Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru

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Karam, HA
Pereira, AJ
Rojas, JLF
Salas, LFS
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Multidisciplinary Digital Publishing Institute (MDPI)
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The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated, using observations from stations located in the Mantaro basin and GOES (Geostationary Operational Environmental Satellite) images. The evaluation analyzes the synoptic conditions averaged over 40 extreme event cases, and considers model simulations organized in 4 nested domains. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases. The analysis of two case studies shows that the underestimation by the model is probably due to three reasons: inability to generate convection in the upstream Amazon during early morning hours, limitations on describing mesoscale processes that lead to vertical movements capable of producing extreme rainfall, and limitations on the microphysics scheme to generate heavy rainfall.
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Precipitación, Meteorología y ciencias atmosféricas