Extreme Rainfall Forecast in the Mantaro River Basin - Application of the Meteorological Model WRF
In this study, the results were evaluated of the application of the meteorological model Weather Research and Forecasting (WRF) in 103 days where extreme precipitation events (90th percentile) occurred within the Mantaro River basin. The WRF atmospheric model was used for four areas through nesting...
| Autores: | , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2023 |
| País: | Perú |
| Recursos: | Universidad Nacional Mayor de San Marcos |
| Repositório: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | espanhol |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/25992 |
| Acesso em linha: | https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/25992 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Extreme Precipitation WRF Model Rainfall Forecast Statistics Precipitación extrema Modelo WRF Pronóstico de lluvias Estadísticos |
| Resumo: | In this study, the results were evaluated of the application of the meteorological model Weather Research and Forecasting (WRF) in 103 days where extreme precipitation events (90th percentile) occurred within the Mantaro River basin. The WRF atmospheric model was used for four areas through nesting multiple, and spatial resolutions of 18, 6, 3 and 0.75 km, respectively, were obtained. Extreme precipitation forecasts were made and the effectiveness of the numerical outputs was evaluated, using observed data {\emph in-situ}, through the SENAMHI weather station network and satellite information. The values of statistical estimators show that the model tends to underestimate the rainfall data in many cases and overestimates it in others, having limitations in representing the spatial variability of the observed data. Accumulated precipitation satellite data always overestimates precipitation values, but has the ability to determine specific areas where extreme rainfall is likely to occur. |
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