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Article

Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia

1
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
2
Dipartimento Protezione Civile Nazionale Ufficio III—Attività Tecnico Scientifiche per la Previsione e Prevenzione dei Rischi, 00189 Rome, Italy
3
ISAC-CNR, Strada Prov.le Lecce-Monteroni, 73100 Lecce, Italy
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(5), 541; https://doi.org/10.3390/atmos11050541
Received: 21 April 2020 / Revised: 17 May 2020 / Accepted: 21 May 2020 / Published: 22 May 2020
(This article belongs to the Special Issue Forecasting Heavy Weather in Mediterranean Region)
On 10 October 2018 an intense storm, characterized by heavy rainfall, hit the Sardinia island, reaching a peak of 452 mm of rain measured in 24 h. Among others, two particularly intense phases were registered between 3 and 6 UTC (Universal Coordinated Time), and between 18 and 24 UTC. The forecast of this case study is challenging because the precipitation was heavy and localized. In particular, the meteorological model used in this paper, provides a good prediction only for the second period over the eastern part of the Sardinia island. In this work, we study the impact of lightning data assimilation and horizontal grid resolution on the Very Short-term Forecast (VSF, 3 and 1 h) for this challenging case, using the [email protected] meteorological model. The comparison between the 3 h VSF control run and the simulations with lightning data assimilation shows the considerable improvement given by lightning data assimilation, especially for the precipitation that occurred in the eastern part of the island. Reducing the VSF range to 1 h, resulted in higher model performance with a good precipitation prediction over eastern and south-central Sardinia. In addition, the comparison between simulated and observed reflectivity shows an important improvement of simulations with lightning data assimilation compared to the control forecast. However, simulations assimilating lightning overestimated the precipitation in the last part of the day. The increasing of the horizontal resolution to 2 km grid spacing reduces the false alarms and improves the model performance. View Full-Text
Keywords: lightning data assimilation; very short-term forecast; numerical weather prediction; [email protected] lightning data assimilation; very short-term forecast; numerical weather prediction; [email protected]
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MDPI and ACS Style

Torcasio, R.C.; Federico, S.; Puca, S.; Vulpiani, G.; Comellas Prat, A.; Dietrich, S. Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia. Atmosphere 2020, 11, 541. https://doi.org/10.3390/atmos11050541

AMA Style

Torcasio RC, Federico S, Puca S, Vulpiani G, Comellas Prat A, Dietrich S. Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia. Atmosphere. 2020; 11(5):541. https://doi.org/10.3390/atmos11050541

Chicago/Turabian Style

Torcasio, Rosa C.; Federico, Stefano; Puca, Silvia; Vulpiani, Gianfranco; Comellas Prat, Albert; Dietrich, Stefano. 2020. "Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia" Atmosphere 11, no. 5: 541. https://doi.org/10.3390/atmos11050541

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