An important challenge for Earth System Models (ESMs) is to represent land surface and subsurface processes and their complex interactions in a changing climate. This is true for all regions of the world, but it is especially important for Arctic ecosystems which are projected to warm at a rate twice that of the global average by the end of the 21st century. The Next-Generation Ecosystem Experiments (NGEE Arctic) project seeks to improve the representation of tundra ecosystems in ESMs through a coordinated series of model-inspired investigations conducted in landscapes near Utqiaġvik (formerly Barrow) and Nome, Alaska.

Our goal is to support the DOE’s Biological and Environmental Research (BER) mission to advance a robust predictive understanding of Earth’s climate and environmental systems by delivering a process-rich ecosystem model, extending from bedrock to the top of the vegetative canopy and atmospheric interface, in which the evolution of Arctic ecosystems in a changing climate can be modeled at the scale of a high-resolution ESM grid cell.

This goal is aligned with the High-Latitude Scientific Grand Challenge in the Climate and Environmental Sciences Division (CESD) Strategic Plan. In Phase 1 (2012 to 2014), we tested and applied a multiscale measurement and modeling framework in a coastal tundra ecosystem on the North Slope of Alaska. This region was chosen to represent a site underlain by cold, continuous permafrost at the northern extent of an ecological and climatic gradient in Alaska. In Phase 2 (2015 to 2019), three additional field sites were established on the Seward Peninsula in western Alaska, which, compared to our research site on the North Slope, are characterized by their proximity to the boreal-tundra transition zone; warmer, discontinuous permafrost; and well-defined watersheds.

Focus on understanding

Integrated field, laboratory, and modeling tasks allowed our team to focus on understanding

  1. the effect of landscape structure and organization on the storage and flux of C, water, and nutrients
  2. edaphic and geochemical mechanisms responsible for variable CO2 and CH4 fluxes across a range of permafrost conditions
  3. variation in plant functional traits across space and time, and in response to changing environmental conditions and resulting consequences for ecosystem processes
  4. controls on shrub distribution and associated biogeochemical and biophysical climate feedbacks
  5. changes in snow processes and surface and groundwater hydrology expected with warming in the 21st century

A major outcome of our Phase 1 and 2 research was an integrated set of in situ and remotely sensed observations that quantify the covariation of hydro-thermal, ecosystem, vegetation dynamics, and biogeochemical function. These efforts provided unique datasets for model parameterization and benchmarking. Knowledge on topics ranging from watershed hydrology to plant physiology is now being incorporated into DOE’s Energy Exascale Earth System Model (E3SM).

In Phase 3 (2020 to 2022), we propose to continue our research at sites on the North Slope and in western Alaska, while also adding a cross-cutting component on disturbance. We will use field campaigns, modeling, and data synthesis to target improvements in simulating disturbance-related processes (e.g., wildfire and abrupt permafrost thaw) and connections to dynamic vegetation (e.g., shrubs) that are missing from or poorly represented in ESMs. Our vision in Phase 3 strengthens the connection between process studies in Arctic ecosystems and high-resolution landscape modeling and scaling strategies developed in Phases 1 and 2. Deliverables will consist of six new source-code modules within the E3SM Github code repository, each evaluated against multiscale measurements and process-based models. We also outline a close-out plan for critical components of the project. This plan includes closure of field sites, removal of instruments and infrastructure, shipment of resources back to home institutions, environmental stewardship as lands are returned to native communities from which we obtained permits, and timely transfer of datasets to the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE). Safety, national and international collaboration, and a commitment to project management continue to be key underpinnings of our model-inspired research in the Arctic.