Influences and Interactions of Inundation, Peat, and Snow on Active Layer Thickness: Modeling Archive

• Main Authors: Atchley, Adam, Coon, Ethan, Painter, Scott, Harp, Dylan, Wilson, Cathy
• Language: unknown
• Published: 2021
• Subjects: 54 Environmental Sciences; Arctic; Active layer thickness; Barrow; Nome; north slope; permafrost; Seward Peninsula; Tundra; Alaska
• Online Access: http://www.osti.gov/servlets/purl/1240734; https://www.osti.gov/biblio/1240734; https://doi.org/10.5440/1240734

The Advanced Terrestrial Simulator was used to simulate thermal hydrological conditions across varied environmental conditions for an ensemble of 1D models of Arctic permafrost. The thickness of organic soil is varied from 2 to 40cm, snow depth is varied from approximately 0 to 1.2 meters, water table depth was varied from -51cm below the soil surface to 31 cm above the soil surface. A total of 15,960 ensemble members are included. Data produced includes the third and fourth simulation year: active layer thickness, time of deepest thaw depth, temperature of the unfrozen soil, and unfrozen liquid saturation, for each ensemble member. Input files used to run the ensemble are also included. File formats in the data package: .py, .h5, .xml, .exo, .txt, and .pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) 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).