Along the Mediterranean coastlines, intense and localized rainfall events are responsible for numerous casualties and several million euros of damage every year. Numerical forecasts of such events are rarely skillful, because they lack information in their initial and boundary conditions at the relevant spatio-temporal scales, namely O(km) and O(h). In this context, the tropospheric delay observations (strongly related to the vertically integrated water vapor content) of the future geosynchronous Hydroterra satellite could provide valuable information at a high spatio-temporal resolution. In this work, Observing System Simulation Experiments (OSSEs) are performed to assess the impact of assimilating this new observation in a cloud-resolving meteorological model, at different grid spacing and temporal frequencies, and with respect to other existent observations. It is found that assimilating the Hydroterra observations at 2.5 km spacing every 3 or 6 h has the largest positive impact on the forecast of the event under study. In particular, a better spatial localization and extent of the heavy rainfall area is achieved and a realistic surface wind structure, which is a crucial element in the forecast of such heavy rainfall events, is modeled.

Meteorological OSSEs for new Zenith Total Delay observations: Impact assessment for the Hydroterra geosynchronous satellite on the October 2019 Genoa event

Meroni A. N.;Monti-Guarnieri A.;
2020-01-01

Abstract

Along the Mediterranean coastlines, intense and localized rainfall events are responsible for numerous casualties and several million euros of damage every year. Numerical forecasts of such events are rarely skillful, because they lack information in their initial and boundary conditions at the relevant spatio-temporal scales, namely O(km) and O(h). In this context, the tropospheric delay observations (strongly related to the vertically integrated water vapor content) of the future geosynchronous Hydroterra satellite could provide valuable information at a high spatio-temporal resolution. In this work, Observing System Simulation Experiments (OSSEs) are performed to assess the impact of assimilating this new observation in a cloud-resolving meteorological model, at different grid spacing and temporal frequencies, and with respect to other existent observations. It is found that assimilating the Hydroterra observations at 2.5 km spacing every 3 or 6 h has the largest positive impact on the forecast of the event under study. In particular, a better spatial localization and extent of the heavy rainfall area is achieved and a realistic surface wind structure, which is a crucial element in the forecast of such heavy rainfall events, is modeled.
2020
Data assimilation
Extreme rainfall
Geosynchronous satellite
InSAR
IWV
Mediterranean
ZTD
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1154136
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