Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-3319-2021
© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
Technical note
| 
16 Jun 2021
Technical note |
| 16 Jun 2021
| 16 Jun 2021
Technical Note: Sequential ensemble data assimilation in convergent and divergent systems
Related authors
Cited articles
Aksoy, A., Zhang, F., and Nielsen-Gammon, J. W.: Ensemble-based simultaneous
state and parameter estimation in a two-dimensional sea-breeze model, Mon.
Weather Rev., 134, 2951–2970, https://doi.org/10.1175/MWR3224.1, 2006. a
Anderson, J. L. and Anderson, S. L.: A Monte Carlo implementation of the
nonlinear filtering problem to produce ensemble assimilations and forecasts,
Mon. Weather Rev., 127, 2741–2758, https://doi.org/10.1175/1520-0493(1999)127<2741:AMCIOT>2.0.CO;2, 1999. a
Bauser, H. H., Jaumann, S., Berg, D., and Roth, K.: EnKF with closed-eye
period – towards a consistent aggregation of information in soil hydrology,
Hydrol. Earth Syst. Sci., 20, 4999–5014, https://doi.org/10.5194/hess-20-4999-2016, 2016. a
Bauser, H. H., Berg, D., Klein, O., and Roth, K.: Inflation method for ensemble Kalman filter in soil hydrology, Hydrol. Earth Syst. Sci., 22,
4921–4934, https://doi.org/10.5194/hess-22-4921-2018, 2018. a, b
Berg, D.: Particle filters for nonlinear data assimilation, PhD thesis, Ruperto-Carola University Heidelberg, Heidelberg, Germany, 2018. a
