ENSO ensemble prediction: Initial error perturbations vs. model error perturbations

Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in bo...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zheng, Fei [verfasserIn] Wang, Hui [verfasserIn] Zhu, Jiang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2009

Schlagwörter:	ENSO ensemble prediction predictability initial-error perturbation model-error perturbation

Übergeordnetes Werk:	Enthalten in: Chinese science bulletin - Beijing, China : Chinese Acad. of Sciences, 1997, 54(2009), 14 vom: 21. März, Seite 2516-2523
Übergeordnetes Werk:	volume:54 ; year:2009 ; number:14 ; day:21 ; month:03 ; pages:2516-2523

Links:	Volltext

DOI / URN:	10.1007/s11434-009-0179-2

Katalog-ID:	SPR019383363

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520			\|a Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions.
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allfields	10.1007/s11434-009-0179-2 doi (DE-627)SPR019383363 (SPR)s11434-009-0179-2-e DE-627 ger DE-627 rakwb eng 500 ASE 30.00 bkl Zheng, Fei verfasserin aut ENSO ensemble prediction: Initial error perturbations vs. model error perturbations 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions. ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213 Wang, Hui verfasserin aut Zhu, Jiang verfasserin aut Enthalten in Chinese science bulletin Beijing, China : Chinese Acad. of Sciences, 1997 54(2009), 14 vom: 21. März, Seite 2516-2523 (DE-627)341897809 (DE-600)2069521-4 1861-9541 nnns volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523 https://dx.doi.org/10.1007/s11434-009-0179-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2106 GBV_ILN_2108 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_4035 GBV_ILN_4037 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4313 GBV_ILN_4328 GBV_ILN_4333 30.00 ASE AR 54 2009 14 21 03 2516-2523
spelling	10.1007/s11434-009-0179-2 doi (DE-627)SPR019383363 (SPR)s11434-009-0179-2-e DE-627 ger DE-627 rakwb eng 500 ASE 30.00 bkl Zheng, Fei verfasserin aut ENSO ensemble prediction: Initial error perturbations vs. model error perturbations 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions. ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213 Wang, Hui verfasserin aut Zhu, Jiang verfasserin aut Enthalten in Chinese science bulletin Beijing, China : Chinese Acad. of Sciences, 1997 54(2009), 14 vom: 21. März, Seite 2516-2523 (DE-627)341897809 (DE-600)2069521-4 1861-9541 nnns volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523 https://dx.doi.org/10.1007/s11434-009-0179-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2106 GBV_ILN_2108 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_4035 GBV_ILN_4037 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4313 GBV_ILN_4328 GBV_ILN_4333 30.00 ASE AR 54 2009 14 21 03 2516-2523
allfields_unstemmed	10.1007/s11434-009-0179-2 doi (DE-627)SPR019383363 (SPR)s11434-009-0179-2-e DE-627 ger DE-627 rakwb eng 500 ASE 30.00 bkl Zheng, Fei verfasserin aut ENSO ensemble prediction: Initial error perturbations vs. model error perturbations 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions. ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213 Wang, Hui verfasserin aut Zhu, Jiang verfasserin aut Enthalten in Chinese science bulletin Beijing, China : Chinese Acad. of Sciences, 1997 54(2009), 14 vom: 21. März, Seite 2516-2523 (DE-627)341897809 (DE-600)2069521-4 1861-9541 nnns volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523 https://dx.doi.org/10.1007/s11434-009-0179-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2106 GBV_ILN_2108 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_4035 GBV_ILN_4037 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4313 GBV_ILN_4328 GBV_ILN_4333 30.00 ASE AR 54 2009 14 21 03 2516-2523
allfieldsGer	10.1007/s11434-009-0179-2 doi (DE-627)SPR019383363 (SPR)s11434-009-0179-2-e DE-627 ger DE-627 rakwb eng 500 ASE 30.00 bkl Zheng, Fei verfasserin aut ENSO ensemble prediction: Initial error perturbations vs. model error perturbations 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions. ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213 Wang, Hui verfasserin aut Zhu, Jiang verfasserin aut Enthalten in Chinese science bulletin Beijing, China : Chinese Acad. of Sciences, 1997 54(2009), 14 vom: 21. März, Seite 2516-2523 (DE-627)341897809 (DE-600)2069521-4 1861-9541 nnns volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523 https://dx.doi.org/10.1007/s11434-009-0179-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2106 GBV_ILN_2108 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_4035 GBV_ILN_4037 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4313 GBV_ILN_4328 GBV_ILN_4333 30.00 ASE AR 54 2009 14 21 03 2516-2523
