Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions.

Clicks: 225
ID: 74284
2019
Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and-the newly developed-5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.
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wieder2019beyondglobal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wieder, William R;Lawrence, David M;Fisher, Rosie A;Bonan, Gordon B;Cheng, Susan J;Goodale, Christine L;Grandy, A Stuart;Koven, Charles D;Lombardozzi, Danica L;Oleson, Keith W;Thomas, R Quinn;
Journal global biogeochemical cycles
Year 2019
DOI 10.1029/2018GB006141
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