Dinámica de Fluidos Geofísicos Computacional
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Item Open Access Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru(MDPI, 2018-09-18) Moya Álvarez, Aldo Saturnino; Gálvez, José; Holguín, Andrea; Estevan, René; Kumar, Shailendra; Villalobos Puma, Elver Edmundo; Martínez Castro, Daniel; Silva Vidal, YaminaThe 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.Item Restricted Response of the WRF model to different resolutions in the rainfall forecast over the complex Peruvian orography(Springer Nature, 2019-08-01) Moya Álvarez, Aldo Saturnino; Martínez Castro, Daniel; Kumar, Shailendra; Estevan, René; Silva Vidal, YaminaThe main objective of the research is to evaluate the response of the WRF model to the domains and resolutions that are used in complex orographic conditions like the central Andes of Peru for the forecast of short- and medium-term rainfall. To do this, the model was configured with four domains and the verifications were made using data from meteorological stations located within the study area and TRMMdata. Experiments were conducted for nine 10-day periods of rainy days, five cases of extreme rainfall, and one event with hail fall on the region. In general, the model overestimates precipitation, but, in the five cases of extreme rainfall, and in the case of the hailstorm, underestimation was observed, so it is not accurate to assert in an absolute way thatWRF overestimates precipitation in the study region. It was observed that the 3-km domain simulate effectively the accumulated rainfall, while the 0.75-km domain reproduces better the process at local scale. The results in the domain with the coarsest resolution of 18 km showed the lowest skill in simulating rainfall compared to the higher resolutions. Thus, it is concluded that an increase of resolution leads to an improvement of the results of rainfall forecast in the region and the structure of clouds systems. At the same time, the domains with resolutions of 18 km showed poorer results.Item Open Access Sensitivity study on the influence of parameterization schemes in WRF_ARW model on short- and medium-range precipitation forecasts in the Central Andes of Peru(Hindawi, 2018-05-22) Moya Álvarez, Aldo Saturnino; Martínez Castro, Daniel; Flores Rojas, José Luis; Silva Vidal, YaminaA 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 () 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.