Abstract
Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the protection of lives and goods. In this study, the skill of the Numerical Tool for Hurricane Forecast (NTHF) for determining rainfall pattern, average rainfall, rainfall volume, and extreme amounts of rain observed during TCs is evaluated against Tropical Rainfall Measuring Mission (TRMM) data. A sample comprising nine systems formed in the North Atlantic basin from 2016 to 2018 is used, where the analysis begins 24 h before landfall. Several statistical indices characterising the abilities of the NTHF and climatology and persistence model for rainfalls (R-CLIPER) for forecasting rain as measured by the TRMM are calculated at 24, 48, and 72 h forecasts for each TC and averaged. The model under consideration presents better forecasting skills than the R-CLIPER for all the attributes evaluated and demonstrates similar performances compared with models reported in the literature. The proposed model predicts the average rainfall well and presents a good description of the rain pattern. However, its forecast of extreme rain is only applicable for 24 h.
Highlights
Tropical cyclones (TCs) are among the most devastating atmospheric phenomena, as they result in strong surface winds, tornadoes, storm surges, and heavy rainfall events
The model can forecast rainfall [20], it has not been evaluated for Cuba and the Inter-American Oceans. e aim of this study is to evaluate the abilities of the Numerical Tool for Hurricane Forecast (NTHF) system for forecasting rainfall associated with TCs, as reported by the Tropical Rainfall Measuring Mission (TRMM). e system demonstrated excellent predictions of the average rainfall and a good description of the rain pattern; its forecast of extreme rain was only applicable for 24 h
Rain field data simulated by models NTHF and R-CLIPER were statistically compared with the satellite observations of the TRMM. ree important elements in the forecast of TC precipitation were considered: ability to match rainfall patterns around the centre, ability to match average and distribution of rainfall volume, and ability to reproduce the largest rain values that are typically related with TCs. e R-CLIPER model was used as a reference and comparison for all study cases
Summary
Tropical cyclones (TCs) are among the most devastating atmospheric phenomena, as they result in strong surface winds, tornadoes, storm surges, and heavy rainfall events. Heavy rainfall events are distributed over wide areas and can cause flash flooding, thereby resulting in human and economic losses. E interaction of the storm with the Earth surface, as well as the available humidity, and intensity of the cyclone significantly affect the distribution and amount of rain [7]. A close relationship between precipitation distribution and thermodynamical symmetry has been discovered in the evolution of Hurricane Edouard [8]. In recent years, these factors have been incorporated in numerical models to perform a quantitative forecast of the track, intensity, and precipitation
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