Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
Volume 11, issue 3
Geosci. Model Dev., 11, 1181–1198, 2018
https://doi.org/10.5194/gmd-11-1181-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 11, 1181–1198, 2018
https://doi.org/10.5194/gmd-11-1181-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 29 Mar 2018

Methods for assessment of models | 29 Mar 2018

Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

Volkmar Sauerland et al.

Related authors

Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0)
Iris Kriest, Volkmar Sauerland, Samar Khatiwala, Anand Srivastav, and Andreas Oschlies
Geosci. Model Dev., 10, 127–154, https://doi.org/10.5194/gmd-10-127-2017,https://doi.org/10.5194/gmd-10-127-2017, 2017
Short summary

Related subject area

Biogeosciences
An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020,https://doi.org/10.5194/gmd-13-4459-2020, 2020
Short summary
Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)
Emily Kyker-Snowman, William R. Wieder, Serita D. Frey, and A. Stuart Grandy
Geosci. Model Dev., 13, 4413–4434, https://doi.org/10.5194/gmd-13-4413-2020,https://doi.org/10.5194/gmd-13-4413-2020, 2020
Short summary
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev., 13, 4091–4106, https://doi.org/10.5194/gmd-13-4091-2020,https://doi.org/10.5194/gmd-13-4091-2020, 2020
Short summary
FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020,https://doi.org/10.5194/gmd-13-4041-2020, 2020
Short summary
The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage
Femke Lutz, Stephen Del Grosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 13, 3905–3923, https://doi.org/10.5194/gmd-13-3905-2020,https://doi.org/10.5194/gmd-13-3905-2020, 2020
Short summary

Cited articles

Anderson, T.: Plankton functional type modelling: running before we can walk?, J. Plankton Res., 27, 1073–1081, https://doi.org/10.1093/plankt/fbi076, 2005.
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015.
Barlow, R. E., Bartholomew, D. J., Bremner, J. M., and Brunk, H. D.: Statistical Inference under Order Restrictions, Theory and Application of Isotonic Regression, Wiley Series in Probability and Mathematical Statistics, John Wiley & Sons, London, https://doi.org/10.1111/j.1467-9574.1973.tb00228.x, 1972.
Boyd, S. and Vandenberghe, L.: Convex optimization, Cambridge University Press, 2004.
Brovkin, V., Petoukhov, V., Claussen, M., Bauer, E., Archer, D., and Jaeger, C.: Geoengineering climate by stratospheric sulfur injections: Earth system vulnerability to technological failure, Climatic Change, 92, 243–259, https://doi.org/10.1007/s10584-008-9490-1, 2009.
Publications Copernicus
Download
Short summary
We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
We present a concept to prove that a parametric model is well calibrated, i.e., that changes of...
Citation