levels, and dynamic trigger mechanisms to originate the extreme rainfall events from the thermodynamic and dynamic parameters. Lastly, we sought to show the challenges of forecasting the extreme rainfall and natural hazards imminence warnings and exploring the daily operational challenges verified in the monitoring centers and civil defenses.

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Data availability

The data used are open access. From Weather Prevision Center and Climate Studies of Brazilian National Space Research Institute (https://www.cptec.inpe.br/) and the forecast data from Global Forecast System (GFS) belonging to National Centers for Environmental Information (https://www.ncdc.noaa.gov/data-access/model-data/model-datasets). This work presents figures and tables as supplementary material.

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Acknowledgements

The authors would also like to recognize the support of Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) by means of the support through the Project FAPERJ –Edital Nº 12/2018—PROGRAMA “Apoio às Universidades Estaduais—UERJ, UENF e UEZO—2018”—Projeto Clima e Energia Proc. n.º E-26/010.101.145/2018.

Funding

This work was supported by Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) by means of the Project FAPERJ—Edital Nº 12/2018—PROGRAMA “Apoio às Universidades Estaduais—UERJ, UENF e UEZO—2018”—Projeto Clima e Energia Proc. n.º E-26/010.101.145/2018.

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Authors and Affiliations

  1. Department of Meteorology, Institute of Geosciences, Universidade Federal do Rio de Janeiro - UFRJ, CCMN ‑ Cidade Universitária - Ilha do Fundão, Avenida Athos da Silveira Ramos, 274, Rio de Janeiro, RJ, 21941‑916, Brazil

    Fabricio Polifke da Silva & Alfredo Silveira da Silva

  2. Meteorology Laboratory, Science and Technology Center, Universidade Estadual do Norte Fluminense Darcy Ribeiro - UENF, Avenida Brenand, s.n, Imboassica, Macaé, RJ, 27925‑535, Brazil

    Maria Gertrudes Alvarez Justi da Silva

  3. Engineering and Society Group, Exact Sciences and Technologies School, Universidade Iguaçu - UNIG, Avenida Abílio Augusto Távora, 2134 ‑ Jardim Nova Era, Nova Iguaçu, RJ, 26275‑580, Brazil

    Gisele Dornelles Pires

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  1. Fabricio Polifke da Silva
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da Silva, F.P., da Silva, A.S., da Silva, M.G.A.J. et al. Assessment of WRF numerical model forecasts using different lead time initializations during extreme precipitation events over Macaé city, Rio de Janeiro (Brazil). Nat Hazards 110, 695–718 (2022). https://doi.org/10.1007/s11069-021-04964-7

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