Using machine learning to correct model error in data assimilation and forecast applications

23 October 2020

Papers citing "Using machine learning to correct model error in data assimilation and forecast applications"

30 / 30 papers shown

Title
Foundation Models for Environmental Science: A Survey of Emerging Frontiers Runlong Yu Shengyu Chen Yiqun Xie Huaxiu Yao J. Willard X. Jia AI4CE 43 1 0 05 Apr 2025
Ensemble Kalman filter in latent space using a variational autoencoder pair I. Pasmans Yumeng Chen Tobias S. Finn Marc Bocquet A. Carrassi 50 0 0 18 Feb 2025
Ensemble Transport Filter via Optimized Maximum Mean Discrepancy Dengfei Zeng Lijian Jiang OT 26 1 0 16 Jul 2024
Decomposing weather forecasting into advection and convection with neural networks Mengxuan Chen Ziqi Yuan Jinxiao Zhang Runmin Dong Haohuan Fu 45 0 0 10 May 2024
U-Net Kalman Filter (UNetKF): An Example of Machine Learning-assisted Ensemble Data Assimilation Feiyu Lu 16 0 0 19 Mar 2024
Online model error correction with neural networks: application to the Integrated Forecasting System A. Farchi M. Chrust Marc Bocquet Massimo Bonavita 26 0 0 06 Mar 2024
Learning Semilinear Neural Operators : A Unified Recursive Framework For Prediction And Data Assimilation Ashutosh Singh R. Borsoi Deniz Erdogmus Tales Imbiriba 60 0 0 24 Feb 2024
Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning Mohamad Abed El Rahman Hammoud Naila Raboudi E. Titi Omar Knio Ibrahim Hoteit AI4CE 32 2 0 01 Jan 2024
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation Yi Xiao Lei Bai Wei Xue Kang Chen Tao Han Wanli Ouyang AI4Cl 44 24 0 16 Dec 2023
Machine-learning parameter tracking with partial state observation Zheng-Meng Zhai Mohammadamin Moradi Bryan Glaz Mulugeta Haile Ying-Cheng Lai 37 7 0 15 Nov 2023
Gradient-free online learning of subgrid-scale dynamics with neural emulators Hugo Frezat Ronan Fablet G. Balarac Julien Le Sommer 32 4 0 30 Oct 2023
Interpretable structural model error discovery from sparse assimilation increments using spectral bias-reduced neural networks: A quasi-geostrophic turbulence test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 38 7 0 22 Sep 2023
Latent assimilation with implicit neural representations for unknown dynamics Zhuoyuan Li Bin Dong Pingwen Zhang AI4CE 29 3 0 18 Sep 2023
Neural Koopman prior for data assimilation Anthony Frion Lucas Drumetz M. Dalla Mura Guillaume Tochon Abdeldjalil Aissa El Bey AI4TS AI4CE 35 4 0 11 Sep 2023
Online machine-learning forecast uncertainty estimation for sequential data assimilation M. Sacco M. Pulido J. J. Ruiz P. Tandeo 32 3 0 12 May 2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 37 124 0 18 Mar 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 46 8 0 27 Jan 2023
Learning 4DVAR inversion directly from observations Arthur Filoche J. Brajard A. Charantonis Dominique Béréziat 29 2 0 17 Nov 2022
Online model error correction with neural networks in the incremental 4D-Var framework A. Farchi M. Chrust Marc Bocquet P. Laloyaux Massimo Bonavita 65 17 0 25 Oct 2022
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 27 56 0 08 Apr 2022
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models Sibo Cheng Jianhua Chen Charitos Anastasiou P. Angeli Omar K. Matar Yi-Ke Guo Christopher C. Pain Rossella Arcucci AI4CE 46 60 0 07 Apr 2022
Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects Megan R. Ebers K. Steele J. Nathan Kutz 42 15 0 10 Mar 2022
Composing a surrogate observation operator for sequential data assimilation Kosuke Akita Yuto Miyatake Daisuke Furihata 16 0 0 29 Jan 2022
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 29 15 0 01 Oct 2021
Combining data assimilation and machine learning to estimate parameters of a convective-scale model Stefanie Legler T. Janjić 48 18 0 07 Sep 2021
State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics Quentin Malartic A. Farchi Marc Bocquet 41 19 0 23 Jul 2021
A comparison of combined data assimilation and machine learning methods for offline and online model error correction A. Farchi Marc Bocquet P. Laloyaux Massimo Bonavita Quentin Malartic OffRL 41 35 0 23 Jul 2021
A Framework for Machine Learning of Model Error in Dynamical Systems Matthew E. Levine Andrew M. Stuart 32 67 0 14 Jul 2021
Variational Data Assimilation with a Learned Inverse Observation Operator Thomas Frerix Dmitrii Kochkov Jamie A. Smith Daniel Cremers M. Brenner Stephan Hoyer 41 29 0 22 Feb 2021
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 64 70 0 10 Feb 2020