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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Observations of high-time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties

Abstract. Aerosols play a critical role in the Arctic's radiative balance, influencing solar radiation and cloud formation. Limited observations in the central Arctic leave gaps in understanding aerosol dynamics year-round, affecting model predictions of climate-relevant aerosol properties. Here, we present the first annual high-time-resolution observations of submicron aerosol chemical composition in the central Arctic during the Arctic Ocean 2018 (AO2018) and the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expeditions. Seasonal variations in the aerosol mass concentrations and chemical composition in the central Arctic were found to be driven by typical Arctic seasonal regimes and resemble those of pan-Arctic land-based stations. Organic aerosols dominated the pristine summer, while anthropogenic sulfate prevailed in autumn and spring under haze conditions. Ammonium, which impacts aerosol acidity, was consistently less abundant, relative to sulfate, in the central Arctic compared to lower latitudes of the Arctic. Cyclonic (storm) activity was found to have a significant influence on aerosol variability by enhancing emissions from local sources and the transport of remote aerosol. Local wind-generated particles contributed up to 80 % (20 %) of the cloud condensation nuclei population in autumn (spring). While the analysis presented herein provides the current central Arctic aerosol baseline, which will serve to improve climate model predictions in the region, it also underscores the importance of integrating short-timescale processes, such as seasonal wind-driven aerosol sources from blowing snow and open leads/ocean in model simulations. This is particularly important, given the decline in mid-latitude anthropogenic emissions and the increase in local ones.

Heutte, Benjamin (ORCID:0000000173727460)↗
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022

From April 3 through April 6 of 2022, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Snow-on data was collected around two NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27 and Kougarok mm 64. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. This survey was conducted during expected peak snow cover at the end of the winter on the Seward Peninsula, and can be paired with data collected in 2021 during the snow-off campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021" (Singhania et al., 2023) (NGA270). This data package contains LiDAR point clouds (.las), Digital Elevation Models (.tif), and shapefiles of the .las tiling system (.shp). A project report detailing data collection details, GNSS stations and GNSS corrections, and processing steps is also included. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska

A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Geothermal Energy and Resilience in Arctic Countries

The eight Arctic countries - Iceland, Canada, Denmark (Greenland and the Faroe Islands) Norway, Sweden, Finland, Russia, and the United States (Alaska) - have diverse energy systems, but can be split into two distinct groups based on energy characteristics. The first group includes systems in Europe (Finland, Norway, Sweden, and Iceland), which are heavily grid-connected. The second group includes the United States (Alaska), Canada, Russia, and Greenland, which have grid-connected energy systems in their more densely populated southern regions, but are also defined by the prevalence of remote microgrids. Energy sources for heat and power vary across grid-connected communities in the Arctic nations. The primary energy source for remote communities, on the other hand, is almost exclusively diesel. This is true for both heat and power. Despite these and other key distinctions, Arctic countries share many commonalities with regard to their energy systems. One is a fundamental need for heat. Heat and electric energy are linked in most communities - remote, rural, and urban - and those linked systems are increasingly vulnerable to disruptions. Several of the Arctic countries use baseload renewable energy resources for heat and power. Iceland uses geothermal and hydroelectric; Canada, the United States, Sweden, Norway, and Finland use hydroelectric. Utilization of baseload renewable energy resources on-site for combined heat and power appears to enhance the resilience of communities in Arctic countries with high penetration of those resources. On the other hand, reliance on diesel by remote communities in other Arctic countries may be amplifying vulnerabilities. Although geothermal energy is currently used in all eight Arctic countries, resources are poorly mapped, and details can be difficult to come by. Despite this, geothermal energy provides heat and sometimes electricity at both utility scales and at the microgrid scale. Geothermal electricity is produced in Iceland, Russia, and the United States (Alaska). Direct use of geothermal heat is used in Iceland, Russia, United States, Canada, and Norway. Geo-exchange is used in Sweden, Finland, Norway, Canada, and the United States. In this paper, we reframe geothermal heat and power systems as integrated energy systems, asking the question: are integrated geothermal energy systems - where available and economic - resilient solutions for communities in Arctic countries? We identify resilience attributes of integrated geothermal energy systems, with a focus on microgrids and small-scale applications. Based on the high-level, qualitative analysis presented in this paper, the answer appears to be yes. Further work should prioritize refining our understanding of geothermal resources in Arctic countries, because development of the most economic geothermal resources in Arctic countries has the potential to enhance the energy resilience of its residents, whether in a grid-connected or remote off-grid context.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022