allfieldsSound	10.1007/s11434-009-0179-2 doi (DE-627)SPR019383363 (SPR)s11434-009-0179-2-e DE-627 ger DE-627 rakwb eng 500 ASE 30.00 bkl Zheng, Fei verfasserin aut ENSO ensemble prediction: Initial error perturbations vs. model error perturbations 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions. ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213 Wang, Hui verfasserin aut Zhu, Jiang verfasserin aut Enthalten in Chinese science bulletin Beijing, China : Chinese Acad. of Sciences, 1997 54(2009), 14 vom: 21. März, Seite 2516-2523 (DE-627)341897809 (DE-600)2069521-4 1861-9541 nnns volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523 https://dx.doi.org/10.1007/s11434-009-0179-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2106 GBV_ILN_2108 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_4035 GBV_ILN_4037 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4313 GBV_ILN_4328 GBV_ILN_4333 30.00 ASE AR 54 2009 14 21 03 2516-2523
language	English
source	Enthalten in Chinese science bulletin 54(2009), 14 vom: 21. März, Seite 2516-2523 volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523
sourceStr	Enthalten in Chinese science bulletin 54(2009), 14 vom: 21. März, Seite 2516-2523 volume:54 year:2009 number:14 day:21 month:03 pages:2516-2523
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topic_facet	ENSO ensemble prediction predictability initial-error perturbation model-error perturbation
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container_title	Chinese science bulletin
authorswithroles_txt_mv	Zheng, Fei @@aut@@ Wang, Hui @@aut@@ Zhu, Jiang @@aut@@
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author	Zheng, Fei
spellingShingle	Zheng, Fei ddc 500 bkl 30.00 misc ENSO misc ensemble prediction misc predictability misc initial-error perturbation misc model-error perturbation ENSO ensemble prediction: Initial error perturbations vs. model error perturbations
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topic_title	500 ASE 30.00 bkl ENSO ensemble prediction: Initial error perturbations vs. model error perturbations ENSO (dpeaa)DE-He213 ensemble prediction (dpeaa)DE-He213 predictability (dpeaa)DE-He213 initial-error perturbation (dpeaa)DE-He213 model-error perturbation (dpeaa)DE-He213
topic	ddc 500 bkl 30.00 misc ENSO misc ensemble prediction misc predictability misc initial-error perturbation misc model-error perturbation
topic_unstemmed	ddc 500 bkl 30.00 misc ENSO misc ensemble prediction misc predictability misc initial-error perturbation misc model-error perturbation
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title	ENSO ensemble prediction: Initial error perturbations vs. model error perturbations
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title_full	ENSO ensemble prediction: Initial error perturbations vs. model error perturbations
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title_sort	enso ensemble prediction: initial error perturbations vs. model error perturbations
title_auth	ENSO ensemble prediction: Initial error perturbations vs. model error perturbations
abstract	Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions.
abstractGer	Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions.
abstract_unstemmed	Abstract Based on our developed ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the impacts of stochastic initial-error and model-error perturbations on ENSO ensemble predictions are examined and discussed by performing four sets of 14-a retrospective forecast experiments in both a deterministic and probabilistic sense. These forecast schemes are differentiated by whether they considered the initial or model stochastic perturbations. The comparison results suggest that the stochastic model-error perturbations, which are added into the modeled physical fields to mainly represent the uncertainties of the physical model, have significant, positive impacts on improving the ensemble prediction skills during the entire 12-month forecast process. However, the stochastic initial-error perturbations have relatively small impacts on the ensemble prediction system, and its impacts are mainly focusing on the first 3-month predictions.
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title_short	ENSO ensemble prediction: Initial error perturbations vs. model error perturbations
url	https://dx.doi.org/10.1007/s11434-009-0179-2
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doi_str	10.1007/s11434-009-0179-2
up_date	2024-07-04T01:21:01.017Z
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ENSO ensemble prediction: Initial error perturbations vs. model error perturbations

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