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Cross‐Attractor Transforms: Improving Forecasts by Learning Optimal Maps Between Dynamical Systems and Imperfect Models
GEOPHYSICAL RESEARCH LETTERS
17 february 2025
Niraj Agarwal, Daniel E. Amrhein, Ian Grooms
Biased, incomplete numerical models are often used for forecasting states of complex dynamical systems by mapping an estimate of a “true̶...
The Averaged Hydrostatic Boussinesq Ocean Equations in Generalized Vertical Coordinates
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
17 december 2024
Malte Jansen, Alistair Adcroft, Stephen M. Griffie...
Due to their limited resolution, numerical ocean models need to be interpreted as representing filtered or averaged equations. How to interpret mod...
Investigating the Seasonality of the Ocean's Inverse Kinetic Energy Cascade using a Quasigeostrophic Model with Time-Dependent Stratification
GEOPHYSICAL FLUID DYNAMICS I ORAL
nonlinear geophysics | 12 december 2024
Houssam Yassin, Baylor Fox-Kemper, Ian Grooms
Upper ocean submesoscale dynamics (with horizontal length scales between 1-100 km) are largely unresolved by climate models. These small-scale current...
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Re-Energizing Ocean Mesoscale Eddies: Assessing Backscatter Parameterizations for Global Ocean Models
HIGH-RESOLUTION EARTH SYSTEM MODELING ON LARGE SUPERCOMPUTERS I POSTER
atmospheric sciences | 11 december 2024
Houssam Yassin, Gustavo M. Marques, Ian Grooms
Course resolution ocean models (e.g., at ~1 degree) are unable resolve mesoscale eddies over most of the ocean. To compensate for this limitation, an ...
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A non-Gaussian, Two-Step, Ensemble Data Assimilation Method for Sea Ice
ADVANCES IN DATA ASSIMILATION, DATA FUSION, MACHINE LEARNING, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IN THE GEOSCIENCES III POSTER
nonlinear geophysics | 09 december 2024
Kate Boden, Ian Grooms
The Ensemble Kalman Filter (EnKF) is a powerful tool in the geosciences to integrate real-time observations into dynamical models for an improved esti...
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Quad-EAKF: A deterministic ensemble Kalman filter with model-space localization
ADVANCES IN DATA ASSIMILATION, DATA FUSION, MACHINE LEARNING, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IN THE GEOSCIENCES III POSTER
nonlinear geophysics | 09 december 2024
Ian Grooms, Robin Armstrong
Deterministic ensemble Kalman filters can be roughly categorized into "transform" methods (like the ETKF) and "adjustment" methods (like the EAKF). Le...
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Data Assimilation Tools to Advance Earth System Science Research: The Newest Developments in NSF NCAR's Data Assimilation Research Testbed
ADVANCES IN DATA ASSIMILATION, DATA FUSION, MACHINE LEARNING, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IN THE GEOSCIENCES III POSTER
nonlinear geophysics | 09 december 2024
Kevin Raeder, Brett M. Raczka, Benjamin Gaubert, N...
Society's ability to make wise decisions depends on an accurate understanding of the state of Earth and an ability to predict future states. Data Assi...
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Cross-attractor transforms: Improving forecasts by learning optimal maps between dynamical systems and imperfect models
ADVANCES IN DATA ASSIMILATION, DATA FUSION, MACHINE LEARNING, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IN THE GEOSCIENCES III POSTER
nonlinear geophysics | 09 december 2024
Daniel E. Amrhein, Niraj Agarwal, Ian Grooms
Biased or incomplete models are often used for forecasting complex dynamical systems by mapping an estimate of an initial observed state into model ph...
View Abstract