Coincident Above- and Below-ground Autonomous Monitoring to Quantify Co-variability in Permafrost, Soil and Vegetation Properties in Arctic Tundra: Supporting Data

• Main Authors: Dafflon, Baptiste, Oktem, Rusen, Peterson, John, Ulrich, Craig, Tran, Anh, Romanovsky, Vladimir, Hubbard, Susan
• Language: unknown
• Published: 2022
• Subjects: 54 Environmental Sciences; Arctic; Barrow; Nome; north slope; permafrost; Seward Peninsula; Tundra; Alaska
• Online Access: http://www.osti.gov/servlets/purl/1355348; https://www.osti.gov/biblio/1355348; https://doi.org/10.5440/1355348

These data are provided in support of an NGEE Arctic publication (Dafflon et al., 2017) available at doi:10.1002/2016JG003724 The dataset (221 *.csv data files) contains measurements obtained through 1) electrical resistivity tomography (ERT) to monitor soil properties, 2) pole-mounted optical cameras to monitor vegetation dynamics, and 3) point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness and soil dielectric permittivity at a study site in the Barrow Environmental Observatory (BEO) in 2013 and 2014. The BEO is located within the Arctic coastal region, about 6 km from the ocean shore and the village of Barrow, AK. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy?s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).