Browsing by Author "Lawrence, David M."
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- Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model AssumptionsWieder, 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 (American Geophysical Union, 2019-10-28)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 (CO2) 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 CO2 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 CO2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2 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.
- The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing UncertaintyLawrence, David M.; Fisher, Rosie A.; Koven, Charles D.; Oleson, Keith W.; Swenson, Sean C.; Bonan, Gordon B.; Collier, Nathan; Ghimire, Bardan; van Kampenhout, Leo; Kennedy, Daniel; Kluzek, Erik; Lawrence, Peter J.; Li, Fang; Li, Hongyi; Lombardozzi, Danica L.; Riley, William J.; Sacks, William J.; Shi, Mingjie; Vertenstein, Mariana; Wieder, William R.; Xu, Chonggang; Ali, Ashehad A.; Badger, Andrew M.; Bisht, Gautam; van den Broeke, Michiel; Brunke, Michael A.; Burns, Sean P.; Buzan, Jonathan; Clark, Martyn; Craig, Anthony; Dahlin, Kyla; Drewniak, Beth; Fisher, Joshua B.; Flanner, Mark; Fox, Andrew M.; Gentine, Pierre; Hoffman, Forrest; Keppel-Aleks, Gretchen; Knox, Ryan; Kumar, Sanjiv; Lenaerts, Jan; Leung, L. Ruby; Lipscomb, William H.; Lu, Yaqiong; Pandey, Ashutosh; Pelletier, Jon D.; Perket, Justin; Randerson, James T.; Ricciuto, Daniel M.; Sanderson, Benjamin M.; Slater, Andrew; Subin, Zachary M.; Tang, Jinyun; Thomas, R. Quinn; Martin, Maria Val; Zeng, Xubin (American Geophysical Union, 2019-10-19)The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.