The Terrestrial Biosphere Model Farm.

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. Plain Language Summary: Comparing models is fundamental to our understanding of how the land surface responds to changes in climate. However, these comparisons are challenging to conduct, requiring the organization of multiple, decentralized teams throughout the world. We explored centralizing these models on a single supercomputing system. The models were all run the same way. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) the centralized system takes a lot of burden off individual teams; (b) running models the same way helps to identify differences in how the world is represented in the models; and (c) the system allows us to run many model experiments relatively quickly. The challenges are: (a) lots of models require lots of data storage and transfer needs; (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. Another system, called PEcAn, which has a lot of tools that can help overcome these challenges, can potentially be used in future work. Key Points: We ran nine terrestrial biosphere models centralized on a common computing frameworkThe Farm allows multiple MIP experiments to be run relatively quickly and uniformlyChallenges included technological demand, model versioning, and interpretation of results [ABSTRACT FROM AUTHOR]