Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific

Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wan, Liying [verfasserIn] Zhu, Jiang [verfasserIn] Bertino, Laurent [verfasserIn] Wang, Hui [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2008

Schlagwörter:	Ensemble Kalman filter Initial ensemble HYCOM model Model uncertainty Ensemble spread Correlation pattern

Übergeordnetes Werk:	Enthalten in: Ocean dynamics - Berlin : Springer, 1948, 58(2008), 2 vom: 14. Mai
Übergeordnetes Werk:	volume:58 ; year:2008 ; number:2 ; day:14 ; month:05

Links:	Volltext

DOI / URN:	10.1007/s10236-008-0133-x

Katalog-ID:	SPR009200118

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245	1	0	\|a Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
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520			\|a Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem.
650		4	\|a Ensemble Kalman filter \|7 (dpeaa)DE-He213
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650		4	\|a Model uncertainty \|7 (dpeaa)DE-He213
650		4	\|a Ensemble spread \|7 (dpeaa)DE-He213
650		4	\|a Correlation pattern \|7 (dpeaa)DE-He213
700	1		\|a Zhu, Jiang \|e verfasserin \|4 aut
700	1		\|a Bertino, Laurent \|e verfasserin \|4 aut
700	1		\|a Wang, Hui \|e verfasserin \|4 aut
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912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
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912			\|a GBV_ILN_105
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912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_267
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
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912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
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912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
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912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
912			\|a GBV_ILN_2086
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
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912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
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matchkey_str	article:16167228:2008----::ntaesmlgnrtoadaiainooenaasiiain
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publishDate	2008
allfields	10.1007/s10236-008-0133-x doi (DE-627)SPR009200118 (SPR)s10236-008-0133-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Wan, Liying verfasserin aut Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213 Zhu, Jiang verfasserin aut Bertino, Laurent verfasserin aut Wang, Hui verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 58(2008), 2 vom: 14. Mai (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:58 year:2008 number:2 day:14 month:05 https://dx.doi.org/10.1007/s10236-008-0133-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 58 2008 2 14 05
spelling	10.1007/s10236-008-0133-x doi (DE-627)SPR009200118 (SPR)s10236-008-0133-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Wan, Liying verfasserin aut Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213 Zhu, Jiang verfasserin aut Bertino, Laurent verfasserin aut Wang, Hui verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 58(2008), 2 vom: 14. Mai (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:58 year:2008 number:2 day:14 month:05 https://dx.doi.org/10.1007/s10236-008-0133-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 58 2008 2 14 05
allfields_unstemmed	10.1007/s10236-008-0133-x doi (DE-627)SPR009200118 (SPR)s10236-008-0133-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Wan, Liying verfasserin aut Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213 Zhu, Jiang verfasserin aut Bertino, Laurent verfasserin aut Wang, Hui verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 58(2008), 2 vom: 14. Mai (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:58 year:2008 number:2 day:14 month:05 https://dx.doi.org/10.1007/s10236-008-0133-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 58 2008 2 14 05
allfieldsGer	10.1007/s10236-008-0133-x doi (DE-627)SPR009200118 (SPR)s10236-008-0133-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Wan, Liying verfasserin aut Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213 Zhu, Jiang verfasserin aut Bertino, Laurent verfasserin aut Wang, Hui verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 58(2008), 2 vom: 14. Mai (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:58 year:2008 number:2 day:14 month:05 https://dx.doi.org/10.1007/s10236-008-0133-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 58 2008 2 14 05
allfieldsSound	10.1007/s10236-008-0133-x doi (DE-627)SPR009200118 (SPR)s10236-008-0133-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Wan, Liying verfasserin aut Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem. Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213 Zhu, Jiang verfasserin aut Bertino, Laurent verfasserin aut Wang, Hui verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 58(2008), 2 vom: 14. Mai (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:58 year:2008 number:2 day:14 month:05 https://dx.doi.org/10.1007/s10236-008-0133-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 58 2008 2 14 05
language	English
source	Enthalten in Ocean dynamics 58(2008), 2 vom: 14. Mai volume:58 year:2008 number:2 day:14 month:05
sourceStr	Enthalten in Ocean dynamics 58(2008), 2 vom: 14. Mai volume:58 year:2008 number:2 day:14 month:05
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Ensemble Kalman filter Initial ensemble HYCOM model Model uncertainty Ensemble spread Correlation pattern
dewey-raw	550
isfreeaccess_bool	false
container_title	Ocean dynamics
authorswithroles_txt_mv	Wan, Liying @@aut@@ Zhu, Jiang @@aut@@ Bertino, Laurent @@aut@@ Wang, Hui @@aut@@
publishDateDaySort_date	2008-05-14T00:00:00Z
hierarchy_top_id	337809313
dewey-sort	3550
id	SPR009200118
language_de	englisch
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author	Wan, Liying
spellingShingle	Wan, Liying ddc 550 bkl 38.90 misc Ensemble Kalman filter misc Initial ensemble misc HYCOM model misc Model uncertainty misc Ensemble spread misc Correlation pattern Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
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topic_title	550 ASE 38.90 bkl Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific Ensemble Kalman filter (dpeaa)DE-He213 Initial ensemble (dpeaa)DE-He213 HYCOM model (dpeaa)DE-He213 Model uncertainty (dpeaa)DE-He213 Ensemble spread (dpeaa)DE-He213 Correlation pattern (dpeaa)DE-He213
topic	ddc 550 bkl 38.90 misc Ensemble Kalman filter misc Initial ensemble misc HYCOM model misc Model uncertainty misc Ensemble spread misc Correlation pattern
topic_unstemmed	ddc 550 bkl 38.90 misc Ensemble Kalman filter misc Initial ensemble misc HYCOM model misc Model uncertainty misc Ensemble spread misc Correlation pattern
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title	Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
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title_full	Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
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author_browse	Wan, Liying Zhu, Jiang Bertino, Laurent Wang, Hui
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title_sort	initial ensemble generation and validation for ocean data assimilation using hycom in the pacific
title_auth	Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
abstract	Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem.
abstractGer	Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem.
abstract_unstemmed	Abstract A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108–129, 1994a; J Geophys Res 99(C5):10143–10162, 1994b; Ocean Dynamics 53:343–367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem.
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title_short	Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific
url	https://dx.doi.org/10.1007/s10236-008-0133-x
remote_bool	true
author2	Zhu, Jiang Bertino, Laurent Wang, Hui
author2Str	Zhu, Jiang Bertino, Laurent Wang, Hui
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doi_str	10.1007/s10236-008-0133-x
up_date	2024-07-04T01:04:30.883Z
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Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific

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