Articles | Volume 21, issue 1
https://doi.org/10.5194/angeo-21-399-2003
© Author(s) 2003. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/angeo-21-399-2003
© Author(s) 2003. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
An Ensemble Kalman Filter with a complex marine ecosystem model: hindcasting phytoplankton in the Cretan Sea
J. I. Allen
Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1 3DH, UK
M. Eknes
Nansen Environmental and Remote Sensing Centre, Edvard Griegsvei 3a, N-5037 Solheimsviken, Norway
G. Evensen
Nansen Environmental and Remote Sensing Centre, Edvard Griegsvei 3a, N-5037 Solheimsviken, Norway
Viewed
Total article views: 1,618 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
854 | 708 | 56 | 1,618 | 74 | 57 |
- HTML: 854
- PDF: 708
- XML: 56
- Total: 1,618
- BibTeX: 74
- EndNote: 57
Cited
52 citations as recorded by crossref.
- Building a Better Forecast: Reformulating the Ensemble Kalman Filter for Improved Applications to Volcano Deformation J. Albright & P. Gregg 10.1029/2022EA002522
- 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 10.1016/j.ocemod.2012.06.003
- Sequential data assimilation in an upwelling influenced estuary R. Torres et al. 10.1016/j.jmarsys.2006.02.001
- A multi-data stream assimilation framework for the assessment of volcanic unrest P. Gregg & J. Pettijohn 10.1016/j.jvolgeores.2015.11.008
- Efficient Characterization of Uncertain Model Parameters with a Reduced-Order Ensemble Kalman Filter B. Lin & D. McLaughlin 10.1137/130910415
- Ecoregions in the Mediterranean Sea Through the Reanalysis of Phytoplankton Functional Types and Carbon Fluxes S. Ciavatta et al. 10.1029/2019JC015128
- Challenges and opportunities for integrating lake ecosystem modelling approaches W. Mooij et al. 10.1007/s10452-010-9339-3
- A model-independent data assimilation (MIDA) module and its applications in ecology X. Huang et al. 10.5194/gmd-14-5217-2021
- EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters J. Bruggeman et al. 10.5194/gmd-17-5619-2024
- Data assimilation strategies for volcano geodesy Y. Zhan & P. Gregg 10.1016/j.jvolgeores.2017.02.015
- Assimilation of ocean colour data into a Biogeochemical Flux Model of the Eastern Mediterranean Sea G. Triantafyllou et al. 10.5194/os-3-397-2007
- Emerging ocean observations for interdisciplinary data assimilation systems T. Dickey 10.1016/S0924-7963(03)00011-3
- Towards a Multi‐Platform Assimilative System for North Sea Biogeochemistry J. Skákala et al. 10.1029/2020JC016649
- Can ocean color assimilation improve biogeochemical hindcasts in shelf seas? S. Ciavatta et al. 10.1029/2011JC007219
- Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations S. Ciavatta et al. 10.1002/2017JC013490
- Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling M. Schartau et al. 10.5194/bg-14-1647-2017
- Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf‐sea ecosystem S. Ciavatta et al. 10.1002/2015JC011496
- On the stability and the uniform propagation of chaos properties of Ensemble Kalman–Bucy filters P. Del Moral & J. Tugaut 10.1214/17-AAP1317
- Variable update strategy to improve water quality forecast accuracy in multivariate data assimilation using the ensemble Kalman filter S. Park et al. 10.1016/j.watres.2020.115711
- Calibration of a coupled biological–physical model for prediction in a coastal inlet M. Guarracino et al. 10.1016/j.csr.2011.07.012
- A hybrid ensemble-OI Kalman filter for efficient data assimilation into a 3-D biogeochemical model of the Mediterranean K. Tsiaras et al. 10.1007/s10236-017-1050-7
- Data assimilation with a local Ensemble Kalman Filter applied to a three-dimensional biological model of the Middle Atlantic Bight J. Hu et al. 10.1016/j.jmarsys.2011.11.016
- A theoretical analysis of one-dimensional discrete generation ensemble Kalman particle filters P. Del Moral & E. Horton 10.1214/22-AAP1843
- Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment E. Simon & L. Bertino 10.5194/os-5-495-2009
- A data assimilation tool for the Pagasitikos Gulf ecosystem dynamics: Methods and benefits G. Korres et al. 10.1016/j.jmarsys.2011.11.004
- Improving Weather Forecasts for Sailing Events Using a Combination of a Numerical Forecast Model and Machine Learning Postprocessing S. Beimel et al. 10.3390/app14072950
- Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model D. Ford et al. 10.5194/os-8-751-2012
- A Novel Data Sampling Driven Kalman Filter Is Designed by Combining the Characteristic Sampling of UKF and the Random Sampling of EnKF T. Cui et al. 10.3390/s22041343
- Nutrient transports in the Baltic Sea – results from a 30-year physical–biogeochemical reanalysis Y. Liu et al. 10.5194/bg-14-2113-2017
- Dynamics and enzymatic degradation of exopolymer particles under increasing concentrations of silver ions and nanoparticles during a marine mesocosm experiment L. Scheidemann et al. 10.3389/fmars.2022.955488
- A sequential Monte Carlo approach for marine ecological prediction M. Dowd 10.1002/env.780
- State and parameter update of a hydrodynamic-phytoplankton model using ensemble Kalman filter J. Huang et al. 10.1016/j.ecolmodel.2013.04.022
- On the mathematical theory of ensemble (linear-Gaussian) Kalman–Bucy filtering A. Bishop & P. Del Moral 10.1007/s00498-023-00357-2
- Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling S. Ciavatta et al. 10.1016/j.pocean.2014.06.002
- Adaptive forecasting of phytoplankton communities T. Page et al. 10.1016/j.watres.2018.01.046
- Estimating time-dependent parameters for a biological ocean model using an emulator approach J. Mattern et al. 10.1016/j.jmarsys.2012.01.015
- Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea G. Triantafyllou et al. 10.1016/j.jmarsys.2012.12.006
- Operational monitoring and forecasting for marine environmental applications in the Aegean Sea K. Nittis et al. 10.1016/j.envsoft.2004.04.023
- Forecasting dryland vegetation condition months in advance through satellite data assimilation S. Tian et al. 10.1038/s41467-019-08403-x
- Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis R. Baatz et al. 10.1029/2020RG000715
- Modelling the hydrodynamics and ecosystem of the North-West European continental shelf for operational oceanography J. Siddorn et al. 10.1016/j.jmarsys.2006.01.018
- Skill assessment in ocean biological data assimilation W. Gregg et al. 10.1016/j.jmarsys.2008.05.006
- Sequential Assimilation of Volcanic Monitoring Data to Quantify Eruption Potential: Application to Kerinci Volcano, Sumatra Y. Zhan et al. 10.3389/feart.2017.00108
- Bayesian statistical data assimilation for ecosystem models using Markov Chain Monte Carlo M. Dowd 10.1016/j.jmarsys.2007.01.007
- Marine ecosystem models for earth systems applications: The MarQUEST experience J. Allen et al. 10.1016/j.jmarsys.2009.12.017
- Development of an Aerosol Retrieval Method: Description and Preliminary Tests G. Carrió et al. 10.1175/2008JAMC1729.1
- Eastern Mediterranean biogeochemical flux model – Simulations of the pelagic ecosystem G. Petihakis et al. 10.5194/os-5-29-2009
- Sequential data assimilation applied to a physical–biological model for the Bermuda Atlantic time series station J. Mattern et al. 10.1016/j.jmarsys.2009.08.004
- Assessment of a regional physical–biogeochemical stochastic ocean model. Part 1: Ensemble generation V. Vervatis et al. 10.1016/j.ocemod.2021.101781
- Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter L. Nerger & W. Gregg 10.1016/j.jmarsys.2007.09.007
- An Ensemble Kalman Filter Data Assimilation Method for the Sea Surface Temperature in the China Seas: Implementation and Simulation Experiments Z. Li et al. 10.1088/1742-6596/2486/1/012028
- Experimental and modeling study on Cr(VI) transfer from soil into surface runoff C. Tan et al. 10.1007/s00477-015-1161-y
Latest update: 23 Nov 2024
Special issue