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Article

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

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CIMA Research Foundation, 17100 Savona, Italy
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Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy
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Department of Civil, Chemical and Environmental Engineering, University of Genoa, 16145 Genoa, Italy
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Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00185 Rome, Italy
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Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
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Geomatics Research and Development (GReD) s.r.l., 22074 Lomazzo, Italy
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LINKS Foundation, 10138 Turin, Italy
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TRE ALTAMIRA s.r.l., 20143 Milan, Italy
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Leibniz Supercomputing Centre, Ludwig Maximilians University of Munich, 85748 Munich, Germany
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European Space Agency (ESA)—European Space Research and Technology Center (ESTEC), 2201 AZ Noordwijk, The Netherlands
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2387; https://doi.org/10.3390/rs11202387
Received: 31 July 2019 / Revised: 8 October 2019 / Accepted: 12 October 2019 / Published: 15 October 2019
(This article belongs to the Special Issue Weather Forecasting and Modeling Using Satellite Data)
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. View Full-Text
Keywords: numerical weather prediction; data assimilation; Sentinel 1; GNSS water vapour numerical weather prediction; data assimilation; Sentinel 1; GNSS water vapour
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MDPI and ACS Style

Lagasio, M.; Parodi, A.; Pulvirenti, L.; Meroni, A.N.; Boni, G.; Pierdicca, N.; Marzano, F.S.; Luini, L.; Venuti, G.; Realini, E.; Gatti, A.; Tagliaferro, G.; Barindelli, S.; Monti Guarnieri, A.; Goga, K.; Terzo, O.; Rucci, A.; Passera, E.; Kranzlmueller, D.; Rommen, B. A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast. Remote Sens. 2019, 11, 2387. https://doi.org/10.3390/rs11202387

AMA Style

Lagasio M, Parodi A, Pulvirenti L, Meroni AN, Boni G, Pierdicca N, Marzano FS, Luini L, Venuti G, Realini E, Gatti A, Tagliaferro G, Barindelli S, Monti Guarnieri A, Goga K, Terzo O, Rucci A, Passera E, Kranzlmueller D, Rommen B. A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast. Remote Sensing. 2019; 11(20):2387. https://doi.org/10.3390/rs11202387

Chicago/Turabian Style

Lagasio, Martina, Antonio Parodi, Luca Pulvirenti, Agostino N. Meroni, Giorgio Boni, Nazzareno Pierdicca, Frank S. Marzano, Lorenzo Luini, Giovanna Venuti, Eugenio Realini, Andrea Gatti, Giulio Tagliaferro, Stefano Barindelli, Andrea Monti Guarnieri, Klodiana Goga, Olivier Terzo, Alessio Rucci, Emanuele Passera, Dieter Kranzlmueller, and Bjorn Rommen. 2019. "A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast" Remote Sensing 11, no. 20: 2387. https://doi.org/10.3390/rs11202387

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