Non-parametric regression modelling of in situ fCO2 in the Southern Ocean
Thesis (MComm)--Stellenbosch University, 2012. ENGLISH ABSTRACT: The Southern Ocean is a complex system, where the relationship between CO2 concentrations and its drivers varies intra- and inter-annually. Due to the lack of readily available in situ data in the Southern Ocean, a model approach was r...
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ftunstellenbosch:oai:scholar.sun.ac.za:10019.1/71630 2023-11-12T04:06:27+01:00 Non-parametric regression modelling of in situ fCO2 in the Southern Ocean Pretorius, Wesley Byron Mostert, Paul J. Das, Sonali Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science. 2012-11-21T22:37:09Z 161 p. : ill., maps application/pdf http://hdl.handle.net/10019.1/71630 unknown Stellenbosch : Stellenbosch University http://hdl.handle.net/10019.1/71630 Stellenbosch University Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science Thesis 2012 ftunstellenbosch 2023-10-22T07:19:23Z Thesis (MComm)--Stellenbosch University, 2012. ENGLISH ABSTRACT: The Southern Ocean is a complex system, where the relationship between CO2 concentrations and its drivers varies intra- and inter-annually. Due to the lack of readily available in situ data in the Southern Ocean, a model approach was required which could predict the CO2 concentration proxy variable, fCO2. This must be done using predictor variables available via remote measurements to ensure the usefulness of the model in the future. These predictor variables were sea surface temperature, log transformed chlorophyll-a concentration, mixed layer depth and at a later stage altimetry. Initial exploratory analysis indicated that a non-parametric approach to the model should be taken. A parametric multiple linear regression model was developed to use as a comparison to previous studies in the North Atlantic Ocean as well as to compare with the results of the non-parametric approach. A non-parametric kernel regression model was then used to predict fCO2 and nally a combination of the parametric and non-parametric regression models was developed, referred to as the mixed regression model. The results indicated, as expected from exploratory analyses, that the non-parametric approach produced more accurate estimates based on an independent test data set. These more accurate estimates, however, were coupled with zero estimates, caused by the curse of dimensionality. It was also found that the inclusion of salinity (not available remotely) improved the model and therefore altimetry was chosen to attempt to capture this e ect in the model. The mixed model displayed reduced errors as well as removing the zero estimates and hence reducing the variance of the error rates. The results indicated that the mixed model is the best approach to use to predict fCO2 in the Southern Ocean and that altimetry's inclusion did improve the prediction accuracy. AFRIKAANSE OPSOMMING: Die Suidelike Oseaan is 'n komplekse sisteem waar die verhouding tussen CO2 konsentrasies en ... Thesis Antarc* Antarctic Antarctic Ocean North Atlantic Southern Ocean Stellenbosch University: SUNScholar Research Repository Antarctic Antarctic Ocean Southern Ocean Tussen ENVELOPE(18.950,18.950,-72.075,-72.075) |
institution |
Open Polar |
collection |
Stellenbosch University: SUNScholar Research Repository |
op_collection_id |
ftunstellenbosch |
language |
unknown |
topic |
Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science |
spellingShingle |
Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science Pretorius, Wesley Byron Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
topic_facet |
Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science |
description |
Thesis (MComm)--Stellenbosch University, 2012. ENGLISH ABSTRACT: The Southern Ocean is a complex system, where the relationship between CO2 concentrations and its drivers varies intra- and inter-annually. Due to the lack of readily available in situ data in the Southern Ocean, a model approach was required which could predict the CO2 concentration proxy variable, fCO2. This must be done using predictor variables available via remote measurements to ensure the usefulness of the model in the future. These predictor variables were sea surface temperature, log transformed chlorophyll-a concentration, mixed layer depth and at a later stage altimetry. Initial exploratory analysis indicated that a non-parametric approach to the model should be taken. A parametric multiple linear regression model was developed to use as a comparison to previous studies in the North Atlantic Ocean as well as to compare with the results of the non-parametric approach. A non-parametric kernel regression model was then used to predict fCO2 and nally a combination of the parametric and non-parametric regression models was developed, referred to as the mixed regression model. The results indicated, as expected from exploratory analyses, that the non-parametric approach produced more accurate estimates based on an independent test data set. These more accurate estimates, however, were coupled with zero estimates, caused by the curse of dimensionality. It was also found that the inclusion of salinity (not available remotely) improved the model and therefore altimetry was chosen to attempt to capture this e ect in the model. The mixed model displayed reduced errors as well as removing the zero estimates and hence reducing the variance of the error rates. The results indicated that the mixed model is the best approach to use to predict fCO2 in the Southern Ocean and that altimetry's inclusion did improve the prediction accuracy. AFRIKAANSE OPSOMMING: Die Suidelike Oseaan is 'n komplekse sisteem waar die verhouding tussen CO2 konsentrasies en ... |
author2 |
Mostert, Paul J. Das, Sonali Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science. |
format |
Thesis |
author |
Pretorius, Wesley Byron |
author_facet |
Pretorius, Wesley Byron |
author_sort |
Pretorius, Wesley Byron |
title |
Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
title_short |
Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
title_full |
Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
title_fullStr |
Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
title_full_unstemmed |
Non-parametric regression modelling of in situ fCO2 in the Southern Ocean |
title_sort |
non-parametric regression modelling of in situ fco2 in the southern ocean |
publisher |
Stellenbosch : Stellenbosch University |
publishDate |
2012 |
url |
http://hdl.handle.net/10019.1/71630 |
long_lat |
ENVELOPE(18.950,18.950,-72.075,-72.075) |
geographic |
Antarctic Antarctic Ocean Southern Ocean Tussen |
geographic_facet |
Antarctic Antarctic Ocean Southern Ocean Tussen |
genre |
Antarc* Antarctic Antarctic Ocean North Atlantic Southern Ocean |
genre_facet |
Antarc* Antarctic Antarctic Ocean North Atlantic Southern Ocean |
op_relation |
http://hdl.handle.net/10019.1/71630 |
op_rights |
Stellenbosch University |
_version_ |
1782327548179382272 |