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 in this study, 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. We first establish that atypical events in the region are those with more than 27 mm of rainfall per day when averaging over all the stations. More than 50% of the selected cases occurred during January, February, and April, with the most extreme occurring during February. The average synoptic conditions show negative geopotential anomalies and positive humidity anomalies in 700 and 500 hPa. At 200 hPa, the subtropical upper ridge or “Bolivian high” was present, with its northern divergent flank over the Mantaro basin. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases, mainly in the south of the basin and in the extreme west along the mountain range. 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, apparently related to processes of larger scales; 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.
Warming sea-surface temperatures (SSTs) have implications for the climate-sensitive Caribbean region, including potential impacts on precipitation. SSTs have been shown to influence deep convection and rainfall, thus understanding the impacts of warming SSTs is important for predicting regional hydrometeorological conditions. This study investigates the long-term annual and seasonal trends in convection using the Galvez-Davison Index (GDI) for tropical convection from 1982–2020. The GDI is used to describe the type and potential for precipitation events characterized by sub-indices that represent heat and moisture availability, cool/warm mid-levels at 500 hPa, and subsidence inversion, which drive the regional Late, Early, and Dry Rainfall Seasons, respectively. Results show that regional SSTs are warming annually and per season, while regionally averaged GDI values are decreasing annually and for the Dry Season. Spatial analyses show the GDI demonstrates higher, statistically significant correlations with precipitation across the region than with sea-surface temperatures, annually and per season. Moreover, the GDI climatology results show that regional convection exhibits a bimodal pattern resembling the characteristic bimodal precipitation pattern experienced in many parts of the Caribbean and surrounding region. However, the drivers of these conditions need further investigation as SSTs continue to rise while the region experiences a drying trend.
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