On data-driven induction of the low-frequency variability in a coarse-resolution ocean model EA Ryzhov, D Kondrashov, N Agarwal, JC McWilliams, P Berloff Ocean Modelling 153, 101664, 2020 | 21 | 2020 |
A comparison of data‐driven approaches to build low‐dimensional ocean models N Agarwal, D Kondrashov, P Dueben, E Ryzhov, P Berloff Journal of Advances in Modeling Earth Systems 13 (9), e2021MS002537, 2021 | 17 | 2021 |
On data-driven augmentation of low-resolution ocean model dynamics EA Ryzhov, D Kondrashov, N Agarwal, PS Berloff Ocean Modelling 142, 101464, 2019 | 17 | 2019 |
Correlation-based flow decomposition and statistical analysis of the eddy forcing N Agarwal, EA Ryzhov, D Kondrashov, P Berloff Journal of Fluid Mechanics 924, A5, 2021 | 10 | 2021 |
Impact of Stochastic Ocean Density Corrections on Air‐Sea Flux Variability N Agarwal, RJ Small, FO Bryan, I Grooms, PJ Pegion Geophysical Research Letters 50 (13), e2023GL104248, 2023 | 1 | 2023 |
Cross-attractor transforms: Improving forecasts by learning optimal maps between dynamical systems and imperfect models N Agarwal, DE Amrhein, I Grooms Authorea Preprints, 2024 | | 2024 |
Cross-Attractor Transformations: A Novel Machine Learning Framework to Minimize Forecast Error in the Presence of Model Bias N Agarwal, DE Amrhein, I Grooms Authorea Preprints, 2023 | | 2023 |
Impact of stochastic ocean density corrections on air-sea flux variability N Agarwal, J Small, FO Bryan, I Grooms, P Pegion Authorea Preprints, 2022 | | 2022 |
On the Parameterization of Sub-Grid Scale Density Variations in Ocean Circulation Models N Agarwal, F Bryan, I Grooms AGU Fall Meeting Abstracts 2022, NG42B-0400, 2022 | | 2022 |
Statistical-dynamical analyses and modelling of multi-scale ocean variability N Agarwal Imperial College London, 2021 | | 2021 |