VTechWorks staff will be away for the winter holidays starting Tuesday, December 24, 2024, through Wednesday, January 1, 2025, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!

Browsing by Author "Bonan, Gordon B."

Now showing 1 - 4 of 4
  • Thumbnail Image
    Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions
    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 (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.
  • Thumbnail Image
    The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty
    Lawrence, 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.
  • Thumbnail Image
    Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model
    Kyker-Snowman, Emily; Lombardozzi, Danica L.; Bonan, Gordon B.; Cheng, Susan J.; Dukes, Jeffrey S.; Frey, Serita D.; Jacobs, Elin M.; McNellis, Risa; Rady, Joshua M.; Smith, Nicholas G.; Thomas, R. Quinn; Wieder, William W.; Grandy, A. Stuart (Wiley, 2021-09-20)
    Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change and broadening the impact of ecological research.
  • Thumbnail Image
    Insights into mechanisms governing forest carbon response to nitrogen deposition: a model–data comparison using observed responses to nitrogen addition
    Thomas, R. Quinn; Bonan, Gordon B.; Goodale, Christine L. (Copernicus Publications, 2013-06-17)
    In many forest ecosystems, nitrogen (N) deposition enhances plant uptake of carbon dioxide, thus reducing climate warming from fossil fuel emissions. Therefore, accurately modeling how forest carbon (C) sequestration responds to N deposition is critical for understanding how future changes in N availability will influence climate. Here, we use observations of forest C response to N inputs along N deposition gradients and at five temperate forest sites with fertilization experiments to test and improve a global biogeochemical model (CLM-CN 4.0). We show that the CLM-CN plant C growth response to N deposition was smaller than observed and the modeled response to N fertilization was larger than observed. A set of modifications to the CLMCN improved the correspondence between model predictions and observational data (1) by increasing the aboveground C storage in response to historical N deposition (1850–2004) from 14 to 34 kgC per additional kgN added through deposition and (2) by decreasing the aboveground net primary productivity response to N fertilization experiments from 91 to 57 gCm⁻² yr⁻¹. Modeled growth response to N deposition was most sensitive to altering the processes that control plant N uptake and the pathways of N loss. The response to N deposition also increased with a more closed N cycle (reduced N fixation and N gas loss) and decreased when prioritizing microbial over plant uptake of soil inorganic N. The net effect of all the modifications to the CLM-CN resulted in greater retention of N deposition and a greater role of synergy between N deposition and rising atmospheric CO₂ as a mechanism governing increases in temperate forest primary production over the 20th century. Overall, testing models with both the response to gradual increases in N inputs over decades (N deposition) and N pulse additions of N over multiple years (N fertilization) allows for greater understanding of the mechanisms governing C–N coupling.