Scaling Knowledge of Arctic Tundra Processes from Field Studies and Fine-Scale Models to an Earth System Model

Authors

Peter Thornton¹* (thorntonpe@ornl.gov), Colleen Iversen¹, Stan Wullschleger¹, Charles Abolt², Scott Painter¹, Ethan Coon¹, Yu Zhang², Rutuja Chitra-Tarak², Katrina Bennett², Benjamin Sulman¹, Fengming Yuan¹, Verity Salmon¹, Amy Breen³, Alistair Rogers⁴, Jitendra Kumar¹, William Riley⁵, Elizabeth Herndon¹, Teri O’Meara¹

Institutions

¹Climate Change Science Institute, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN; ²Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM; ³International Arctic Research Center, University of Alaska–Fairbanks, AK; ⁴Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY; ⁵Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA

URLs

• https://ngee-arctic.ornl.gov/

Abstract

The overarching objective for the NGEE-Arctic project is to deliver an improved predictive understanding of Arctic tundra processes at the scale of a high-resolution Earth System Model (ESM) gridcell. To achieve that goal, researchers have identified six Integrated Modeling (IM) efforts, each of which results in improved prediction capability implemented within the DOE’s Energy Exascale Earth System Model (E3SM). During phase three of NGEE-Arctic, researchers are synthesizing observations, experimentation, and fine-scale modeling results to arrive at new ELM parameterizations suitable for a high-resolution ESM gridcell. The product of each IM effort is an updated code module that extends the default capability of the E3SM Land Model (ELM). Researchers are currently targeting a 1 km × 1 km ELM gridcell size for this work, which is the most highly resolved land grid that is currently planned for continental-to-global scale simulations with E3SM. The six IM efforts focus on improved representations of the following important drivers of energy-water-carbon-biogeochemistry interactions in tundra landscapes: (1) fractional inundated area; (2) hillslope processes; (3) snow-terrain-vegetation interactions; (4) tundra-specific plant functional types; (5) dynamic biogeography; and (6) biogeochemistry in variably saturated soils. Researchers are making extensive use of the existing multilevel hierarchical subgrid capability of ELM to capture new knowledge about variability at scales finer than the 1 km grid, and the team is putting in place strategic extensions of that subgrid capability as needed to represent Arctic tundra ecosystems. The results for each IM effort is shown, demonstrating how observations, experimentation, and fine-scale modeling are producing improved performance within ELM compared to a baseline implementation without Arctic-relevant parameterizations.