Progress and Accomplishments

Reduced Arctic Tundra Productivity Linked with Landform and Climate Change Interactions

Scientists working on the NGEE Arctic project provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity, using newly developed decade time-scale remote

California’s Governor Jerry Brown Learns About Climate Change Science in Nome

NGEE Arctic scientists from the University of Alaska Fairbanks and Lawrence Berkeley National Lab gave an overland tour of the Seward Peninsula to California’s Governor Jerry Brown to share hands-on climate change research in the Arctic.

Metadata and NGEE Arctic search tool metrics

View metrics about the NGEE Arctic metadata records and data downloads.

PEcAn integration of dvm-dos-tem for uncertainty quantification and variance decomposition

We successfully integrated the Dynamic Vegetation, Dynamic Organic Soil, Terrestrial Ecosystem Model (DVM-DOS-TEM, University of Alaska Fairbanks) into the PEcAn framework to enable formal model uncertainty quantification (UQ), parameterization, and data-

Multi-sensor visible, spectral, and thermal Unmanned Aerial System (UAS) flights in Nome

We conducted our first NGEE-Arctic deployment of the multi-instrument Osprey heavy-lift octocopter at the three Seward Peninsula sites where we collected high-resolution visible imagery for structure from motion (SfM) 3-D plant and terrain surface heights

Soil warming decreases microbial functional diversity in the Arctic Tundra

Soil warming decreases microbial functional diversity in the Arctic Tundra

Trait-based modeling for the Arctic

Database survey of key traits for improved modeling of Arctic vegetation

UAS Lidar and photogrammetry survey at Teller site, Alaska.

Successfully acquired LiDAR and photogrammetry data at centimeter resolution of the NGEE-Arctic Teller research site using an Unmanned Aerial System (UAS)

Modeling ground temperature dynamics across the Seward Peninsula

Data assimilation of the historical temperature observations is completed.

Coupled land surface-subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in an Arctic tundra ecosystem

We develop and test a joint deterministic–stochastic inversion approach that can take advantage of time-lapse electrical resistivity and other data.