Implementation of various ensemble Kalman Filter data assimilation methods in Julia
Author Alexander-Barth
25 Stars
Updated Last
2 Years Ago
Started In
November 2016


Build Status Build Status Windows

documentation latest

The packages implements various data assimilation methods:

  • (Extended) Kalman Filter
  • Incremental 4D-Var
  • Ensemble Square Root Filter (EnSRF)
  • Ensemble Square Root Filter with serial processing of the observations (serialEnSRF)
  • Ensemble Transform Kalman Filter (ETKF)
  • Ensemble Transform Kalman Filter (EAKF)
  • Singular Evolutive Interpolated Kalman filter (SEIK)
  • Error-subspace Transform Kalman Filter (ESTKF)
  • Ensemble Kalman Filter (EnKF)

The Julia code is ported from the Matlab/Octave code generated in the frame of the Sangoma project (


An example of using to package is available as a jupyter-notebook.


Most of the algorithms are described in the review article:

Sanita Vetra-Carvalho, Peter Jan van Leeuwen, Lars Nerger, Alexander Barth, M. Umer Altaf, Pierre Brasseur, Paul Kirchgessner, and Jean-Marie Beckers. State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems. Tellus A: Dynamic Meteorology and Oceanography, 70(1):1445364, 2018. doi: 10.1080/16000870.2018.1445364.

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