Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System
The Benguela Upwelling System (BUS) on the west coast of southern Africa is one of the global ocean’s most productive upwelling systems supporting a large fishing industry, a fledgling aquaculture sector and offshore mining interests. Despite intensive monitoring and modelling studies, there is no r...
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Department of Oceanography
2018
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ftunivcapetownir:oai:open.uct.ac.za:11427/29734 2024-09-15T18:35:36+00:00 Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System Luyt, Hermann Backeberg, B C Veitch, J Vichi, M 2018 application/pdf http://hdl.handle.net/11427/29734 eng eng Department of Oceanography Faculty of Science University of Cape Town http://hdl.handle.net/11427/29734 Oceanography Master Thesis Masters MSc 2018 ftunivcapetownir 2024-06-25T04:01:00Z The Benguela Upwelling System (BUS) on the west coast of southern Africa is one of the global ocean’s most productive upwelling systems supporting a large fishing industry, a fledgling aquaculture sector and offshore mining interests. Despite intensive monitoring and modelling studies, there is no regionally tailored ocean forecasting system that is explicitly developed to deal with the unique ocean dynamics of the Benguela. In this study, the Hybrid Coordinate Ocean Model (HYCOM) is used in conjunction with the Ensemble Optimal Interpolation (EnOI) assimilation scheme to study the impact of assimilating sea surface temperature (SST) and along-track sea level anomalies (SLA) observations on predicted upwelling dynamics in the Benguela. In order to evaluate the predictive skill and impact of data assimilation, three experiments with HYCOMEnOI are evaluated: (1) with no assimilation (HYCOMFREE), (2) only assimilating along-track SLA (HYCOMSLA) and (3) assimilating both SLA and SST (HYCOMSLA+SST). Using MODIS Terra SST as reference, the model SST outputs are evaluated. HYCOMFREE is found to exhibit a warm bias along the coast, HYCOMSLA shows an even greater warm bias while HYCOMSLA+SST conversely shows a much improved SST forecast skill. It is hypothesised that the warm biases could be due to errors in boundary conditions and/or the ERA-interim wind product used to force the model. Furthermore, a comparison of the assimilated SST product (the Operational Sea Surface Temperature and Sea Ice Analysis; OSTIA) with MODIS SST reveals biases in OSTIA up to ±1 ◦C, raising questions over its suitability for assimilation in upwelling regions. Studying the effect of assimilation on SSH, SST and surface currents before and after the assimilation suggests that an increase in SSH from assimilated SLA leads to increased warm SST biases in HYCOMSLA. This is due to an incorrect relationship between SSH and SST in the free-running HYCOM, from which the static ensemble is derived for the EnOI. HYCOMSLA+SST exhibits slightly enhanced ... Master Thesis Sea ice University of Cape Town: OpenUCT |
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University of Cape Town: OpenUCT |
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ftunivcapetownir |
language |
English |
topic |
Oceanography |
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Oceanography Luyt, Hermann Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
topic_facet |
Oceanography |
description |
The Benguela Upwelling System (BUS) on the west coast of southern Africa is one of the global ocean’s most productive upwelling systems supporting a large fishing industry, a fledgling aquaculture sector and offshore mining interests. Despite intensive monitoring and modelling studies, there is no regionally tailored ocean forecasting system that is explicitly developed to deal with the unique ocean dynamics of the Benguela. In this study, the Hybrid Coordinate Ocean Model (HYCOM) is used in conjunction with the Ensemble Optimal Interpolation (EnOI) assimilation scheme to study the impact of assimilating sea surface temperature (SST) and along-track sea level anomalies (SLA) observations on predicted upwelling dynamics in the Benguela. In order to evaluate the predictive skill and impact of data assimilation, three experiments with HYCOMEnOI are evaluated: (1) with no assimilation (HYCOMFREE), (2) only assimilating along-track SLA (HYCOMSLA) and (3) assimilating both SLA and SST (HYCOMSLA+SST). Using MODIS Terra SST as reference, the model SST outputs are evaluated. HYCOMFREE is found to exhibit a warm bias along the coast, HYCOMSLA shows an even greater warm bias while HYCOMSLA+SST conversely shows a much improved SST forecast skill. It is hypothesised that the warm biases could be due to errors in boundary conditions and/or the ERA-interim wind product used to force the model. Furthermore, a comparison of the assimilated SST product (the Operational Sea Surface Temperature and Sea Ice Analysis; OSTIA) with MODIS SST reveals biases in OSTIA up to ±1 ◦C, raising questions over its suitability for assimilation in upwelling regions. Studying the effect of assimilation on SSH, SST and surface currents before and after the assimilation suggests that an increase in SSH from assimilated SLA leads to increased warm SST biases in HYCOMSLA. This is due to an incorrect relationship between SSH and SST in the free-running HYCOM, from which the static ensemble is derived for the EnOI. HYCOMSLA+SST exhibits slightly enhanced ... |
author2 |
Backeberg, B C Veitch, J Vichi, M |
format |
Master Thesis |
author |
Luyt, Hermann |
author_facet |
Luyt, Hermann |
author_sort |
Luyt, Hermann |
title |
Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
title_short |
Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
title_full |
Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
title_fullStr |
Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
title_full_unstemmed |
Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
title_sort |
quantifying the sst biases in data assimilative ocean simulations of the benguela upwelling system |
publisher |
Department of Oceanography |
publishDate |
2018 |
url |
http://hdl.handle.net/11427/29734 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
http://hdl.handle.net/11427/29734 |
_version_ |
1810478795889573888 |