Impact of using scatterometer and altimeter data on storm surge forecasting

- We use scatterometer data to tune biased model wind and altimeter data assimilation in storm surge modelling.
- Unbiased global wind achieves better rms error and correlation than local wind.
- The maximum storm surge peaks are reproduced better by high resolution wind.
- Altimeter data assimilation can be used independently by the wind forcing.
- Altimeter data assimilation improves only in some cases (in presence of seiches).

Satellite data are rarely used in storm surge models because of the lack of established methodologies. Nevertheless, they can provide useful information on surface wind and sea level, which can potentially improve the forecast. In this paper satellite wind data are used to correct the bias of wind originating from a global atmospheric model, while satellite sea level data are used to improve the initial conditions of the model simulations. In a first step, the capability of global winds (biased and unbiased) to adequately force a storm surge model are assessed against that of a high resolution local wind. Then, the added value of direct assimilation of satellite altimeter data in the storm surge model is tested. Eleven storm surge events, recorded in Venice from 2008 to 2012, are simulated using different configurations of wind forcing and altimeter data assimilation. Focusing on the maximum surge peak, results show that the relative error, averaged over the eleven cases considered, decreases from 13% to 7%, using both the unbiased wind and assimilating the altimeter data, while, if the high resolution local wind is used to force the hydrodynamic model, the altimeter data assimilation reduces the error from 9% to 6%. Yet, the overall capabilities in reproducing the surge in the first day of forecast, measured by the correlation and by the rms error, improve only with the use of the unbiased global wind and not with the use of high resolution local wind and altimeter data assimilation.