Data Assimilation with Python: a Package for Experimental Research

Ert has been split into three repositories, libecl, libres, and ert, and now lives at Equinor's GitHub organization — https://github.com/equinor/libecl | https://github.com/equinor/libres | https://github.com/equinor/ert

Tutorials on data assimilation (DA) and the EnKF

EnKF code for DA with large-scale layered geophysical models.

Kalman filter sanctuary - including continuous-discrete extended Kalman filter. Bring additional filters here for a bigger collection.

EnKF analysis routines in Fortran 90. Stochastich and SQRT formulations with subspace inversion.

Ensemble-based history matching method with latent-space proxy model for nonlinear forward model and non-Gaussian models.

A Python interface to parallel data assimilation framework - pyPDAF

A companion repository to "A low-rank ensemble Kalman filter for elliptic observations" by Le Provost et al. (2022)

Tutorials for variational methods and EnKF with Lorenz 1963 and 1996

A collection of time-efficient state estimation algorithms for the medium-fidelity WindFarmSimulator (WFSim) control model

⌨️ Nino-Ruiz, E.D., & Consuegra Ortega (2023) AMLCS-DA: A data assimilation package in Python for Atmospheric General Circulation Models. SoftwareX, Elsevier, 1– 10. Available from: https://doi.org/10.1016/j.softx.2023.101374

the hub for all the computational projects related to NWP, DA, and predictability

Code used for the paper "A Method for Imaging Energetic Particle Precipitation with Subionospheric VLF Signals"

This repo is work done for fun on trying to apply the parametric Kalman Filter (Pannekoucke et al. 2016) on the sphere for a transport equation.

Real time multi-dimensional data modeling with new observations

5 types of Kalman Filters and examples.

Data Assimilation Project with the Lorenz63 Model