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A sensitivity study of the performance of the Weather Research and Forecasting regional model (WRF, version 3.7) to the use of different microphysics, cumulus, and boundary layer parameterizations for short- and medium-term precipitation forecast is conducted in the Central Andes of Peru. Lin-Purdué, Thompson, and Morrison microphysics schemes were tested, as well as the Grell–Freitas, Grell 3d, and Betts–Miller–Janjic cumulus parameterizations. The tested boundary layer schemes were the Yonsei University and Mellor–Yamada–Janjic. A control configuration was defined, using the Thompson, Grell–Freitas, and Yonsei University schemes, and a set of numerical experiments is made, using different combinations of parameterizations. Data from 19 local meteorological stations and regional and global gridded were used for verification. It was concluded that all the configurations overestimate precipitation, but the one using the Morrison microphysical scheme had the best performance, based on the indicators of bias (B) and root mean square error (RMSE). It is recommended not to use the Betts–Miller–Janjic scheme in this region for low resolution domains. Categorical forecast verification of the occurrence of rainfall as a binary variable showed detection rates higher than 85%. According to this criterion, the best performing configuration was the combination of Betts–Miller–Janjic and Morrison. Spatial verification showed that, even if all the configurations overestimated precipitation in some degree, spatial patterns of rainfall match the TRMM and PISCO rainfall data. Morrison’s microphysics scheme shows the best results, and consequently, this configuration is recommended for short- and medium-term rainfall forecasting tasks in the Central Andes of Peru and particularly in the Mantaro basin. The results of a special sensitivity experiment showed that the activation or not of cumulus parametrization for the domain of 3 km resolution is not relevant for the precipitation forecast in the study region.

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.

The present study explores the cloud microphysics (MPs) impact on the simulation of two convective rainfall events (CREs) over the complex topography of Andes mountains, using the Weather Research and Forecasting- Advanced Research (WRF-ARW) model. The events occurred on December 29 2015 (CRE1) and January 7 2016 (CRE2). Six microphysical parameterizations (MPPs) (Thompson, WSM6, Morrison, Goddard, Milbrandt and Lin) were tested, which had been previously applied in complex orography areas. The one-way nesting technique was applied to four domains, with horizontal resolutions of 18, 6, and 3 km for the outer ones, in which cumulus and MP parameterizations were applied, while for the innermost domain, with a resolution of 0.75 km, only MP parameterization was used. It was integrated for 36 h with National Centers for Environmental Prediction (NCEP Final Operational Global Analysis (NFL) initial conditions at 00:00 UTC (Coordinated Universal Time). The simulations were verified using Geostationary Operational Environmental Satellites (GOES) brightness temperature, Ka band cloud radar, and surface meteorology variables observed at the Huancayo Observatory. All the MPPs detected the surface temperature signature of the CREs, but for CRE2, it was underestimated during its lifetime in its vicinity, matching well after the simulated event. For CRE1, all the schemes gave good estimations of 24 h precipitation, but for CRE2, Goddard and Milbrandt underestimated the 24 h precipitation in the inner domain. The Morrison and Lin configurations reproduced the general dynamics of the development of cloud systems for the two case studies. The vertical profiles of the hydrometeors simulated by different schemes showed significant differences. The best performance of the Morrison scheme for both case studies may be related to its ability to simulate the role of graupel in precipitation formation. The analysis of the maximum reflectivity field, cloud top distribution, and vertical structure of the simulated cloud field also shows that the Morrison parameterization reproduced the convective systems consistently with observations.

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