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...
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ftunivalaska:oai:scholarworks.alaska.edu:11122/10993 2023-05-15T15:54:29+02:00 Assimilation of High-Frequency Radar Data in the East Chukchi Sea Stroh, J. Panteleev, G. G. Yaremchuk, M. Weingartner, T. 2014-03 http://hdl.handle.net/11122/10993 en_US eng http://hdl.handle.net/11122/10993 Poster 2014 ftunivalaska 2023-02-23T21:37:36Z 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. Still Image Chukchi Chukchi Sea University of Alaska: ScholarWorks@UA Chukchi Sea |
institution |
Open Polar |
collection |
University of Alaska: ScholarWorks@UA |
op_collection_id |
ftunivalaska |
language |
English |
description |
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. |
format |
Still Image |
author |
Stroh, J. Panteleev, G. G. Yaremchuk, M. Weingartner, T. |
spellingShingle |
Stroh, J. Panteleev, G. G. Yaremchuk, M. Weingartner, T. Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
author_facet |
Stroh, J. Panteleev, G. G. Yaremchuk, M. Weingartner, T. |
author_sort |
Stroh, J. |
title |
Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
title_short |
Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
title_full |
Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
title_fullStr |
Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
title_full_unstemmed |
Assimilation of High-Frequency Radar Data in the East Chukchi Sea |
title_sort |
assimilation of high-frequency radar data in the east chukchi sea |
publishDate |
2014 |
url |
http://hdl.handle.net/11122/10993 |
geographic |
Chukchi Sea |
geographic_facet |
Chukchi Sea |
genre |
Chukchi Chukchi Sea |
genre_facet |
Chukchi Chukchi Sea |
op_relation |
http://hdl.handle.net/11122/10993 |
_version_ |
1766389683971948544 |