Assimilation of High-Frequency Radar Data in the East Chukchi Sea
The maximum-likelihood ensemble filter (MLEF) is an eficient technique of data assimilation related to both 3D-variational (3Dvar) and Ensemble Kalman Filter (EnKF) methods. We demonstrate the utility of MLEF by assimilating high-frequency radar (HFR) data into a realistic model of the east Chukchi...
| Main Authors: | , , , |
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| Format: | Still Image |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11122/10993 |
| Summary: | The maximum-likelihood ensemble filter (MLEF) is an eficient technique of data assimilation related to both 3D-variational (3Dvar) and Ensemble Kalman Filter (EnKF) methods. We demonstrate the utility of MLEF by assimilating high-frequency radar (HFR) data into a realistic model of the east Chukchi Sea. A set of three radar stations in Wainwright, Point Lay, and Barrow provide two-dimensional resolution of the sea-surface velocity. We use MLEF to incorporate this HFR data into a numerical model constructed using the Regional Ocean Modelling System (ROMS) for the ice-free months of 2012. The resulting analysis can be used as a benchmark for future operational forecasting, allowing for better real-time monitoring and decision-making as this biologically rich region is influenced by industry and commerce. |
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