Due to El Salvador’s complex topography, its proximity to the Pacific Ocean, the predominance of convective precipitation, and the current infrastructural capacity for weather forecasting and modeling, convective permitting modeling is likely to be useful in this particular country. This work focuses on evaluating the added value of a convective permitting (CP) regional modeling approach, using the Weather Research and Forecasting Model (WRF), in the short-term operational forecast problem, and in the regional climate modeling problem for precipitation and cloud top temperature (CTT) simulated for three extreme weather events: 1) mesoscale convective system, 2) tropical depression and 3) drought. The nest grid configuration for all the events is similar to the operational forecasting configuration used at El Salvador’s Ministry of Environment and Natural Resources (MARN), and GEFS data is used as forcing boundary. Model results are compared with the GPM Final and CHIRPS data. Short-term operational forecast’s evaluation of precipitation and CTT simulation results is estimated with effectiveness of detection metric skills such as probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). Preliminary results show that GEFS ensembles suggest that WRF convective-permitting modeling using GEFS forcing improves precipitation intensity and location when compared to raw GEFS ensembles input. GEFS raw precipitation seems to be overestimated or underestimated, and sometimes the location misrepresented. Therefore, this work proposes that the usage of ensemble-based approach in WRF-CP modeling simulations can represent an alternative and better option to best capture precipitation intensity and location in cases like the Mesoscale Convective Systems or the Tropical Depression events studied in this work.
Short-term NWP forecast and regional climate modeling evaluation in convective permitting simulation of weather and climate events in El Salvador with the Weather Research and Forecasting Model
Lourdes M. Fierro1, Christopher L. Castro1
1Department of Hydrology and Atmospheric Sciences, University of Arizona