NGEE Arctic Leaf Spectral Reflectance and Transmittance, Barrow, Alaska, 2014-2016

• Main Authors: Shawn Serbin, Wil Lieberman-Cribbin, Kim Ely, Alistair Rogers
• Format: Dataset
• Language: unknown
• Published: ESS-DIVE: Deep Insight for Earth Science Data 2019
• Subjects: Site; Overlap_Handling; Sample_Barcode; North Slope, Alaska; Sample_Date; Overlap_Matching_Type; Utqiagvik, Alaska; Collection_Units; Spectra_Type; Spectra_Name; Interpolation_Method; BNL_Barcode; BEO; Barrow Environmental Observatory; USDA_Species; White_Reference_Standard; Overlap_Removal; Spectra_Units; Spectral_Resolution; Instrument; Foreoptic; Barrow, Alaska; Reflectance_Type; leaf spectral reflectance; Wave 350; Wave 2500; Arctic; albedo; Barrow; Nome; north slope; permafrost; Seward Peninsula; Tundra; Alaska
• Online Access: https://search.dataone.org/view/ess-dive-f0861161a6bd3bf-20231109T125444193

Data were collected to characterize the leaf-level optical properties and albedo of dominant Arctic tundra species in the Barrow, AK area and to enable trait scaling. Measurements of full-spectrum (i.e. 350-2500nm) leaf spectral reflectance of Arctic plant species. Data were collected in Barrow, Alaska during the 2014-2016 period. This dataset contains 5 zipped folders, 4 csv, 4 xlsx, 1 txt, and 1 pdf files. 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).