Ensemble Kalman Filter Tutorial

Yan Zhan and Patricia M Gregg

The Ensemble Kalman Filter Tutorial is a Python-based Jupyter Notebook, which has been orginally designed for CIDER 2019 Workshop. It presents a data assimilation framework using the Ensemble Kalman Filter (EnKF) approach to combine geodetic data with geodynamic models to investigate volcanic unrest. Although the code is based on examples in volcanic deformation, the code can be easily applied to other disciplines. Click here to preview the tutorial.

Please cite:

• Zhan and Gregg, 2022, Ensemble Kalman Filter Tutorial, DOI: 10.5281/zenodo.8475

Other references:

1. Zhan, Y., & Gregg, P. M. (2017). Data assimilation strategies for volcano geodesy. Journal of Volcanology and Geothermal Research, 344(Supplement C), 13–25. https://doi.org/10.1016/j.jvolgeores.2017.02.015

2. Gregg, P. M., and J. C. Pettijohn (2016), A multi-data stream assimilation framework for the assessment of volcanic unrest, Journal of Volcanology and Geothermal Research, 309, 63-77, https://doi.org/10.1016/j.jvolgeores.2015.11.008.

(References are available in the folder: /ref)

Full Changelog: https://github.com/geoyanzhan3/EnKF_tutorial/commits/v1.0.0