Sun-induced chlorophyll fluorescence (SIF) is emitted from the chlorophyll antenna complexes during the light harvesting and photophysical reactions of photosynthesis. It is directly coupled with and therefore can be used to estimate photosynthetic electron transport and CO2 assimilation. SIF, when observed at the ecosystem level, provides information about ecosystem functions that complements the net ecosystem exchange (NEE) of CO2, CH4, water vapor, and sensible heat. NEE observations have been conducted with the eddy covariance (EC) approach at the NGEE Arctic Council, Alaska site for years. However, concurrent SIF observations have not been available. In June 2022, we installed the fluorescence automated measurement equipment (FAME) at the NGEE Arctic Council site. The zip file contains 3,187 *.dat files that can be opened with a text editor or in *.csv.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large emissions of CO2 and CH4 due to active-layer warming in Arctic tundra: Supporting Data

Climate warming may accelerate decomposition of Arctic soil carbon, but few controlled experiments have manipulated the entire active layer. To determine surface-atmosphere fluxes of carbon dioxide and methane under anticipated end-of-century warming, we used heating rods to warm soil (by 3.8 °C) to the depth of permafrost in polygonal tundra over two growing seasons at the Barrow Environmental Observatory in Utqiaġvik (formerly Barrow), Alaska. This data product includes supporting data for the companion paper entitled "Large emissions of CO2 and CH4 due to active-layer warming in Arctic tundra", published in Nature Communications by Torn et al. This data package contains seven data files in csv format with corresponding data dictionaries and file-level metadata, describing vegetation biomass dry weight ("Utqiagvik_Vegetation_Biomass_2014.csv"), radiocarbon measurements of respired carbon dioxide ("Utqiagvik_Radiocarbon_2015_2016.csv"), surface-atmosphere fluxes of carbon dioxide and methane and associated soil temperature ("Utqiagvik_Fluxes_Temperature_2015_2016.csv"), and soil temperature measurements averaged every 15-min and 1-hr for 2015 and 2016 ("Utqiagvik_Temperature_15min_2015.csv", "Utqiagvik_Temperature_15min_2016.csv", "Utqiagvik_Temperature_1hr_2015.csv", "Utqiagvik_Temperature_1hr_2016.csv"). There are no specific software requirements to use these data. UIC Science Native Corporation facilitated our scientific research on the Barrow Environmental Observatory, which is Iñupiat land.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml 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).

Air temperature↗
DOE OSTI2025

Elucidating Processes Controlling Arctic Atmospheric Aerosol Sources, Aging, and Mixing States (Final Report)

