Verification by Multiple Methods of Precipitation Forecast from HDRFFGS and SisPI Tools during the Impact of the Tropical Storm Isaias over the Dominican Republic

Abstract

During 2020, the Dominican Republic received the impact of several tropical organisms. Among those that generated the greatest losses in the country, tropical storm Isaias stands out because of the significant precipitation (327.6 mm at Sabana del Mar during 29–31 July 2020) and flooding it caused. The study analyzes the behavior of the products of the Flash Flood Guidance System (FFGS) and the Nowcasting and Very Short Range Prediction System (Spanish acronym SisPI) for the quantitative precipitation forecast (QPF) of the precipitation generated by Isaias on 30 July 2020 over the Dominican Republic. Traditional categorical verification and featured-based spatial verification methods are used in the study, taking as observation the quantitative precipitation estimation of GPM. The results show that both numerical weather prediction systems are powerful tools for QPF and also to contribute to the prevention and mitigation of disasters caused by the extreme hydro-meteorological event analyzed. For the forecast of rain occurrence, the HIRESW-NMMB product of FFGS presented the highest ability with a CSI greater than 0.4. The HIRESW-ARW and SisPI products not only presented high rates of false alarms but also performed better in forecasting heavy rain values. The results of the verification based on objects with the MODE are consistent with those obtained in the verification by categories. The HIRESW-NMMB product underestimated the intense rainfall values by approximately 60 mm, while HIRESW-ARW and SisPI tools presented minor differences, the latter being the one with the greatest skill.