Remote Estimation of Surface Water p CO 2 in the Gulf of Mexico

• Main Author: Chen, Shuangling
• Format: Doctoral or Postdoctoral Thesis
• Language: unknown
• Published: Digital Commons @ University of South Florida 2018
• Subjects: dominant controls; remote sensing; sea surface salinity; surface pCO2; Other Earth Sciences; Ocean acidification
• Online Access: https://digitalcommons.usf.edu/etd/8107; https://digitalcommons.usf.edu/context/etd/article/9304/viewcontent/Chen_usf_0206D_15061.pdf

Surface ocean partial pressure of CO2 (pCO2) is a critical parameter in the quantification of air-sea CO2 flux, which further plays an important role in quantifying the global carbon budget and understanding ocean acidification. The demand for a clearer understanding of how, and how fast, the ocean is changing due to atmospheric CO2 absorption, requires accurate and synoptic estimation of surface pCO2. Surface ocean pCO2 is mainly controlled by four oceanic processes – thermodynamics, ocean mixing, biological activities, and air-sea CO2 exchange. Surface ocean pCO2 is therefore closely related to environmental variables that characterize each oceanic process. These variables include sea surface temperature (SST), sea surface salinity (SSS), chlorophyll-a concentration (Chl), diffuse attenuation of downwelling irradiance (Kd), and wind speed. Ocean color satellites provide a means by which the relationship between these environmental variables and surface pCO2 can be developed. Yet, remote estimation of surface pCO2 in coastal oceans has been difficult due to the dynamic and complex biogeochemical processes. To date, most of the published satellite-based pCO2 models are developed for single-process dominated regions, therefore having poor applicability in other oceanic regions. Particularly, there is no unified approach, let alone unified model, to remotely estimate surface pCO2 in oceanic regions that are dominated by different oceanic processes. This work provides solutions to these challenging issues for the remote estimation of surface pCO2 in the Gulf of Mexico (GOM), with the following objectives: 1) Develop satellite-based surface pCO2 models and data products for single-process dominated subregions of the GOM, and quantify the sensitivities of the pCO2 algorithms to the input environmental variables; 2) Quantify the oceanic processes in controlling surface pCO2 in the GOM, analyze the relationships between environmental variables and surface pCO2, and understand the mechanisms of seasonal and interannual ...