Improving predictions of water levels and currents for Singapore regional waters through Data Assimilation using OpenDA

摘要

Hydrodynamic models are useful for predicting water levels and currents in an ocean environment. Their accuracy is typically limited by challenges such as the complexity of the physical interactions, the coastal geometry and the insufficiency of the available data to validate the model results. An example of this with much practical relevance for navigation, safety and port operations is SE Asian waters, in particular Malacca Strait and Singapore waters. The present paper addresses the improvement of predicting tides and surges through the use of a portable interface for enabling flexible data assimilation and calibration (OpenDA). Through the OpenDA interface an ensemble Kalman Filter (EnKF) is coupled to the hydrodynamic models used to improving boundary forcing. As a first step a twin experiment of improving tidal boundary forcing in a semi-enclosed estuary is studied. The results show that this data assimilation can improve model results significantly.