48 citations as recorded by crossref.

1. Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic M. Gharamti et al. https://doi.org/10.1016/j.jmarsys.2016.12.003
2. Globally Consistent Quantitative Observations of Planktonic Ecosystems F. Lombard et al. https://doi.org/10.3389/fmars.2019.00196
3. Simulation of Observed PCBs and Pesticides in the Water Column during the North Atlantic Bloom Experiment L. Zhang et al. https://doi.org/10.1021/acs.est.5b00223
4. Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models S. Kern et al. https://doi.org/10.5194/gmd-17-621-2024
5. Data assimilation with a local Ensemble Kalman Filter applied to a three-dimensional biological model of the Middle Atlantic Bight J. Hu et al. https://doi.org/10.1016/j.jmarsys.2011.11.016
6. Phytoplankton growth formulation in marine ecosystem models: Should we take into account photo-acclimation and variable stoichiometry in oligotrophic areas? S. Ayata et al. https://doi.org/10.1016/j.jmarsys.2012.12.010
7. Framework to Extract Extreme Phytoplankton Bloom Events with Remote Sensing Datasets: A Case Study W. Lu et al. https://doi.org/10.3390/rs14153557
8. Mixed layer eddies supply nutrients to enhance the spring phytoplankton bloom I. Simoes-Sousa et al. https://doi.org/10.3389/fmars.2022.825027
9. Sustainability of corrosion-induced degradation of marine engineering structures: A bibliometric analysis based on CiteSpace and VOSviewer (1972-2026) Z. Yang et al. https://doi.org/10.1016/j.marenvres.2026.108214
10. Air-sea CO2 fluxes and cross-shelf exchange of inorganic carbon in the East China Sea from a coupled physical-biogeochemical model R. Na et al. https://doi.org/10.1016/j.scitotenv.2023.167572
11. An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas V. Yumruktepe et al. https://doi.org/10.5194/gmd-16-6875-2023
12. Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook H. Dierssen et al. https://doi.org/10.3389/fenvs.2021.649528
13. Icebergs as Unique Lagrangian Ecosystems in Polar Seas K. Smith et al. https://doi.org/10.1146/annurev-marine-121211-172317
14. The assimilation of satellite‐derived data into a one‐dimensional lower trophic level marine ecosystem model Y. Xiao & M. Friedrichs https://doi.org/10.1002/2013JC009433
15. Estimation of hyperspectral inherent optical properties from in-water radiometry: error analysis and application to in situ data E. Rehm & C. Mobley https://doi.org/10.1364/AO.52.000795
16. Assessing the utility of frequency dependent nudging for reducing biases in biogeochemical models K. Lagman et al. https://doi.org/10.1016/j.ocemod.2014.06.006
17. Nitrogen uptake and nitrification in the subarctic North Atlantic Ocean X. Peng et al. https://doi.org/10.1002/lno.10784
18. Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon M. Falls et al. https://doi.org/10.5194/gmd-15-5713-2022
19. The interactive roles of temperature, nutrients, and zooplankton grazing in controlling the winter-spring phytoplankton bloom in a temperate, coastal ecosystem, Long Island Sound J. George et al. https://doi.org/10.1002/lno.10020
20. A 50-Year Journey from Phosphate to Autonomous Underwater Vehicles M. Perry https://doi.org/10.1146/annurev-marine-010419-010945
21. Simple parameter estimation for complex models — Testing evolutionary techniques on 3-dimensional biogeochemical ocean models J. Mattern & C. Edwards https://doi.org/10.1016/j.jmarsys.2016.10.012
22. Eddy-driven subduction exports particulate organic carbon from the spring bloom M. Omand et al. https://doi.org/10.1126/science.1260062
23. Ocean biogeochemical modelling K. Fennel et al. https://doi.org/10.1038/s43586-022-00154-2
24. A Satellite-Based Lagrangian View on Phytoplankton Dynamics Y. Lehahn et al. https://doi.org/10.1146/annurev-marine-121916-063204
