A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast

The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are current...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2019-10, Vol.11 (20), p.2387
Main Authors: Lagasio, Martina, Parodi, Antonio, Pulvirenti, Luca, Meroni, Agostino, Boni, Giorgio, Pierdicca, Nazzareno, Marzano, Frank, Luini, Lorenzo, Venuti, Giovanna, Realini, Eugenio, Gatti, Andrea, Tagliaferro, Giulio, Barindelli, Stefano, Monti Guarnieri, Andrea, Goga, Klodiana, Terzo, Olivier, Rucci, Alessio, Passera, Emanuele, Kranzlmueller, Dieter, Rommen, Bjorn
Format: Article
Language:English
Subjects:
Atmospheric models
Boundary conditions
Case studies
Casualties
data assimilation
Earth observations (from space)
Economic forecasting
Economic models
Experiments
Floods
Global navigation satellite system
gnss water vapour
High resolution
Numerical weather forecasting
numerical weather prediction
Precipitation
Prediction models
Radiation
Rainfall
Remote sensing
Satellite constellations
Satellite observation
Satellites
sentinel 1
Severe weather
Temporal resolution
Water vapor
Weather forecasting
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Summary:The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs11202387