Assimilating Surface Current Data into a Model of Estuarine and Coastal Ocean Circulation

A surface current observation system based on High Frequency (HF) radar has been developed in Raritan Bay, New Jersey; and New York Bight Apex. The availability of surface current data, measured using HF radar in real time over a synoptic scale of the order of hundreds of kilometers makes it appropriate for data assimilation. The present work is an attempt to develop a practical, but still nearly optimal, method for the assimilation of HF radar data into an estuarine and coastal ocean circulation model, providing more accurate hindcasts, nowcasts, and forecasts for the study domain. Data assimilation scheme used in the present work is based on nudging technique. A nudging parameter is introduced to the equations of motion, which affects the model dynamics and the information is imparted to neighboring (three-dimensional) grid points. The data assimilation is limited to near surface layers, which depends on a prescribed exponential decay parameter. Prior to the data assimilation of HF radar derived surface currents into an operational New York Harbor Observing and Prediction System (NYHOPS), a series of sensitivity experiments were conducted using idealized estuaries to study the effects of the data assimilation on the circulation away from the assimilation site. An idealized estuary with a long straight channel configuration and a curved configuration were considered. The effect of the data assimilation is studied with respect to fresh water, tide, curvature, and density stratification conditions. The nudging scheme is robust, and can be easily implemented in the real-time data assimilation of the NYHOPS forecast model.