Performance of the WRF Model for the Forecasting of the V-Shaped Storm Recorded on 11–12 November 2019 in the Eastern Sicily

During the autumn season, Sicily is often affected by severe weather events, such as self-healing storms called V-shaped storms. These phenomena cause significant total rainfall quantities in short time intervals in localized spatial areas. In this framework, this study analyzes the meteorological e...

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Bibliographic Details
Published in:Atmosphere 2023-02, Vol.14 (2), p.390
Main Authors: Castorina, Giuseppe, Semprebello, Agostino, Insinga, Vincenzo, Italiano, Francesco, Caccamo, Maria Teresa, Magazù, Salvatore, Morichetti, Mauro, Rizza, Umberto
Format: Article
Language:English
Subjects:
Climate change
Cyclone forecasting
Data assimilation
Data collection
False alarms
FDDA
Forecasting
Mathematical models
Methods
Modelling
numerical weather prediction
Observatories
Performance indices
Precipitation
precipitation forecast
Precipitation forecasting
Probability theory
Rain
Rain and rainfall
Rainfall
Root-mean-square errors
Severe weather
severe weather events
Simulation
Storms
Temperature
Vortices
Weather
Weather forecasting
Weather stations
WRF model
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Summary:During the autumn season, Sicily is often affected by severe weather events, such as self-healing storms called V-shaped storms. These phenomena cause significant total rainfall quantities in short time intervals in localized spatial areas. In this framework, this study analyzes the meteorological event recorded on 11–12 November 2019 in Sicily (southern Italy), using the Weather Research and Forecasting (WRF) model with a horizontal spatial grid resolution of 3 km. It is important to note that, in this event, the most significant rainfall accumulations were recorded in eastern Sicily. In particular, the weather station of Linguaglossa North Etna (Catania) recorded a total rainfall of 293.6 mm. The precipitation forecasting provided by the WRF model simulation has been compared with the data recorded by the meteorological stations located in Sicily. In addition, a further simulation was carried out using the Four-Dimensional Data Assimilation (FDDA) technique to improve the model capability in the event reproduction. In this regard, in order to evaluate which approach provides the best performance (with or without FDDA), the Root Mean Square Error (RMSE) and dichotomous indexes (Accuracy, Threat Score, BIAS, Probability of Detection, and False Alarm Rate) were calculated.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos14020390