Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Oceanography
2019
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613922062761984 |
|---|---|
| access_status_str | Open Access |
| author | Luyt, Hermann |
| author2 | Backeberg, B C |
| author_browse | Backeberg, B C Luyt, Hermann |
| author_facet | Backeberg, B C Luyt, Hermann |
| author_sort | Luyt, Hermann |
| collection | Thesis |
| 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 SSH increments but the associated increase in SST is significantly reduced by the assimilated SST, resulting in a reduction of the bias with very little impact on the current dynamics. This is reflected in the surface velocitiy increments, which are similar to or worse than that of HYCOMSLA. Investigating the potential of HYCOM-EnOI as an operational forecasting system has revealed that the assimilation of SST and along-track SLA vastly improves modelled SST for the BUS upwelling. Errors in the free-running model, which constitutes the static ensemble, need addressing and comparisons between MODIS and OSTIA SSTs suggests that OSTIA may not be ideally suited for assimilation in the case of coastal upwelling, due to limitations in capturing the dynamics correctly. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/29734 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:43:50.434Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Department of Oceanography |
| publisherStr | Department of Oceanography |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/29734 Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System Luyt, Hermann Backeberg, B C Veitch, J Vichi, M Oceanography 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 SSH increments but the associated increase in SST is significantly reduced by the assimilated SST, resulting in a reduction of the bias with very little impact on the current dynamics. This is reflected in the surface velocitiy increments, which are similar to or worse than that of HYCOMSLA. Investigating the potential of HYCOM-EnOI as an operational forecasting system has revealed that the assimilation of SST and along-track SLA vastly improves modelled SST for the BUS upwelling. Errors in the free-running model, which constitutes the static ensemble, need addressing and comparisons between MODIS and OSTIA SSTs suggests that OSTIA may not be ideally suited for assimilation in the case of coastal upwelling, due to limitations in capturing the dynamics correctly. 2019-02-22T10:39:46Z 2019-02-22T10:39:46Z 2018 2019-02-21T13:29:25Z Master Thesis Masters MSc http://hdl.handle.net/11427/29734 eng application/pdf Department of Oceanography Faculty of Science University of Cape Town |
| spellingShingle | Oceanography Luyt, Hermann Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System |
| thesis_degree_str | Master's |
| title | 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_short | 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 |
| topic | Oceanography |
| url | http://hdl.handle.net/11427/29734 |
| work_keys_str_mv | AT luythermann quantifyingthesstbiasesindataassimilativeoceansimulationsofthebenguelaupwellingsystem |