Quantifying ocean carbon and oxygen cycles using Biogeochemical Argo

Abstract

The ocean plays an important role in the global carbon and oxygen cycles. Not only has it taken up one third of total anthropogenic carbon dioxide emissions, but it also produces 50% of the oxygen in the atmosphere due to phytoplankton that live in the surface ocean. This thesis explores different aspects of the ocean carbon and oxygen cycles using Biogeochemical (BGC) Argo, which is a global array of autonomous drifting profiling floats. Chapter 2 of this thesis addresses the question of: “How can we improve BGC-Argo float oxygen measurement and address biases related to sensor response time?” by characterizing the temperature and flow speed dependence of a suite of oxygen optodes that are or may become suitable for profiling applications. This work provides a novel approach for estimating sensor response time based on physical principles from temperature, salinity, and flow speed measurements. In Chapter 3, particulate backscatter data from the global BGC Argo float array is used to better constrain metrics of the biological carbon pump for both small and large sinking particles. Results from this work find that the transfer efficiency, which is the fraction of carbon exported out of the surface ocean that makes it to a specified depth horizon and is an important metric because deeper export results in longer carbon sequestration times, is high at low latitudes and low at high latitudes. In Chapters 4 and 5, BGC-Argo oxygen data is used in combination with other observational oxygen datasets to evaluate how effectively current ocean observing systems can spatially interpolate sparse and irregularly gridded observations onto a uniform grid, using temperature and salinity variability, in the subpolar North Atlantic. These Chapters leverage machine learning and compare results to previously published gridded oxygen products. Ultimately, this thesis work spans various spatial and temporal scales, tackling important questions in ocean observing from the sensor to global scale, with additional benefits of reducing uncertainties in sensor measurements and global fluxes, all of which are necessary for understanding and modeling the current state of the ocean to better model the future one.