1 Perspectives for a data assimilation system in Tagus Estuary
In this work a simplified extended Kalman filter correcting state along pre-specified error variability modes is applied, in a twin experiment, to a 2D hydrodynamic model of a large shallow Northeast Atlantic tidal estuary- the Tagus Estuary (Portugal) – and adjacent coast to correct a forecast erro...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.543.8382 2023-05-15T17:41:28+02:00 1 Perspectives for a data assimilation system in Tagus Estuary Ângela Canasa The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.543.8382 http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.543.8382 http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf Estuarine dynamics Tide gauges Modelling Kalman filters Twin experiment MOHID Water Portugal text ftciteseerx 2016-01-08T11:11:45Z In this work a simplified extended Kalman filter correcting state along pre-specified error variability modes is applied, in a twin experiment, to a 2D hydrodynamic model of a large shallow Northeast Atlantic tidal estuary- the Tagus Estuary (Portugal) – and adjacent coast to correct a forecast error derived from mean sea level perturbation with tide gauge measurements. Forecast error departures from normal probability distribution are assessed to verify optimality of the filter correction. Considering a system state comprised of water level and zonal and meridional horizontal velocity components, the error variability modes are derived from the EOF analysis of historical model forecast estimates. The filter performance is assessed in several coastal locations in the context of different number of measurement locations and use of different error variability modes. Important departures from normal probability distribution in the forecast error are detected in some of the locations, which are explained by bathymetry shallowness and circulation. The forecast state variability is very much dominated by astronomic tide, whose presence is evident in the first two EOFs which represent more than 70 % of total variability. Error variability, which is not related to tide, appears to be captured only on lower eigenvalue EOFs and very affected by local processes. The consideration of the Text Northeast Atlantic Unknown |
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English |
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Estuarine dynamics Tide gauges Modelling Kalman filters Twin experiment MOHID Water Portugal |
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Estuarine dynamics Tide gauges Modelling Kalman filters Twin experiment MOHID Water Portugal Ângela Canasa 1 Perspectives for a data assimilation system in Tagus Estuary |
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Estuarine dynamics Tide gauges Modelling Kalman filters Twin experiment MOHID Water Portugal |
description |
In this work a simplified extended Kalman filter correcting state along pre-specified error variability modes is applied, in a twin experiment, to a 2D hydrodynamic model of a large shallow Northeast Atlantic tidal estuary- the Tagus Estuary (Portugal) – and adjacent coast to correct a forecast error derived from mean sea level perturbation with tide gauge measurements. Forecast error departures from normal probability distribution are assessed to verify optimality of the filter correction. Considering a system state comprised of water level and zonal and meridional horizontal velocity components, the error variability modes are derived from the EOF analysis of historical model forecast estimates. The filter performance is assessed in several coastal locations in the context of different number of measurement locations and use of different error variability modes. Important departures from normal probability distribution in the forecast error are detected in some of the locations, which are explained by bathymetry shallowness and circulation. The forecast state variability is very much dominated by astronomic tide, whose presence is evident in the first two EOFs which represent more than 70 % of total variability. Error variability, which is not related to tide, appears to be captured only on lower eigenvalue EOFs and very affected by local processes. The consideration of the |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Ângela Canasa |
author_facet |
Ângela Canasa |
author_sort |
Ângela Canasa |
title |
1 Perspectives for a data assimilation system in Tagus Estuary |
title_short |
1 Perspectives for a data assimilation system in Tagus Estuary |
title_full |
1 Perspectives for a data assimilation system in Tagus Estuary |
title_fullStr |
1 Perspectives for a data assimilation system in Tagus Estuary |
title_full_unstemmed |
1 Perspectives for a data assimilation system in Tagus Estuary |
title_sort |
1 perspectives for a data assimilation system in tagus estuary |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.543.8382 http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf |
genre |
Northeast Atlantic |
genre_facet |
Northeast Atlantic |
op_source |
http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.543.8382 http://maretec.mohid.com/PublicData/products/Papers/TagusAssimilationINSEAPaper.pdf |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766143054272528384 |