Data Assimilation with Python: a Package for Experimental Research
-
Updated
Aug 15, 2024 - Python
Data Assimilation with Python: a Package for Experimental Research
Tutorials on data assimilation (DA) and the EnKF
FlowNet - Data-Driven Reservoir Predictions
Official implementation of Score-based Data Assimilation
This is a 'hands-on' tutorial for the RIKEN International School on Data Assimilation (RISDA2018).
Benchmarking tools for applying AI/ML to data assimilation
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.
Estimating observation and model errors in ocean data assimilation
Pre- and post-processing for MIKE FM Data Assimilation
An AOT-based algorithm to estimate multiple unknown parameters in the Kuramoto-Saviashinski equation. Source code for the paper "Concurrent Multiparameter Learning Demonstrated on the Kuramoto-Sivashinsky Equation" by Pachev, Whitehead, and McQuarrie.
Simple Reservoir Simulator and ESMDA
This is a basic python interface to CRTM v2.3.0.
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.
A simulated experiment to test novel applications of ensemble filtering methods to adjust for misreported time in weather prediction.
Nonlinear, sub-pixel correction for geophysical interpolation
DAHSI code package for model selection with hidden variables
Cryospheric Monitoring and Prediction Online
Nino-Ruiz, Elias D., and Sebastian Racedo Valbuena. "TEDA: A Computational Toolbox for Teaching Ensemble Based Data Assimilation." Computational Science–ICCS 2022: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. Cham: Springer International Publishing, 2022.
A Python-based Blended sEamLess soLver for Atmospheric dynamics coupled to an ensemble data assimilation engine
Add a description, image, and links to the data-assimilation topic page so that developers can more easily learn about it.
To associate your repository with the data-assimilation topic, visit your repo's landing page and select "manage topics."