The terrestrial biosphere model farm

Fisher, Joshua B.; Sikka, Munish; Block, Gary L.; Schwalm, Christopher R.; Parazoo, Nicholas C.; Kolus, Hannah R.; Sok, Malen; Wang, Audrey; Gagne‐Landmann, Anna; Lawal, Shakirudeen; Guillaume, Alexandre; Poletti, Alyssa; Schaefer, Kevin M.; Masri, Bassil; Levy, Peter E. ORCID: https://orcid.org/0000-0002-8505-1901; Wei, Yaxing; Dietze, Michael C.; Huntzinger, Deborah N.. 2022 The terrestrial biosphere model farm. Journal of Advances in Modeling Earth Systems, 14 (2), e2021MS002676. 16, pp. https://doi.org/10.1029/2021MS002676

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Abstract/Summary

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2021MS002676
UKCEH and CEH Sections/Science Areas:	Atmospheric Chemistry and Effects (Science Area 2017-)
ISSN:	1942-2466
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	terrestrial biosphere model, land surface model, vegetation model, ecosystem model, Earth System Model, ecoinformatic model intercomparison project, PEcAn
NORA Subject Terms:	Ecology and Environment
Date made live:	22 Mar 2022 17:17 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/532299

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