Simulating Arctic Vegetation Distributions and Biogeochemical Processes in the E3SM Land Model
Authors
Benjamin N. Sulman1* (sulmanbn@ornl.gov), Fengming Yuan1, Peter Thornton1, Verity Salmon1, Amy Breen2, Jitendra Kumar1, David Graham4, Teri O’Meara1, Elizabeth Herndon1, Neslihan Tas5, Colleen M. Iversen1
Institutions
1Climate Change Science Institute, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN; 2International Arctic Research Center, University of Alaska–Fairbanks, AK; 3Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY; 4Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN; 5Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA
URLs
Abstract
A major goal of the NGEE-Arctic project is to integrate improved scientific understanding of Arctic systems into the Energy Exascale Earth System Model (E3SM) to connect scientific discoveries from observations, experiments, and detailed modeling of the Arctic into global-scale predictive models. New understanding of Arctic processes is being incorporated into hydrological, physical, biogeochemical, and vegetation process modules in the E3SM Land Model (ELM) through multiple integrative modeling efforts as part of NGEE-Arctic phase three.
Researchers have conducted spatially explicit simulations of vegetation distributions across three intensively studied field sites in the Seward Peninsula, AK. Recent ELM updates incorporated nine tundra-specific plant functional types (PFTs), several of which are new to the model, including nonvascular mosses and lichens, graminoids, forbs, and shrubs of various height classes as well as a nitrogen-fixing alder shrub. The spatially explicit vegetation simulations combine parameterization based on extensive field sampling of vegetation biomass and traits with remote sensing-based mapping of vegetation distributions to drive model projections of how vegetation carbon (C) stocks, net primary production, and nutrient cycling vary across space and time in areas with contrasting climate, topography, and soil properties.
Researchers have implemented new soil biogeochemical capabilities into ELM with the goal of better representing greenhouse gas production across complex tundra landscapes. The team has used a new, direct coupling between ELM and the reactive transport simulator PFLOTRAN to integrate a reaction network combining soil organic matter decomposition with pH dynamics, iron redox cycling, oxygen consumption, fermentation, and methanogenesis into ELM soil columns. The team then simulated coupled C, oxygen, and iron redox cycling in polygonal tundra soils at the Barrow Environmental Observatory in Utqiaġvik, AK and evaluated simulations using measured profiles of pH, C, nitrate, iron, and sulfate as well as surface methane (CH4) and carbon dioxide (CO2) fluxes from nearby polygonal tundra sites. Directly integrating subsurface geochemical interactions into ELM allows process-based simulation of variations in CO2 and CH4 production across gradients of redox state, terminal electron acceptor availability, and soil geochemical properties. Altogether, these developments translate discovery science from a range of above- and belowground observations, experiments, and detailed modeling studies within the NGEE-Arctic Project into concrete improvements in E3SM modeling capabilities.