A novel empirical approach to diagnose patterns of air-sea carbon dioxide fluxes and ocean acidification
Understanding the oceans role in mitigating atmospheric CO2 and climate requires a good constraint on spatiotemporal variability in the ocean carbon system. However, large spatiotemporal data limitations hamper our ability to quantify and understand patterns of ocean carbon dynamics. Here, I have de...
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| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
| Published: |
UNSW, Sydney
2013
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| Online Access: | http://hdl.handle.net/1959.4/52867 https://unsworks.unsw.edu.au/bitstreams/18c8314b-aca2-48b8-85f9-440561882d30/download https://doi.org/10.26190/unsworks/2482 |
| Summary: | Understanding the oceans role in mitigating atmospheric CO2 and climate requires a good constraint on spatiotemporal variability in the ocean carbon system. However, large spatiotemporal data limitations hamper our ability to quantify and understand patterns of ocean carbon dynamics. Here, I have developed a novel empirical approach to predict inorganic CO2 concentrations (total inorganic carbon (CT), total alkalinity (AT) and partial pressure of CO2 (pCO2)) in the global ocean mixed-layer using standard hydrographic parameters (SHP; temperature, salinity, dissolved oxygen and nutrients) in order to provide independent constraints and insights on our understanding of ocean carbon dynamics, air-sea gas exchange and ocean acidification. The novel technique, called SOMLO (Self-Organizing Multiple-Linear Output), couples a neural-network clustering algorithm with a multiple-linear regression to derive empirical relationships using bottle-data. Deploying and testing the SOMLO approach on a newly synthesized global bottle-dataset showed significant improvements over traditional linear approaches; improving global predictive skill by 19% for CT, with a global capacity to predict CT to within ±10.9 μmol kg-1 (±9.2 μmol kg-1 for AT and ±22.5 μatm for pCO2). In particular, the new non-linear method improved predictive skill in the most complex and dynamically important regions of the ocean (equatorial Pacific and Southern Ocean) by up to 30%. The SOMLO approach was then applied to monthly SHP climatologies (WOA09) in order to diagnose monthly ocean surface CT, AT and pCO2 patterns for the nominal year of 2000. Based on this analysis, patterns of air-sea CO2 flux were diagnosed and found to be broadly consistent with the global underway pCO2 database, suggesting a contemporary oceanic CO2 uptake of 1.10±0.25 PgC yr-1 for the year of 2000. However, significant differences were found in 30% of the ocean, particularly in the equatorial Pacific and Southern Oceans. For ocean acidification, seasonality in CO2 was found to bring ... |
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