Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Assimilating X- and S-band Radar Data for a Heavy Precipitation Event in Italy

Version 1 : Received: 3 June 2021 / Approved: 4 June 2021 / Online: 4 June 2021 (12:54:12 CEST)

A peer-reviewed article of this Preprint also exists.

Capecchi, V.; Antonini, A.; Benedetti, R.; Fibbi, L.; Melani, S.; Rovai, L.; Ricchi, A.; Cerrai, D. Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy. Water 2021, 13, 1727. Capecchi, V.; Antonini, A.; Benedetti, R.; Fibbi, L.; Melani, S.; Rovai, L.; Ricchi, A.; Cerrai, D. Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy. Water 2021, 13, 1727.

Journal reference: Water 2021, 13, 1727
DOI: 10.3390/w13131727

Abstract

During the night between 9 and 10 September 2017, multiple flash floods associated to a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours, associated with a return period higher than 200 years, caused all the largest streams of the Livorno municipality to flood several areas of the town. We used the limited-area Weather Research and Forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. By providing more accurate descriptions of the low-level flow and a better assessment of the atmospheric water vapour, the results demonstrate that assimilating radar data improved the quantitative precipitation forecasts.

Subject Areas

WRF model; 3D-Var data assimilation; radar data; short-range prediction; heavy precipitation event

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.