Abstract
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.
Highlights
Mesoscale meteorological models are a powerful tool, both for operational simulation and for atmospheric investigations [1]
The Weather Research and Forecasting (WRF) model [2] is currently one of the most used in the world for these purposes, since it supports the use of very high-resolution grids for domains in any region of the planet and allows changes in its physics schemes configuration to tune it for regional conditions without having to compile it every time
The greater di erence is that TRMM shows a maximum of rainfall around 12°S and 73°W, which is less notorious in PISCO, due to the fact that in that region there are scarce meteorological stations
Summary
Mesoscale meteorological models are a powerful tool, both for operational simulation and for atmospheric investigations [1]. In this sense, the Weather Research and Forecasting (WRF) model [2] is currently one of the most used in the world for these purposes, since it supports the use of very high-resolution grids for domains in any region of the planet and allows changes in its physics schemes configuration to tune it for regional conditions without having to compile it every time. Rainfall plays an important economic role, since 71% of the arable land in the basin depends on it for crops [7]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
