Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting
The issue of ocean wave analysis and forecasting is today of increasing importance for a variety of scientific and social-economic purposes. In this framework, a number of state-of-the-art research and operational tools have been developed, mainly based on numerical modeling and advanced statistical...
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ftnkunivathens:oai:lib.uoa.gr:uoadl:3028100 2024-04-14T08:15:48+00:00 Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting Emmanouil, G. Galanis, G. Kallos, G. 2012-01-01 https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3028100 Αγγλικά English unknown eng uoadl:3028100 https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3028100 scientific_publication_article Επιστημονική δημοσίευση - Άρθρο Περιοδικού Scientific publication - Journal Article 2012 ftnkunivathens 2024-03-19T08:47:49Z The issue of ocean wave analysis and forecasting is today of increasing importance for a variety of scientific and social-economic purposes. In this framework, a number of state-of-the-art research and operational tools have been developed, mainly based on numerical modeling and advanced statistical techniques. The performance of the latter is essentially dependant on the utilization of external information (remote sensing and in situ measurements). In this work, a combination of ocean wave numerical models, statistical Kalman filters and data assimilation techniques is used for improvement of simulation-accuracy. More precisely, the systematic deviations of the wave model results are minimized by the use of Kalman filtering algorithms in areas with continuous flow of observations. Then, the improved outputs are assimilated by an optimum interpolation scheme, into the forecasting period of the wave model, in order to extend the assimilation impact in time and space. The case studied concerns four one-monthly intervals in the North Atlantic Ocean. © 2012 Elsevier Ltd. Article in Journal/Newspaper North Atlantic Pergamos - Library and Information Center of National and Kapodistrian University of Athens |
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Open Polar |
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Pergamos - Library and Information Center of National and Kapodistrian University of Athens |
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ftnkunivathens |
language |
unknown English |
description |
The issue of ocean wave analysis and forecasting is today of increasing importance for a variety of scientific and social-economic purposes. In this framework, a number of state-of-the-art research and operational tools have been developed, mainly based on numerical modeling and advanced statistical techniques. The performance of the latter is essentially dependant on the utilization of external information (remote sensing and in situ measurements). In this work, a combination of ocean wave numerical models, statistical Kalman filters and data assimilation techniques is used for improvement of simulation-accuracy. More precisely, the systematic deviations of the wave model results are minimized by the use of Kalman filtering algorithms in areas with continuous flow of observations. Then, the improved outputs are assimilated by an optimum interpolation scheme, into the forecasting period of the wave model, in order to extend the assimilation impact in time and space. The case studied concerns four one-monthly intervals in the North Atlantic Ocean. © 2012 Elsevier Ltd. |
format |
Article in Journal/Newspaper |
author |
Emmanouil, G. Galanis, G. Kallos, G. |
spellingShingle |
Emmanouil, G. Galanis, G. Kallos, G. Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
author_facet |
Emmanouil, G. Galanis, G. Kallos, G. |
author_sort |
Emmanouil, G. |
title |
Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
title_short |
Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
title_full |
Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
title_fullStr |
Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
title_full_unstemmed |
Combination of statistical Kalman filters and data assimilation for improving ocean waves analysis and forecasting |
title_sort |
combination of statistical kalman filters and data assimilation for improving ocean waves analysis and forecasting |
publishDate |
2012 |
url |
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3028100 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
uoadl:3028100 https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3028100 |
_version_ |
1796314250662117376 |