Group
Students and alumni working on data assimilation and prediction.
Our group brings together students from atmospheric and oceanic science and applied mathematics who share an interest in data assimilation, uncertainty quantification, and prediction. Many projects are carried out jointly with scientists at NOAA, NASA, NSF NCAR, and the Naval Research Laboratory.
Student members
10 Ph.D. studentsComparing how particle filters and ensemble Kalman filters shape uncertainty in NOAA's global model using singular vectors, and bringing data assimilation to machine learning models of the atmosphere.
Expanding small ensembles with statistically generated members so particle filters stay accurate at low cost, starting with low-order models (with J. Chan, Ohio State University).
Developing data assimilation capabilities for estimating and monitoring carbon fluxes in NASA's GEOS model, with carbon cycle scientists at Goddard's Global Modeling and Assimilation Office.
Testing hourly cycled Bayesian data assimilation with the local particle filter in NOAA's global Unified Forecast System, toward more frequently updated forecasts and reanalyses.
Constraining atmospheric forcing errors for sea ice data assimilation, and developing methods to assimilate far-infrared radiances from NASA's PREFIRE mission over Arctic sea ice.
Learning likelihoods with generative machine learning, including marginalized likelihoods that stabilize ensemble data assimilation when observations depend on small-scale processes that small ensembles sample poorly.
Predicting hurricane intensity forecast uncertainty in NOAA's HAFS with machine learning, informed by rapid intensity changes and satellite precipitation structure (with the Naval Research Laboratory).
Quantifying how atmospheric rivers shape snowfall, snow depth, and mass balance on Antarctic sea ice, how their role is changing, and the circulation patterns behind their impacts.
Retrieving winds in the atmospheres of Neptune and other planets in our solar system with a multi-incremental 3DVar framework (with NASA Goddard's Planetary Systems Laboratory).
Developing fully non-parametric data assimilation with learned likelihoods, using manifold learning and kernel embeddings to assimilate sea ice concentration without explicit measurement operators.
Alumni
- Joseph Knisely
Ph.D. · AOSC“Towards a Self-Contained Analysis and Reanalysis System for Hurricanes”2026 - Joshua McCurry
Ph.D. · AOSC“Implications of New Observing and Data Assimilation Strategies for Moist Convection in the Atmosphere”2025 - Kenta Kurosawa
Ph.D. · AOSC“Bridging Gaussian and non-Gaussian Data Assimilation for High-Dimensional Geophysical Models”2023 - Craig Schwartz
Ph.D. · AOSC/NCAR“An Evaluation of Convection-Allowing Ensemble Forecast Sensitivity to Initial Conditions”2021
- Alisha Wellington
M.S. · AOSC“Analyzing Ensemble Uncertainty Using Contour Band Depth: Atlantic Hurricane Season 2022”2024 - Gillian Felton
M.S. · AOSC · academic advisor; research advisor M. Gerst“Recommendations on Forecast Verification Methodology and Communication for the DAWN Project”2024 - Benjamin Sheppard
M.S. · AOSC“Implications of Non-Gaussian Data Assimilation for Probabilistic Prediction Using Ensembles”2023 - Andrew Walsworth
M.S. · AOSC“Challenges for Online Observation Error Estimation Revealed from Idealized Numerical Experiments”2022
- Nick Szapiro
Postdoctoral researcher · ESSIC2022 – 2024 - Deanna Easley
Postdoctoral researcher · ESSIC2022 – 2023
- Malcolm Maas
Honors thesis · AOSC“Using Diffusion Maps to Quantify Data Assimilation and Microphysical Errors in Convective Clouds”2025 - Sean Engler
Senior thesis · AOSC · co-advised with Ph.D. student J. McCurry“Evaluating the Accuracy of an Experimental Hurricane Model During Hurricane Marco and Hurricane Laura”2024 - Randall Bowers
Senior thesis · AOSC · co-advised with Ph.D. student H. Santer“Probabilistic Predictions for Tropical Cyclones Explored Using Contour Band Depth”2023 - Henry Santer
Summer internship (CISESS) · AOSC“Visualizing Ensemble Uncertainty With Contour Boxplots”2021 - Charles Kropiewnicki
Senior thesis · AOSC · co-advised with J. Henrikson“Impact of Forecast Error Covariance on Ensemble Model Accuracy”2021 - Gavin Harrison
Senior thesis · AOSC“Hurricane Nowcasting With Particle Filters”2021 - Katriella Tenembaum
Senior thesis · AOSC“Exploring Imbalance Introduced by EnKFs in Tropical Cyclone Analyses”2020 - Audrey Nash
Senior thesis · AOSC“Forecast Challenges Posed by Convective Outbreaks Associated With Landfalling Hurricanes”2020