With one third of the EU population living within 50 km of the coast, and one hundred thousand people annually exposed to coastal flooding in Europe [Vousdoukas et al., 2018], the combined effects of sea level rise and potential increment in the frequency and intensity of storm surges require innovative and effective monitoring and protection stategies. In recent years, substantial research effort has been dedicated to improve initial and boundary conditions of storm surge models in order to obtain more accurate sea level forecasts [De Biasio et al., 2016; De Biasio et al., 2017; Bajo et al., 2017]. The accuracy of numerical storm surge model simulations depends critically on the quality of the atmospheric forcing, i.e. the surface boundary conditions used to drive the simulation. The forcing - usually supplied to operational storm surge models by atmospheric model forecasts - is dictated by the physical variables producing the surge and determining its evolution. The wind at the sea surface has a key role, as the surge elevation depends on the wind stress, which is proportional to the squared wind speed. Zecchetto et al. [2015] have demonstrated that It is possible to improve the description of the model wind field at the sea surface using satellite scatterometer data, reducing the bias between global model forecasts and observations. The method, called wind bias mitigation (WBM), supplies a "mitigated model wind" wm' obtained by multiplication of the "standard model wind" field wm by a factor (1+?ws): wm' = (1+?ws) wm. After a period of transition, dedicated to fine-tuning the procedure algorithm [De Biasio and Zecchetto, 2017], an operational system has been set up at the Tide Forecasting and Early Warning Center of the Venice Municipality, which is in charge of providing the sea level forecast for Venice and the surrounding lagoon. The system relies on the availability of sea surface wind observations over the Mediterranean Sea coming from four satellite scatterometer: MetOp-A/B/C of EUMETSAT and ScatSat-1 of ISRO. The first three scatterometers rely on the C-band ASCAT instrument with fixed antenna geometry, while the fourth carries the Ku-band Pencil Beam scatterometer (rotating dish antenna). The four datasets are provided by the Eumetsat Satellite Application Facility on Ocean and Sea Ice (OSI-SAF) Wind subsystem, under the responsibility of the Royal Netherlands Meteorological Institute (KNMI). The data collected in one year of operation allow us to delineate a statistics of the scatterometer-model wind bias. They also permit to outline the spatial and temporal features of the sea surface wind over the Mediterranean Sea as seen by the four scatterometers, both alone and with respect to the European Centre for Medium-Range Weather Forecasts (ECMWF) high resolution deterministic model simulations.
Reducing the scatterometer-model sea surface wind bias in the Mediterranean Sea for storm-surge forecast application: the operational system of the Tide Forecasting Center in Venice
De Biasio F;S Zecchetto;
2019
Abstract
With one third of the EU population living within 50 km of the coast, and one hundred thousand people annually exposed to coastal flooding in Europe [Vousdoukas et al., 2018], the combined effects of sea level rise and potential increment in the frequency and intensity of storm surges require innovative and effective monitoring and protection stategies. In recent years, substantial research effort has been dedicated to improve initial and boundary conditions of storm surge models in order to obtain more accurate sea level forecasts [De Biasio et al., 2016; De Biasio et al., 2017; Bajo et al., 2017]. The accuracy of numerical storm surge model simulations depends critically on the quality of the atmospheric forcing, i.e. the surface boundary conditions used to drive the simulation. The forcing - usually supplied to operational storm surge models by atmospheric model forecasts - is dictated by the physical variables producing the surge and determining its evolution. The wind at the sea surface has a key role, as the surge elevation depends on the wind stress, which is proportional to the squared wind speed. Zecchetto et al. [2015] have demonstrated that It is possible to improve the description of the model wind field at the sea surface using satellite scatterometer data, reducing the bias between global model forecasts and observations. The method, called wind bias mitigation (WBM), supplies a "mitigated model wind" wm' obtained by multiplication of the "standard model wind" field wm by a factor (1+?ws): wm' = (1+?ws) wm. After a period of transition, dedicated to fine-tuning the procedure algorithm [De Biasio and Zecchetto, 2017], an operational system has been set up at the Tide Forecasting and Early Warning Center of the Venice Municipality, which is in charge of providing the sea level forecast for Venice and the surrounding lagoon. The system relies on the availability of sea surface wind observations over the Mediterranean Sea coming from four satellite scatterometer: MetOp-A/B/C of EUMETSAT and ScatSat-1 of ISRO. The first three scatterometers rely on the C-band ASCAT instrument with fixed antenna geometry, while the fourth carries the Ku-band Pencil Beam scatterometer (rotating dish antenna). The four datasets are provided by the Eumetsat Satellite Application Facility on Ocean and Sea Ice (OSI-SAF) Wind subsystem, under the responsibility of the Royal Netherlands Meteorological Institute (KNMI). The data collected in one year of operation allow us to delineate a statistics of the scatterometer-model wind bias. They also permit to outline the spatial and temporal features of the sea surface wind over the Mediterranean Sea as seen by the four scatterometers, both alone and with respect to the European Centre for Medium-Range Weather Forecasts (ECMWF) high resolution deterministic model simulations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
