On the Definition of Marginal Ice Zone Width
C. Strong, D. Foster, E. Cherkaev, I. Eisenman, K.M. Golden, On the definition and analysis of marginal ice zone width, \textit{Journal of Atmospheric and Oceanic Technology}, Vol. 34, 2017.
Education
- B.S. in Mathematics, University of Utah, 2016
- B.S. in Political Science, University of Utah, 2016
- Ph.D in Mathematics, Oregon State University, 2021
Work experience
- 2021- : Postdoctoral Research Assistant
- Massachusetts Institute of Technology
- Center for the Exascale Simulation of Materials in Extreme Environments
- Supervisor: Youssef Marzouk
- 2020-2021: Graduate Research Assistant
- National Center for Atmospheric Research
- Probabilistic AI modeling of oceanographic systems
- Supervisor: DJ Gagne, Dan Whitt
- 2018: Graduate Research Assistant
- Los Alamos National Laboratory
- Bayesian modeling of global temperature dynamics
- Supervisor: Nathan Urban
- 2016-2021: Graduate Research Assistant
- Oregon State University
- Data Assimilation for Hyperbolic Systems
- Advisor: Juan Restrepo
Publications
A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability
D. Foster, D. Comeau, and N. M. Urban, A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability, \textit{J. Climate}, 33, 6065-6081.
Dynamic Likelihood Filter: A Data Assimilation Scheme that Exploits Hyperbolicity in Wave Problems to Propagate Observations
D. Foster, J.M. Restrepo, Dynamic Likelihood Filter: A Data Assimilation Schemethat Exploits Hyperbolicity in Wave Problems to Propagate Observations, AMS MWR (submitted), 2021
Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations
D. Foster, David John Gagne II, Daniel B. Whitt, Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations, Submitted to Journal of Advances in Modeling Earth Systems, Oct. 2021.
Talks
Bayesian Parameter Estimation in Linear Inverse Models: An Application to High-Latitude Decadal Sea Surface Temperature Variability
Talk at 2019 Fall Meeting of the American Geophysical Union, San Francisco, CA
Dynamic Likelihood Filter: A Data Assimilation Scheme that Exploits Hyperbolicity in Wave Problems to Propagate Observations
Talk at 2020 Fall Meeting of the American Geophysical Union, San Francisco, California
Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations
Talk at 101st American Meteorological Society Annual Meeting, Virtual