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Non-parametric regression modelling of in situ fCO2 in the Southern Ocean
Thesis (MComm)--Stellenbosch University, 2012.
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Stellenbosch : Stellenbosch University
2012
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| _version_ | 1867613778194989056 |
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| access_status_str | Open Access |
| author | Pretorius, Wesley Byron |
| author2 | Mostert, Paul J. |
| author_browse | Mostert, Paul J. Pretorius, Wesley Byron |
| author_facet | Mostert, Paul J. Pretorius, Wesley Byron |
| author_sort | Pretorius, Wesley Byron |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MComm)--Stellenbosch University, 2012. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/71630 |
| institution | Stellenbosch University (South Africa) |
| last_indexed | 2026-06-10T12:41:32.562Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/71630 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. Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science 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 die drywers daarvoor intra- en interjaarliks varieer. 'n Tekort aan maklik verkrygbare in situ data van die Suidelike Oseaan het daartoe gelei dat 'n model benadering nodig was wat die CO2 konsentrasie plaasvervangerveranderlike, fCO2, kon voorspel. Dié moet gedoen word deur om gebruik te maak van voorspellende veranderlikes, beskikbaar deur middel van afgeleë metings, om die bruikbaarheid van die model in die toekoms te verseker. Hierdie voorspellende veranderlikes het ingesluit see-oppervlaktetemperatuur, log getransformeerde chloro l-a konsentrasie, gemengde laag diepte en op 'n latere stadium, hoogtemeting. 'n Aanvanklike, ondersoekende analise het aangedui dat 'n nie-parametriese benadering tot die data geneem moet word. 'n Parametriese meerfoudige lineêre regressie model is ontwikkel om met die vorige studies in die Noord-Atlantiese Oseaan asook met die resultate van die nieparametriese benadering te vergelyk. 'n Nie-parametriese kern regressie model is toe ingespan om die fCO2 te voorspel en uiteindelik is 'n kombinasie van die parametriese en nie-parametriese regressie modelle ontwikkel vir dieselfde doel, wat na verwys word as die gemengde regressie model. Die resultate het aangetoon, soos verwag uit die ondersoekende analise, dat die nie-parametriese benadering meer akkurate beramings lewer, gebaseer op 'n onafhanklike toets datastel. Dié meer akkurate beramings het egter met "nul"beramings gepaartgegaan wat veroorsaak word deur die vloek van dimensionaliteit. Daar is ook gevind dat die insluiting van soutgehalte (nie beskikbaar oor via sateliet nie) die model verbeter en juis daarom is hoogtemeting gekies om te poog om hierdie e ek in die model vas te vang. Die gemengde model het kleiner foute getoon asook die "nul"beramings verwyder en sodoende die variasie van die foutkoerse verminder. Die resultate het dus aangetoon dat dat die gemengde model die beste benadering is om te gebruik om die fCO2 in die Suidelike Oseaan te beraam en dat die insluiting van altimetry die akkuraatheid van hierdie beraming verbeter. Masters 2012-11-21T22:37:09Z 2012-12-12T08:07:08Z 2012-11-21T22:37:09Z 2012-12-12T08:07:08Z 2012-12 Thesis http://hdl.handle.net/10019.1/71630 Stellenbosch University 161 p. : ill., maps application/pdf Stellenbosch : Stellenbosch University |
| 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 |
| title | 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_short | 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 |
| topic | Nonparametric regression Regression analysis Nonparametric statistics Carbon dioxide -- Antarctic Ocean Dissertations -- Statistics and actuarial science Theses -- Statistics and actuarial science |
| url | http://hdl.handle.net/10019.1/71630 |
| work_keys_str_mv | AT pretoriuswesleybyron nonparametricregressionmodellingofinsitufco2inthesouthernocean |