Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction

24 April 2019

Papers citing "Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction"

12 / 12 papers shown

Title
History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96 Mohamed Aziz Bhouri Pierre Gentine AI4TS AI4CE 77 6 0 26 Oct 2022
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction Taehyeon Kim Namgyu Ho Donggyu Kim Se-Young Yun BDL 68 6 0 30 Jun 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 87 16 0 01 Oct 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 86 36 0 23 Jul 2021
Bridging observation, theory and numerical simulation of the ocean using Machine Learning Maike Sonnewald Redouane Lguensat Daniel C. Jones P. Dueben J. Brajard Venkatramani Balaji AI4Cl AI4CE 94 101 0 26 Apr 2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution Omer San Adil Rasheed T. Kvamsdal 89 54 0 26 Mar 2021
Machine Learning Emulation of 3D Cloud Radiative Effects David Meyer R. Hogan P. Dueben Shannon L. Mason 87 28 0 22 Mar 2021
Using machine learning to correct model error in data assimilation and forecast applications A. Farchi P. Laloyaux Massimo Bonavita Marc Bocquet AI4CE 85 107 0 23 Oct 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 88 31 0 10 Jun 2020
Data-driven super-parameterization using deep learning: Experimentation with multi-scale Lorenz 96 systems and transfer-learning Ashesh Chattopadhyay Adam Subel Pedram Hassanzadeh BDL AI4CE 66 56 0 25 Feb 2020
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model D. Gagne H. Christensen A. Subramanian A. Monahan AI4CE BDL 125 143 0 10 Sep 2019
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM Ashesh Chattopadhyay Pedram Hassanzadeh D. Subramanian AI4CE 79 40 0 20 Jun 2019