Articles | Volume 9, issue 1
https://doi.org/10.5194/gmd-9-59-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-59-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
15 Jan 2016
Methods for assessment of models |
| 15 Jan 2016
The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, PL1 3DH, UK
M. Butenschön
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, PL1 3DH, UK
J. I. Allen
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, PL1 3DH, UK
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25 citations as recorded by crossref.
- Using feature-based verification methods to explore the spatial and temporal characteristics of the 2019 chlorophyll-<i>a</i> bloom season in a model of the European Northwest Shelf M. Mittermaier et al. 10.5194/os-17-1527-2021
- A numerical study of the benthic–pelagic coupling in a shallow shelf sea (Gulf of Trieste) G. Mussap & M. Zavatarelli 10.1016/j.rsma.2016.11.002
- Factors Regulating the Relationship Between Total and Size-Fractionated Chlorophyll-a in Coastal Waters of the Red Sea R. Brewin et al. 10.3389/fmicb.2019.01964
- Numerical Modeling of Long-Term Biogeochemical Processes and Its Application to Sedimentary Bed Formation in Tokyo Bay M. Amunugama & J. Sasaki 10.3390/w10050572
- Skill assessment of models relevant for the implementation of ecosystem-based fisheries management A. Kempf et al. 10.1016/j.fishres.2023.106845
- Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry E. Terzić et al. 10.5194/bg-16-2527-2019
- Observing and modelling phytoplankton community structure in the North Sea D. Ford et al. 10.5194/bg-14-1419-2017
- A system of metrics for the assessment and improvement of aquatic ecosystem models M. Hipsey et al. 10.1016/j.envsoft.2020.104697
- Ocean carbon from space: Current status and priorities for the next decade R. Brewin et al. 10.1016/j.earscirev.2023.104386
- Future digital twins: emulating a highly complex marine biogeochemical model with machine learning to predict hypoxia J. Skákala et al. 10.3389/fmars.2023.1058837
- Uncertainty in Ocean-Color Estimates of Chlorophyll for Phytoplankton Groups R. Brewin et al. 10.3389/fmars.2017.00104
- Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations S. Ciavatta et al. 10.1002/2017JC013490
- Improved Representation of Underwater Light Field and Its Impact on Ecosystem Dynamics: A Study in the North Sea J. Skákala et al. 10.1029/2020JC016122
- The Assimilation of Phytoplankton Functional Types for Operational Forecasting in the Northwest European Shelf J. Skákala et al. 10.1029/2018JC014153
- Reproducible and relocatable regional ocean modelling: fundamentals and practices J. Polton et al. 10.5194/gmd-16-1481-2023
- A management oriented 1-D ecosystem model: Implementation in the Gulf of Trieste (Adriatic Sea) G. Mussap et al. 10.1016/j.rsma.2016.03.015
- Determining Atlantic Ocean province contrasts and variations T. Smyth et al. 10.1016/j.pocean.2016.12.004
- Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll B. Jönsson et al. 10.5194/gmd-16-4639-2023
- Capturing the big picture of Mediterranean marine biodiversity with an end-to-end model of climate and fishing impacts F. Moullec et al. 10.1016/j.pocean.2019.102179
- Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing G. Maniaci et al. 10.3389/fmars.2022.1035399
- BGC-val: a model- and grid-independent Python toolkit to evaluate marine biogeochemical models L. de Mora et al. 10.5194/gmd-11-4215-2018
- Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf‐sea ecosystem S. Ciavatta et al. 10.1002/2015JC011496
- Global Chlorophyll a Concentrations of Phytoplankton Functional Types With Detailed Uncertainty Assessment Using Multisensor Ocean Color and Sea Surface Temperature Satellite Products H. Xi et al. 10.1029/2020JC017127
- Modelling size-fractionated primary production in the Atlantic Ocean from remote sensing R. Brewin et al. 10.1016/j.pocean.2017.02.002
- Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean V. Martínez-Vicente et al. 10.3389/fmars.2017.00378
Saved (preprint)
Latest update: 23 Nov 2024
Short summary
To use models to inform policy or to forecast the impact of climate change, the model must first be shown to be a valid representation of the ecosystem. Here we show an novel method to validate a marine model using its ability to represent ecosystem function. These relationships are the community structure, the carbon to chlorophyll ratio and the stoichiometric balance of the ecosystem. These methods are powerful, valid over large spatial scales and independent of the circulation model.
To use models to inform policy or to forecast the impact of climate change, the model must first...
