STORM-SURGE FORECASTING USING KALMAN FILTERING

Two data assimilation procedures for real time storm surge forecasting based on Kalman filtering are described. To reduce the computational burden of the Kalman filter, a time invariant filter approximation is suggested first. This filter is computed using the Chandrasekhar-type algorithm. The resulting data assimilation procedure has been used for storm surge forecasting on a routine basis for a number of years in T he Netherlands and in Denmark. The results of these operational system s are discussed in detail. Finally also a new efficient algorithm for time varying Kalman filtering problems is introduced and applied to st orm surge forecasting.