Atmospheric aerosols play critical roles in the Earth’s energy budget, directly by scattering or absorbing solar and terrestrial radiation and indirectly by serving as seeds (nuclei) for cloud droplet and ice crystal formation and by depositing on snow and ice surface, thereby changing the surface albedo. These effects are dependent on aerosol particle size and chemical composition and impact the hydrological cycle as well. This project provided single-particle size and chemical composition measurements across the entire annual cycle in the high Arctic and in the Alaskan Arctic during fall – winter, addressing the most significant gaps in Arctic aerosol observational data. These needs were based on recent rapid sea ice loss across the entire Arctic, as well as the major annual delays in sea ice freeze-up during fall in the Chukchi Sea and increased wintertime sea ice fracturing in the Beaufort Sea, both off the North Slope of Alaska. Two DOE Atmospheric Radiation Measurement (ARM) field campaigns were conducted for atmospheric aerosol sampling. The Aerosols during the Polar Utqiagvik Night (APUN – ‘snow on ground’ in Iñupiaq) ARM field campaign at Utqagivik, Alaska was conducted from Oct. 28 – Dec. 22, 2018. Aerosol sizing instrumentation and a single-particle mass spectrometer were successfully deployed for size-resolved number concentration measurements and measurements of individual particle size and chemical composition, respectively. These results show the influence of locally-produced sea spray aerosol, with high cloud-forming potential, due to delayed sea ice freeze-up in the fall. During the 2019‐2020 international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, daily atmospheric aerosol particles were collected aboard the German icebreaker Polarstern in the Central Arctic from Nov. 2019 – Oct. 2020. Sea salt aerosol and marine organics were observed year-round during MOSAiC with varying morphologies and sources. These findings are important because most Arctic models do not include a sea spray aerosol source, despite this source increasing with declining sea ice extent. In addition to collecting new samples and data, this project also conducted further analysis of previously collected single-particle chemical composition measurements within the North Slope of Alaska oil fields and at Utqiaġvik, AK, during Aug. – Sep. 2015 and 2016 field campaigns. This work resulted in the discovery of chemical reactions of oil field combustion emissions occurring within fog droplets across the North Slope of Alaska and forming secondary aerosol, showing the impact of Arctic oil field emissions beyond black carbon aerosol and greenhouse gases. In addition, the distribution of chemical species across the aerosol population within the oil fields was quantified, using these data and a previously development framework. We also presented the first ambient evidence of the collision of two atmospheric particles resulting in formation of an organic-coated ammonium sulfate particle of marine origin, which has implications for cloud formation with declining sea ice extent. Overall, this project has elucidated connections between seawater biogeochemistry, resource extraction activities, atmospheric composition, clouds, and the energy budget of the Arctic region. The results of this project are expected to improve weather and sea ice forecasting for security and development in the Arctic and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data

Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. This data package includes one *.csv data file and one *.pdf user guide. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

NGEE Arctic Soil Micro-warming Experiment Temperature Profiles, Council Road Mile Marker 71, Seward Peninsula, Alaska, 2017-2019

The reported soil temperature profile measurements (24 locations - 2 probes with 5 and 6 thermistors, respectively - Fig. 1 and Fig. 2) were initiated as part of a soil micro-warming experiment at the Council Road Mile Marker 71 Site (CN_MM71) in September 2017. From 2017 through August 2019, these were measurements of ambient pre-treatment plot conditions. This tussock tundra site (with underlying permafrost) experiences annual frost heaving that causes a vertical movement of the ground surface, hence causing some of the upper most temperature thermistors to be at surface level or above ground and recorded therefore air temperatures near the surface and not below ground soil temperature (see section on Quality Assurance). After August 2019, these measurements ended in preparation for transitioning to the experimental warming of individual plots. The reported temperature data are nominally 3-hour averages of measurements made at varying frequencies (3-hour maximum) with frequencies that depended upon power (solar) availability to operate the sensors (see section in documentation on Methods). The number of values and the standard deviation for each 3-hour average (where appropriate) are also provided. These measurements are located near the NGEE-Arctic CO2 and CH4 eddy covariance tower at the Council Road Site (US-NGC: NGEE Arctic Council, https://ameriflux.lbl.gov/sites/siteinfo/US-NGC#overview) and auxiliary data at https://doi.org/10.5440/1526749. This dataset contains four *.csv files and one *.pdf file. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Riley et al. (2021) “Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate” (Riley et al., 2021). The dataset contains “ecosys” model outputs reported in Riley et al. (2021) that examines the role of non-growing season (NGS) nutrient dynamics on 21st century vegetation composition. The study highlighted the importance of these nutrient dynamics on the emergent plant functional type distributions, focusing on their role in shrub expansion. The study showed that ignoring NGS nutrient dynamics led to a dramatic under-prediction of shrub expansion by year 2100, motivating the need to include these processes in Earth System Models. Included are modeled net primary production (NPP) and nitrogen (N) uptake for two scenarios: (1) baseline and (2) no NGS N uptake. The output is provided (1) at 25 km resolution across the North American tundra; (2) for years 2012 through 2100; and (3) PFT-specific. Dataset contains 20 NetCDF files in a zip file and one pdf.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Concentration-Discharge Relationships in the Six Largest Arctic Rivers, 2003-2019

