Cargando…

Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter

The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. Ho...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Xuan, Tandeo, Pierre, Fablet, Ronan, Husson, Romain, Guan, Lei, Chen, Ge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190981/
https://www.ncbi.nlm.nih.gov/pubmed/27898005
http://dx.doi.org/10.3390/s16122000
_version_ 1782487525060771840
author Wang, Xuan
Tandeo, Pierre
Fablet, Ronan
Husson, Romain
Guan, Lei
Chen, Ge
author_facet Wang, Xuan
Tandeo, Pierre
Fablet, Ronan
Husson, Romain
Guan, Lei
Chen, Ge
author_sort Wang, Xuan
collection PubMed
description The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets.
format Online
Article
Text
id pubmed-5190981
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-51909812017-01-03 Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter Wang, Xuan Tandeo, Pierre Fablet, Ronan Husson, Romain Guan, Lei Chen, Ge Sensors (Basel) Article The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. MDPI 2016-11-25 /pmc/articles/PMC5190981/ /pubmed/27898005 http://dx.doi.org/10.3390/s16122000 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Xuan
Tandeo, Pierre
Fablet, Ronan
Husson, Romain
Guan, Lei
Chen, Ge
Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title_full Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title_fullStr Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title_full_unstemmed Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title_short Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
title_sort validation and parameter sensitivity tests for reconstructing swell field based on an ensemble kalman filter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190981/
https://www.ncbi.nlm.nih.gov/pubmed/27898005
http://dx.doi.org/10.3390/s16122000
work_keys_str_mv AT wangxuan validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter
AT tandeopierre validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter
AT fabletronan validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter
AT hussonromain validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter
AT guanlei validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter
AT chenge validationandparametersensitivitytestsforreconstructingswellfieldbasedonanensemblekalmanfilter