25. An Assessment of Vertical Carbon Flux Parameterizations Using Backscatter Data From BGC Argo B. Wang & K. Fennel https://doi.org/10.1029/2022GL101220
26. High-resolution observations of aggregate flux during a sub-polar North Atlantic spring bloom N. Briggs et al. https://doi.org/10.1016/j.dsr.2011.07.007
27. Tidal impacts on primary production in the North Sea C. Zhao et al. https://doi.org/10.5194/esd-10-287-2019
28. Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison I. Irby et al. https://doi.org/10.5194/bg-13-2011-2016
29. Model investigations of the North Atlantic spring bloom initiation A. Kuhn et al. https://doi.org/10.1016/j.pocean.2015.07.004
30. Ensemble data assimilation for ocean biogeochemical state and parameter estimation at different sites M. Gharamti et al. https://doi.org/10.1016/j.ocemod.2017.02.006
31. Using biogeochemical data assimilation to assess the relative skill of multiple ecosystem models in the Mid-Atlantic Bight: effects of increasing the complexity of the planktonic food web Y. Xiao & M. Friedrichs https://doi.org/10.5194/bg-11-3015-2014
32. Environmental Change at Deep-Sea Sponge Habitats Over the Last Half Century: A Model Hindcast Study for the Age of Anthropogenic Climate Change A. Samuelsen et al. https://doi.org/10.3389/fmars.2022.737164
33. An operational biogeochemical model of the North-East Atlantic: Model description and skill assessment T. Dabrowski et al. https://doi.org/10.1016/j.jmarsys.2013.08.001
34. Uncertainties in ocean biogeochemical simulations: Application of ensemble data assimilation to a one-dimensional model N. Mamnun et al. https://doi.org/10.3389/fmars.2022.984236
35. Sustenance of Phytoplankton in the Subpolar North Atlantic During Winter F. Karimpour et al. https://doi.org/10.1029/2017JC013639
36. Solving calibration and reanalysis challenges of ocean biogeochemical dynamics with neural schemes: a 1D vertical model case-study J. Littaye et al. https://doi.org/10.5194/bg-23-6879-2026
37. Nutrient consumption and chain tuning in diatoms exposed to storm-like turbulence G. Dell’Aquila et al. https://doi.org/10.1038/s41598-017-02084-6
38. Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. https://doi.org/10.5194/bg-15-73-2018
39. Autonomous data describe North Atlantic spring bloom K. Fennel et al. https://doi.org/10.1029/2011EO500002
40. Spring plankton dynamics in the Eastern Bering Sea, 1971–2050: Mechanisms of interannual variability diagnosed with a numerical model N. Banas et al. https://doi.org/10.1002/2015JC011449
41. Evaluating ecosystem model complexity for the northwest North Atlantic through surrogate-based optimization A. Kuhn & K. Fennel https://doi.org/10.1016/j.ocemod.2019.101437
42. A multi-method autonomous assessment of primary productivity and export efficiency in the springtime North Atlantic N. Briggs et al. https://doi.org/10.5194/bg-15-4515-2018
43. Assessing the value of biogeochemical Argo profiles versus ocean color observations for biogeochemical model optimization in the Gulf of Mexico B. Wang et al. https://doi.org/10.5194/bg-17-4059-2020
44. 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
45. Simulating sediment–water exchange of nutrients and oxygen: A comparative assessment of models against mesocosm observations R. Wilson et al. https://doi.org/10.1016/j.csr.2013.05.003
46. ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic V. Yumruktepe et al. https://doi.org/10.5194/gmd-15-3901-2022
47. Experiments in optimizing simulations of the subsurface chlorophyll maximum in the South China Sea S. Wang et al. https://doi.org/10.1016/j.jmarsys.2015.11.003
48. Optimal control and system limitation in a Southern Ocean ecosystem model J. Melbourne-Thomas et al. https://doi.org/10.1016/j.dsr2.2013.02.017