This dataset provides the results of the analysis of the relationship of dissolved analyte concentrations and river discharges in the six largest Arctic rivers across the global panarctic region (see Figure 1 in documentation file *.pdf). Long-term measurements of dissolved analyte concentrations and river discharge have been collected for each of the Kolyma, Lena, Mackenzie, Ob, Yenisey, and Yukon rivers by the Arctic Great Rivers Observatory (ArcticGRO) project from ~2003-present (Shiklomanov, 2021). The relationship of dissolved analyte concentrations and discharges in each river was characterized by statistical analysis of the slope of the log(concentration) vs log(discharge) (b), the coefficient of variation ratio (CVc/CVq), the 2.5% and 97.5% confidence intervals of b, and assigning a chemostatic, flushing, diluting, or non-systematic behavior category according to Koger (2018). The summary of these analyses for all six rivers is provided in one .csv file. The concentrations of 20 dissolved analytes and discharge measurement data for the individual Kolyma, Lena, Mackenzie, Ob, Yenisey, and Yukon rivers are also provided with this dataset. There are seven *.csv files; one for each river plus the statistical summary. These public ArcticGRO data at "https://www.arcticgreatrivers.org" (Shiklomanov, 2021) were downloaded on Feb 13, 2020, but each river has different measurement dates over the sampling and analysis period. The ArcticGRO metadata document (*.pdf) downloaded on Feb 13, 2020 is also included in this dataset. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Hyperspectral remote sensing-based plant community map for region around NGEE-Arctic intensive research watersheds at Seward Peninsula, Alaska, 2017-2019

Using airborne hyperspectral remote sensing data from NASA Airborne Visible-Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) platforms in a region near NGEE-Arctic intensive watersheds at Seward peninsula of Alaska, high resolution (5m) maps of plant community distribution were developed and included in this data collected. AVIRIS-NG data collected over 2017-2019 period were used to develop deep neural networks, trained using vegetation plot observations collected at NGEE-Arctic watersheds at Kougarok, Council and Teller. A hierarchical vegetation classification scheme consisting of six classes at Level I, and 16 classes at Level II contained in two .txt files were used to developed the plant community maps for the region. Two geospatial raster data files (.tif) at both thematic levels are shared in this data collection. Data files in this collection use Alaska Albers Equal Area projection. Readme files available in three formats (*.html, *.md, *.pdf) and one *.png visualization map.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Shirley et al. (2022) “Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed". [DOI].The dataset contains outputs from the global sensitivity analysis (GSA) of the “ecosys” model as reported in Shirley et al. (2022). The study showed that discontinuous permafrost environments are characterized by complex feedback loops and strong spatial heterogeneity which is created by variability in near-surface hydrology and soil properties. Additionally, the study demonstrated that missing representation of sub-grid heterogeneity in terrestrial ecosystem models can lead to biased estimates of the high-latitude carbon budget. Included in this dataset are the factor values for each run in the GSA and the model outputs used in this study. Included are two *.csv data files and one *.pdf.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

NGEE Arctic Soil Pit and Core Inventory for Samples Collected Between 2016-2019: Locations, Sampling Characteristics, Collection, and Contacts, Seward Peninsula, Alaska, USA

This dataset includes associated information about individual pit and core samples (e.g., location, contact, date, data collected) sampled between 2016 and 2019 from NGEE Arctic sites at Teller (MM 27 and MM47), Kougarok (MM47 and MM56, Hillslope, and vegetation plot areas), and Council (MM71). The inventory is qualitative and excludes those datasets on soil pit cores that included time-series information. The package includes one each *.csv data file, *.kml and *.pdf. All quantitative data is available in the related datasets https://doi.org/10.5440/1417652, https://doi.org/10.5440/1423892, https://doi.org/10.5440/1342956, https://doi.org/10.5440/1854940, https://doi.org/10.5440/1544760, https://doi.org/10.5440/1346200, and https://doi.org/10.5440/1856042. The goal of this dataset is to help modelers understand when, where, and what data was collected with respect to physical soil properties on the Seward Peninsula, AK, USA over the course of NGEE Arctic’s campaigns in the region from 2016-2019. 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).

54 ENVIRONMENTAL SCIENCES↗