BGC-val: a model- and grid-independent Python toolkit to evaluate marine biogeochemical modelsde Mora, L., Yool, A., Palmieri, J., Sellar, A., Kuhlbrodt, T. ORCID: https://orcid.org/0000-0003-2328-6729, Popova, E., Jones, C. and Allen, J. I. (2018) BGC-val: a model- and grid-independent Python toolkit to evaluate marine biogeochemical models. Geoscientific Model Development, 11 (10). pp. 4215-4240. ISSN 1991-9603
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.5194/gmd-11-4215-2018 Abstract/SummaryThe biogeochemical evaluation toolkit, BGC-val, is a model- and grid-independent Python toolkit that has been built to evaluate marine biogeochemical models using a simple interface. Here, we present the ideas that motivated the development of the BGC-val software framework, introduce the code structure, and show some applications of the toolkit using model results from the Fifth Climate Model Intercomparison Project (CMIP5). A brief outline of how to access and install the repository is presented in Appendix A, but the specific details on how to use the toolkit are kept in the code repository. The key ideas that directed the toolkit design were model and grid independence, front-loading analysis functions and regional masking, interruptibility, and ease of use. We present each of these goals, why they were important, and what we did to address them. We also present an outline of the code structure of the toolkit illustrated with example plots produced by the toolkit. After describing BGC-val, we use the toolkit to investigate the performance of the marine physical and biogeochemical quantities of the CMIP5 models and highlight some predictions about the future state of the marine ecosystem under a business-as-usual CO2 concentration scenario (RCP8.5).
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