24 citations as recorded by crossref.

1. A comparison of different versions of the SEEK Filter for assimilation of biogeochemical data in numerical models of marine ecosystem dynamics M. Butenschön & M. Zavatarelli https://doi.org/10.1016/j.ocemod.2012.06.003
2. Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models M. Gharamti & I. Hoteit https://doi.org/10.1016/j.jhydrol.2013.12.004
3. Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation C. Raick et al. https://doi.org/10.1016/j.jmarsys.2005.06.006
4. M3A system (2000–2005) – operation and maintenance G. Petihakis et al. https://doi.org/10.5194/os-3-117-2007
5. Incremental four-dimensional variational data assimilation of positive-definite oceanic variables using a logarithm transformation H. Song et al. https://doi.org/10.1016/j.ocemod.2012.06.001
6. Towards a Multi‐Platform Assimilative System for North Sea Biogeochemistry J. Skákala et al. https://doi.org/10.1029/2020JC016649
7. Improving the quantification of terrestrial ecosystem carbon dynamics over the United States using an adjoint method Q. Zhu & Q. Zhuang https://doi.org/10.1890/ES13-00058.1
8. Data assimilation of depth-distributed satellite chlorophyll-α in two Mediterranean contrasting sites S. Kalaroni et al. https://doi.org/10.1016/j.jmarsys.2016.03.018
9. Enhanced flood forecasting through ensemble data assimilation and joint state-parameter estimation M. Ziliani et al. https://doi.org/10.1016/j.jhydrol.2019.123924
10. Sequential data assimilation in an upwelling influenced estuary R. Torres et al. https://doi.org/10.1016/j.jmarsys.2006.02.001
11. Assimilation of SeaWiFS ocean chlorophyll data into a three-dimensional global ocean model W. Gregg https://doi.org/10.1016/j.jmarsys.2006.02.015
12. Skill assessment in ocean biological data assimilation W. Gregg et al. https://doi.org/10.1016/j.jmarsys.2008.05.006
13. Nutrient transports in the Baltic Sea – results from a 30-year physical–biogeochemical reanalysis Y. Liu et al. https://doi.org/10.5194/bg-14-2113-2017
14. Application of SeaWIFS- and AVHRR-derived data for mesoscale and regional validation of a 3-D high-resolution physical–biological model of the Gulf of St. Lawrence (Canada) V. Le Fouest et al. https://doi.org/10.1016/j.jmarsys.2005.11.008
15. A hybrid ensemble-OI Kalman filter for efficient data assimilation into a 3-D biogeochemical model of the Mediterranean K. Tsiaras et al. https://doi.org/10.1007/s10236-017-1050-7
16. Eastern Mediterranean biogeochemical flux model – Simulations of the pelagic ecosystem G. Petihakis et al. https://doi.org/10.5194/os-5-29-2009
17. EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters J. Bruggeman et al. https://doi.org/10.5194/gmd-17-5619-2024
18. A data assimilation tool for the Pagasitikos Gulf ecosystem dynamics: Methods and benefits G. Korres et al. https://doi.org/10.1016/j.jmarsys.2011.11.004
19. Assimilating Ferry Box data into the Aegean Sea model G. Korres et al. https://doi.org/10.1016/j.jmarsys.2014.03.013
20. Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling S. Ciavatta et al. https://doi.org/10.1016/j.pocean.2014.06.002
21. Data assimilation in a coupled physical–biogeochemical model of the California Current System using an incremental lognormal 4-dimensional variational approach: Part 1—Model formulation and biological data assimilation twin experiments H. Song et al. https://doi.org/10.1016/j.ocemod.2016.04.001
22. Assimilation of ocean colour data into a Biogeochemical Flux Model of the Eastern Mediterranean Sea G. Triantafyllou et al. https://doi.org/10.5194/os-3-397-2007
23. Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model D. Ford et al. https://doi.org/10.5194/os-8-751-2012
24. Emerging ocean observations for interdisciplinary data assimilation systems T. Dickey https://doi.org/10.1016/S0924-7963(03)00011-3