Abstract
A variety of data assimilation approaches have been applied to enhance modelling capability and accuracy using observations from different sources. The algorithms have varying degrees of complexity of implementation, and they improve model results with varying degrees of success. Very little work has been carried out on comparing the implementation of different data assimilation algorithms using High Frequency radar (HFR) data into models of complex inshore waters strongly influenced by both tides and wind dynamics, such as Galway Bay. This research entailed implementing four different data assimilation algorithms: Direct Insertion (DI), Optimal Interpolation (OI), Nudging and indirect data assimilation via correcting model forcing into a three-dimensional hydrodynamic model and carrying out detailed comparisons of model performances. This work will allow researchers to directly compare four of the most common data assimilation algorithms being used in operational coastal hydrodynamics. The suitability of practical data assimilation algorithms for hindcasting and forecasting in shallow coastal waters subjected to alternate wetting and drying using data collected from radars was assessed. Results indicated that a forecasting system of surface currents based on the three-dimensional model EFDC (Environmental Fluid Dynamics Code) and the HFR data using a Nudging or DI algorithm was considered the most appropriate for Galway Bay. The largest averaged Data Assimilation Skill Score (DASS) over the ≥6 h forecasting period from the best model NDA attained 26% and 31% for east–west and north–south surface velocity components respectively. Because of its ease of implementation and its accuracy, this data assimilation system can provide timely and useful information for various practical coastal hindcast and forecast operations.
Highlights
Significant commercial and recreational activities occur along coasts; knowledge of coastal circulation patterns is of great importance
The best assimilation parameters in each data assimilation algorithm were selected based on sensitivity tests generating closer patterns of surface currents to the High Frequency radar (HFR) data during hindcasting period
The Authors found that hourly assimilation of the HFR data did not have significantly positive impacts on forecasting when using these data assimilation algorithms
Summary
Significant commercial and recreational activities occur along coasts; knowledge of coastal circulation patterns is of great importance. The timely information of surface flow patterns with high accuracy plays a key role in many coastal activities. Hydrodynamic operational forecasting is becoming more common, and plays an important role in forecasting events such as storm surges, coastal flooding and for search and rescue missions. As electronic communication technology advances, installation of advanced remote sensing oceanic platforms based on radars or satellite mean that more and more near real-time ocean data such as surface currents and waves over a large domain and short observation windows are available [1,2,3]. A large number of radar observation systems have been deployed in coastal areas around the world due to their relatively low cost and higher data density than satellite data sources
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