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 The Netherlands and in Denmark. The results of these operational systems are discussed in detail. Finally also a new efficient algorithm for time varying Kalman filtering problems is introduced and applied to storm surge forecasting.