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

Author:

Castorina Giuseppe123ORCID,Semprebello Agostino124ORCID,Insinga Vincenzo2,Italiano Francesco1ORCID,Caccamo Maria Teresa24ORCID,Magazù Salvatore24ORCID,Morichetti Mauro5ORCID,Rizza Umberto5ORCID

Affiliation:

1. Istituto Nazionale di Geofisica e Vulcanologia (INGV)—Sezione di Palermo, Sede Operativa di Milazzo, 98057 Milazzo, Italy

2. Consorzio Interuniversitario di Scienze Fisiche Applicate (CISFA), Piazza Salvatore Pugliatti, 98123 Messina, Italy

3. Associazione Meteo Professionisti (AMPRO), Via Francesco Morandini, 00142 Roma, Italy

4. Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra (MIFT), Università degli Studi di Messina, Viale F. Stagno D’Alcontres, 98166 Messina, Italy

5. Institute of Atmospheric Sciences and Climate (ISAC), National Research Council (CNR), Unit of Lecce, 73100 Lecce, Italy

Abstract

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.

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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