Environmental Internship Program - 2023 Booklet

OCEANS AND
ATMOSPHERE
Charlotte Merchant ’24
COMPUTER SCIENCE
Certificates: Applied and Computational
Mathematics, Statistics and Machine Learning
PROJECT TITLE
Sensitivity Analysis of
pCO 2
Estimations and
Code Migration for
Enhanced Climate
Modeling
ORGANIZATION(S)
Max Planck Institute
for Meteorology
LOCATION(S)
Hamburg, Germany;
Ostend, Belgium
MENTOR(S)
Peter Landschützer,
Research Director,
Flanders Marine Institute
(VLIZ); Annika Jersild,
Postdoctoral Researcher,
Max Planck Institute for
Meteorology
I studied the influence of sea surface
temperatures on the estimation of the
partial pressure of carbon dioxide (pCO 2
)
globally. As a fundamental indicator of the
ocean’s thermodynamic interactions, mixing
phenomena, and air-sea interactions, sea
surface temperature remains a key predictor of
pCO 2
in statistical, algorithmic and machine
learning approaches. However, input sea surface
temperature datasets are inconsistent across all
pCO 2
estimation methods due to differences in
spatial and temporal focus, leading to sources
combining different instrumental records
and interpolation techniques. By evaluating
the sensitivity of pCO 2
predictions to different
datasets, I aimed to distill the reliability of these
estimations. In the program MATLAB, I used a
previously described two-step neural network
methodology for global pCO 2
estimation. I also
worked on migrating the MATLAB code into
the program Python to enable execution within
a high-performance computing environment.
Engaging with an early implementation
of machine learning in a climate science
context motivated me to explore how other
computational advancements can amplify the
predictive capabilities of climate models. I also
enjoyed the opportunity to engage in dynamic
discussions with colleagues. The intellectually
stimulating environment of the institute
cemented my desire to pursue further study in
climate computing.
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