GeoHydrodynamics and Environment Research
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Updated
Jun 4, 2024 - JavaScript
GeoHydrodynamics and Environment Research
sequential MCMC method for data assimilation
FEniCS implementation of the numerical method introduced in the paper E. Burman, M. Nechita and L. Oksanen, Unique continuation for the Helmholtz equation using stabilized finite element methods, J. Math. Pures Appl., 2019.
An adjointable cardiac mechanics data assimilator.
Notebooks to test out ideas or develop understanding
This is a collection of scripts and functions that serve as exercises for understanding and writing various numerical methods from scratch.
A simulated experiment to test novel applications of ensemble filtering methods to adjust for misreported time in weather prediction.
Data Assimilation Project with the Lorenz63 Model
This repository is the reproducible code of the paper Data Assimilation using ERA5, ASOS, and the U-STN model for Weather Forecasting over the UK. This paper has been accepted in the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning.
An agent-based model of wealth inequality in the US supported with an Ensemble Kalman Filter.
Correlation functions versus field-level inference in cosmology: example with log-normal fields
Nonlinear, sub-pixel correction for geophysical interpolation
A set of Data assimilation tools. Filter smoothers, ensemble and variational methods, localization, etc.
A Python-based Blended sEamLess soLver for Atmospheric dynamics coupled to an ensemble data assimilation engine
Experiments for online learning and data assimilation for time series data.
Python tools and latex files for the Colloquium
Lorenz 63 and Lorenz 96 reconstruction state with data assimilation and neural networks.
A project to correct misreported observation times in data assimilation
An interactive jupyter notebook to illustrate Kalman-Bucy filter.
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