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Evaluation of the New CNDV Option of the Community Land Model: Effects of Dynamic Vegetation and Interactive Nitrogen on CLM4 Means and Variability

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  • 1 Department of Earth and Atmospheric Sciences, and Purdue Climate Change Research Center, Purdue University, West Lafayette, Indiana
  • | 2 National Center for Atmospheric Research, Boulder, Colorado
  • | 3 Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee
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Abstract

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon–nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen (N) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen–carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger “regulator” of variability compared to the other configurations. Discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate–vegetation interactions.

Supplemental information related to this paper is available at the Journals Online Website.

Current affiliation: Manila Observatory, Quezon City, Philippines.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: C. Kendra Gotangco Castillo, Manila Observatory, P.O. Box 122, UP Post Office, Diliman, Quezon City 1101, Philippines. E-mail: kgotangco@observatory.ph

This article is included in the CESM1 Special Collection.

Abstract

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon–nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen (N) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen–carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger “regulator” of variability compared to the other configurations. Discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate–vegetation interactions.

Supplemental information related to this paper is available at the Journals Online Website.

Current affiliation: Manila Observatory, Quezon City, Philippines.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: C. Kendra Gotangco Castillo, Manila Observatory, P.O. Box 122, UP Post Office, Diliman, Quezon City 1101, Philippines. E-mail: kgotangco@observatory.ph

This article is included in the CESM1 Special Collection.

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