Maike Sonnewald

Developing pathways between theoretical, observational and computational oceanography

The ocean is a key component of the climate system acting as a sink for heat and carbon dioxide. Helping to understand dynamics to predict change, I use inference from theory, computational tools and dynamical systems theory.
Modern oceanography is interdisciplinary: the field is becoming data rich from observations and models, creating a need for new tools. I am a physical oceanographer using computer science/dynamical systems tools to explore decadal ocean dynamics. Passionate about bringing together different branches of oceanography, my goal is to discover the underlying principles that govern ocean dynamics from small to global scales. My work connects to observational efforts and model parameterizations, and I also work on ocean acidification and ecology in collaborative efforts. I focus on the global ocean, using scalable methods, with a special interest in the Southern Ocean and the North Atlantic.

Associate Research Scholar at Princeton University and Geophysical Fluid Dynamics Laboratory

I currently focus on understanding how small scale dynamics impact global features like heat transport in simulations allowing mesoscale turbulence. This work continues the development of the SAGE (Systematic AGgregated Eco-province) method, combining statistical tools, unsupervised machine learning and graphs, designed to work with non-linear data ubiquitous in oceanography and beyond. Overall, my research areas include:
  • Objective region discovery for dynamics, ecology and acidification
  • Vorticity dynamics
  • Predictability of sea level
  • Small scale interactions with bathymetry
  • Machine learning and dynamical systems
More details under projects, and a list of publications here.
I am invested in furthering the modernisation of computational resources used in oceanography:
  • Conceptualize (plan) a US Research Software Sustainability Institute that goes beyond resources like GitHub
  • Join the discussion on Open Code at NASA and AMS.
  • Further the use of Open Code and development processes
  • Focus on the entire research software ecosystem, including the people who create, maintain, and use research software
  • Work towards reproducible research as described in this paper

Popular press articles

Ecological provinces: Eos Buzz News, MIT News, SciTechDailyand Scienceblog. It also featured on The Batch from deeplearning.ai.
Dynamical regimes: MIT News, Artificial Intelligence Research, physics.org, and ECN magazine.

My work was highlighted at the Data Institute of the Univ. Grenoble Alpes.

Institute for Complex Systems Simulation and the National Oceanography Centre

I was awarded a PhD in Complex Systems Simulation, working to bring dynamical systems theory back to physical oceanography under title: "Ocean model utility dependence on horizontal resolution". This was the first systematic assessment of changing the resolution of a global realistic ocean model from non-eddy resolving through eddy-permiting to eddy resolving. Major topics we explored were to do with the boundary layers and how to quantify "utility" and divergence:
  • Surface: Mixed Layer Depth
  • Interior: Steric decompositions and surface-depth covariance
  • Depth: Baroclinic/barotropic topographic interactions and the imprint on the overturning
  • Lyapunov divergence of SSH field
  • Notional functions for defining utility

I worked with Joel J.M. Hirschi, George Nurser and James Dyke. There is a copy here. See resulting publications under publications.