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

TL;DR

This study demonstrates that assimilating X- and S-band radar data into a high-resolution weather model significantly improves the accuracy of precipitation forecasts during a severe flash flood event in Italy.

Contribution

It introduces an innovative verification method and shows how radar data assimilation enhances precipitation prediction accuracy in extreme weather events.

Findings

Radar data assimilation improved forecast accuracy.

Enhanced low-level flow and water vapor assessment.

Better prediction of heavy precipitation events.

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.