Observational estimates of ocean energy from Argo floats
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Abstract
This dissertation investigates energy in the ocean interior, focusing on the baroclinic conversion pathway
between Eddy Available Potential Energy (EAPE) and Eddy Kinetic Energy (EKE), as well as the reservoir
of EKE itself. This topic is explored using observational data from the global Argo float array, compared
to using the classic approach in ocean energy analysis of examining model output. A major component of
this dissertation is the development of methodology for estimating energy from observational data, which
requires the consideration of numerous steps of quality control, spatial averaging techniques, and merging
multiple sources of data.
Because the baroclinic conversion pathway is driven by vertical motion, I show the novel method for
estimating mesoscale vertical velocities from Argo float data at 1,000 m. We find that the distribution of
vertical velocities in the ocean is highly non-Gaussian, with a large number of small values near zero and
a small number of large values up to the order of 10−4 m s-1. The spatial variability of vertical velocity is
linked to the ocean depth, where the largest values of vertical velocity appear to occur as horizontal flow
interacts with topographic features. Due to the small magnitudes and high spatial variability, these estimates
are amongst the first for vertical velocity across wide swaths of the interior ocean.
Using these estimates of vertical velocity, I include here the result of computing the baroclinic conversion
in the Southern Ocean. Using a local least-squares spatial regression for mapping, we find the anomaly
components for vertical velocity and density that drive the conversion of energy by converting the EAPE
in sloping isopycnals into EKE. We find that the largest values of baroclinic conversion occur in the ACC
as it flows over large topographic features. The magnitude ranges from −5 to 5 × 10−5 kg m−1 s−3 but is
positively skewed meaning that potential energy is being converted into eddy kinetic energy. This is found
to agree well with model estimates of baroclinic conversion.
To further understand ocean energy, I also explore estimates of EKE throughout the water column using
the horizontal velocity field from the surface to 2,000 m estimated by Argo float profiles. To examine the
vertical structure in the EKE, we use the square of the Rossby wave vertical modes and apply two different
boundary conditions: a flat bottom and a rough bottom. Comparing the proportion of variance in the EKE
explained by the different regimes, we find that the flat-bottom boundary condition accounts for a greater
proportion of the variance in fewer modes; however, this result is spatially variable where the rough-bottom
modes are better suited for estimating the vertical structure of EKE where there are topographic features
present.
The final part of this dissertation branches away from scientific research on ocean energy and into sci
ence education, where I discuss an introductory Python programming course for oceanographic data meth
ods. Working collaboratively with another graduate student, we used evidence-based teaching practices and
a constructivist approach to redesign a course to include a flipped structure, activities infused with active
learning, an individualized final research project, and a focus on creating an accessible learning environ
ment. By analyzing quantitative and qualitative data from surveys, online learning platforms, student work,
assessments, and a focus group, we conclude that the instructional design facilitated learning and supported
self-guided scientific inquiry. Students with less or no prior exposure to coding achieved similar success as
peers with more experience, an outcome likely mediated by higher engagement with course resources.
The result of this dissertation is an examination of one branch of energy in the ocean from an observa
tional standpoint and an in-depth description of effective science communication in the classroom. Captur
ing the structure of EKE and the pathway that contributes to it is fundamental for understanding the effects
of a changing system on climate and carbon.
Description
Thesis (Ph.D.)--University of Washington, 2024
