Articles | Volume 5, issue 2
Geosci. Model Dev., 5, 471–498, 2012
https://doi.org/10.5194/gmd-5-471-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 5, 471–498, 2012
https://doi.org/10.5194/gmd-5-471-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
20 Apr 2012
Development and technical paper
| 20 Apr 2012
Addressing the impact of environmental uncertainty in plankton model calibration with a dedicated software system: the Marine Model Optimization Testbed (MarMOT 1.1 alpha)
J. C. P. Hemmings and P. G. Challenor
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Cited
19 citations as recorded by crossref.
- Editorial: The publication of geoscientific model developments v1.0 10.5194/gmd-6-1233-2013
- Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing U. Löptien & H. Dietze 10.5194/bg-16-1865-2019
- Variations in the elemental ratio of organic matter in the central Baltic Sea: Part II – Sensitivities of annual mass flux estimates to model parameter variations M. Kreus & M. Schartau 10.1016/j.csr.2015.02.004
- Climate change impacts on southern Ross Sea phytoplankton composition, productivity, and export D. Kaufman et al. 10.1002/2016JC012514
- Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling M. Schartau et al. 10.5194/bg-14-1647-2017
- A general framework for aquatic biogeochemical models J. Bruggeman & K. Bolding 10.1016/j.envsoft.2014.04.002
- Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem U. Löptien & H. Dietze 10.1002/2017GB005690
- When is a biogeochemical model too complex? Objective model reduction and selection for North Atlantic time-series sites B. Ward et al. 10.1016/j.pocean.2013.06.002
- Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. 10.5194/bg-15-73-2018
- Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1) J. Hemmings et al. 10.5194/gmd-8-697-2015
- MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies A. Yool et al. 10.5194/gmd-6-1767-2013
- A perturbed biogeochemistry model ensemble evaluated against in situ and satellite observations P. Anugerahanti et al. 10.5194/bg-15-6685-2018
- Slow science: the value of long ocean biogeochemistry records S. Henson 10.1098/rsta.2013.0334
- Inferred support for disturbance‐recovery hypothesis of N orth A tlantic phytoplankton blooms M. Smith et al. 10.1002/2015JC011080
- Enhanced global optimization methods applied to complex fisheries stock assessment models D. Penas et al. 10.1016/j.asoc.2019.01.012
- Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks? U. Löptien & H. Dietze 10.5194/os-11-573-2015
- The assimilation of satellite‐derived data into a one‐dimensional lower trophic level marine ecosystem model Y. Xiao & M. Friedrichs 10.1002/2013JC009433
- Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0) V. Sauerland et al. 10.5194/gmd-11-1181-2018
- Enhancing Ocean Biogeochemical Models With Phytoplankton Variable Composition P. Anugerahanti et al. 10.3389/fmars.2021.675428
19 citations as recorded by crossref.
- Editorial: The publication of geoscientific model developments v1.0 10.5194/gmd-6-1233-2013
- Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing U. Löptien & H. Dietze 10.5194/bg-16-1865-2019
- Variations in the elemental ratio of organic matter in the central Baltic Sea: Part II – Sensitivities of annual mass flux estimates to model parameter variations M. Kreus & M. Schartau 10.1016/j.csr.2015.02.004
- Climate change impacts on southern Ross Sea phytoplankton composition, productivity, and export D. Kaufman et al. 10.1002/2016JC012514
- Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling M. Schartau et al. 10.5194/bg-14-1647-2017
- A general framework for aquatic biogeochemical models J. Bruggeman & K. Bolding 10.1016/j.envsoft.2014.04.002
- Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem U. Löptien & H. Dietze 10.1002/2017GB005690
- When is a biogeochemical model too complex? Objective model reduction and selection for North Atlantic time-series sites B. Ward et al. 10.1016/j.pocean.2013.06.002
- Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. 10.5194/bg-15-73-2018
- Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1) J. Hemmings et al. 10.5194/gmd-8-697-2015
- MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies A. Yool et al. 10.5194/gmd-6-1767-2013
- A perturbed biogeochemistry model ensemble evaluated against in situ and satellite observations P. Anugerahanti et al. 10.5194/bg-15-6685-2018
- Slow science: the value of long ocean biogeochemistry records S. Henson 10.1098/rsta.2013.0334
- Inferred support for disturbance‐recovery hypothesis of N orth A tlantic phytoplankton blooms M. Smith et al. 10.1002/2015JC011080
- Enhanced global optimization methods applied to complex fisheries stock assessment models D. Penas et al. 10.1016/j.asoc.2019.01.012
- Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks? U. Löptien & H. Dietze 10.5194/os-11-573-2015
- The assimilation of satellite‐derived data into a one‐dimensional lower trophic level marine ecosystem model Y. Xiao & M. Friedrichs 10.1002/2013JC009433
- Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0) V. Sauerland et al. 10.5194/gmd-11-1181-2018
- Enhancing Ocean Biogeochemical Models With Phytoplankton Variable Composition P. Anugerahanti et al. 10.3389/fmars.2021.675428
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