Modeling ocean transport and its biogeochemical impacts at global, regional, and sub-meso scales
type: CreativeWork
description: Improving understanding of how carbon is cycled through the ocean is crucial for predicting, mitigating, and adapting to climate change. This thesis explores how horizontal and vertical currents at different scales impact biogeochemical cycling through the redistribution of tracers such as alkalinity, nutrients, and carbon. Starting at the large scale in Chapter 2, we use a mesoscale-permitting global ocean model to investigate ocean alkalinity enhancement as a negative emissions technology. We find that local ocean dynamics are crucial for determining optimal alkalinity addition locations that maximize carbon removal, while minimizing adverse ecological impacts. Among the best locations identified are coastal upwelling systems, which are also regions of high primary productivity due to the large influx of nutrients to the surface. We take a closer look at coastal upwelling systems in Chapter 3 to identify the dynamics that impact source waters of steady-state upwelling at a regional scale, and we propose a scaling relation in which wind stress and stratification sets the upwelling source depth. Looking more closely at an upwelling front in a high-resolution submesoscale-permitting model, we see enhanced vertical velocities that reach 𝒪(100 m d−1). These submesoscale vertical velocities can enhance vertical transport, but they are very difficult to measure. In Chapter 4, we demonstrate the possibility of diagnosing the 3D submesoscale vertical velocity field from remotely-observable surface ocean observations with machine learning, which motivates future satellite missions for high-resolution remote-sensing of the surface ocean. Finally in Chapter 5, we evaluate the importance of resolving smaller scale submesoscale dynamics on the vertical transport of nutrient and phytoplankton carbon biomass in upwelling systems.
abstract: Improving understanding of how carbon is cycled through the ocean is crucial for predicting, mitigating, and adapting to climate change. This thesis explores how horizontal and vertical currents at different scales impact biogeochemical cycling through the redistribution of tracers such as alkalinity, nutrients, and carbon. Starting at the large scale in Chapter 2, we use a mesoscale-permitting global ocean model to investigate ocean alkalinity enhancement as a negative emissions technology. We find that local ocean dynamics are crucial for determining optimal alkalinity addition locations that maximize carbon removal, while minimizing adverse ecological impacts. Among the best locations identified are coastal upwelling systems, which are also regions of high primary productivity due to the large influx of nutrients to the surface. We take a closer look at coastal upwelling systems in Chapter 3 to identify the dynamics that impact source waters of steady-state upwelling at a regional scale, and we propose a scaling relation in which wind stress and stratification sets the upwelling source depth. Looking more closely at an upwelling front in a high-resolution submesoscale-permitting model, we see enhanced vertical velocities that reach 𝒪(100 m d−1). These submesoscale vertical velocities can enhance vertical transport, but they are very difficult to measure. In Chapter 4, we demonstrate the possibility of diagnosing the 3D submesoscale vertical velocity field from remotely-observable surface ocean observations with machine learning, which motivates future satellite missions for high-resolution remote-sensing of the surface ocean. Finally in Chapter 5, we evaluate the importance of resolving smaller scale submesoscale dynamics on the vertical transport of nutrient and phytoplankton carbon biomass in upwelling systems.
author: He, Jing
language: en_US
keywords: Modeling, Costal upwelling systems, Carbon removal
date published: 2023-06
date modified: 2026-07-27T22:05:23Z
provider: Woods Hole Oceanographic Institute
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Massachusetts Institute of Technology and Woods Hole Oceanographic Institution

PropertyValue
property ID: Handle
value: https://hdl.handle.net/1912/65810

PropertyValue
property ID: DOI
value: 10.1575/1912/65810