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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Doubling of U.S. Population Exposure to Climate Extremes by 2050

We quantify historical and projected trends in the population exposure to climate extremes as measured by the United States National Center for Environmental Information Climate Extremes Index (CEI). Based on the analyses of the historical observations, we find that the U.S. has already experienced a rise in the occurrence of aggregated extremes in recent decades, consistent with the climate response to historical increases in radiative forcing. Additionally, we find that exposure can be expected to intensify under the Representative Concentration Pathway 8.5, with all counties permanently exceeding the baseline variability in the occurrence of extreme hot days, warm nights, and drought conditions by 2050. As a result, every county in the U.S. is projected to permanently exceed the historical CEI variability (as measured by one standard deviation during the 1981–2005 period). Based on the current population distribution, this unprecedented change implies a yearly exposure to extreme conditions for one in every three people. We find that the increasing trend in exposure to the aggregated extremes is already detectable over much of the U.S., and particularly in the central and eastern U.S. The high correspondence between the pattern of trends in our simulations and observations increases confidence in the projected amplification of population exposure to unprecedented combinations of extreme climate conditions, should greenhouse gas concentrations continue to escalate along their current trajectory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data from: "Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range"

This data package contains data that were used for analysis in “Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range”, by Moyes et al. 2013. All data collection and field research were completed on Niwot Ridge, Colorado, USA.This data package contains nine comma-separated-values (.csv) files, one text (.txt) file, and two zipped seedling folders that were used for leaf area analysis. One zipped folder contains 468 .jpg photographs of seedlings, and the second contains 468 corresponding Image J-processed .jpg images that include silhouette leaf area values. .csv and .txt files can be opened using any compatible simple text-editor software such as TextEdit (Mac) and Notepad (Windows); .csv’s can also be opened using R and Microsoft Excel. Image files can be opened using Preview (Mac) and Photos (Windows). In addition, there are a total of 31 Microsoft Excel files: three .xlsx files, and 28 raw Li-Cor output .xls files. This data user’s guide is available in .pdf format, and can be opened using Adobe Acrobat Reader, or any other compatible file viewing software. Geospatial data showing field site locations are also included in the archive for use and reference. There are two geospatial formats in this archive: ESRI shapefiles (.shp) and keyhole markup-language (.kml) files. Both file types contain bounding box information, with the former being polygons, and the latter containing corner coordinates for each site. ESRI shapefiles can be opened using any geospatial software compatible with the file type (such as ESRI’s ArcGIS suite and QGIS), and .kml files are compatible with Google Earth and Google Maps.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Continued changes in climate are projected to alter the geographic distributions of plant species, in part by affecting where individuals can establish from seed. We tested the hypothesis that warming promotes uphill redistribution of subalpine tree populations by reducing cold limitation at high elevation and enhancing drought stress at low elevation. We seeded limber pine (Pinus flexilis) into plots with combinations of infrared heating and water addition treatments, at sites positioned in lower subalpine forest, the treeline ecotone, and alpine tundra. In 2010, first-year seedlings were assessed for physiological performance and survival over the snow-free growing season. Seedlings emerged in midsummer, about 5–8 weeks after snowmelt. Low temperature was not observed to limit seedling photosynthesis or respiration between emergence and October, and thus experimental warming did not appear to reduce cold limitation at high elevation. Instead, gas exchange and water potential from all sites indicated a prevailing effect of summer moisture stress on photosynthesis and carbon balance. Infrared heaters raised soil growing degree days (base 5 °C, p < 0.001) and August–September mean soil temperature (p < 0.001). Despite marked differences in vegetation cover and meteorological conditions across sites, volumetric soil moisture content (θ) at 5–10 cm below 0.16 and 0.08 m^3 m^(−3) consistently corresponded with moderate and severe indications of drought stress in midday stem water potential, stomatal conductance, photosynthesis, and respiration. Seedling survival was greater in watered plots than in heated plots (p = 0.01), and negatively related to soil growing degree days and duration of exposure to θ < 0.08 m^3 m^(−3) in a stepwise linear regression model (p < 0.0001). We concluded that seasonal moisture stress and high soil surface temperature imposed a strong limitation to limber pine seedling establishment across a broad elevation gradient, including at treeline, and that these limitations are likely to be enhanced by further climate warming.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Maintenance log:Amended file name error in Data User's Guide May 19 2022

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Throughfall-Reduction Drying Effects on Soil Moisture and Soil Temperature at 30-Minute Intervals Four Lowland Panamanian Forests

Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Chronic throughfall exclusion also suppressed soil moisture across the four forests, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (Cusack et al. 2023). Datasets included: Datasets here include .csv and .xls files for volumetric soil moisture (volume/volume) and soil temperature (°C). Data were taken at 30-minute intervals at 5cm and 20cm depths using permanent probes and data loggers (see methods). Data presented are from 2018-2019. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2019-2021

Time lapse camera images from Kougarok mile marker (MM) 64 and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2019 to August 2021. Thirty three Wingscape Timelapse Pro cameras were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from were recorded at hourly intervals from 11 AM to 2 PM, continuously for 25 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. 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

Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey

The warming climate is likely to increase hurricane-associated extreme rainfall and lead to sea-level rise (SLR). Thus, how the floods induced by intense hurricanes respond to these potential changes is of great concern. This study investigates the future warmer climate impacts on hurricane-induced extreme rainfall, and—more importantly—the subsequent compound flooding at the watershed scale (from an event-based analysis perspective). To this goal, a modeling framework is designed based on the Distributed Hydrology Soil Vegetation Model (DHSVM), the Two-Dimensional fvand the Regional Community Earth System Model (R-CESM). The framework was applied to Hurricane Harvey (2017) at the Clear Creek watershed (a coastal watershed in the southern Houston) as a case study. The results show that the projected maximum rainfall totals over the watershed would be exacerbated by 17.7 % and 49.7 % in the 2050s and 2090s (respectively) under Representative Concentration Pathway 8.5 (RCP 8.5). This means a 16.1 % increase in Harvey rainfall over the watershed per degree Celsius increase in Mean Surface Temperature over the Gulf of Mexico region (18°~31° N, 77°~98° W). Meanwhile, the increases in maximum inundation extent would be 11.0 % (2050s) and 19.5 % (2090s). Furthermore, considerable increases in maximum inundation depth and duration in regions along the middle and downstream of Clear Creek (and also those around Clear Lake) are expected. The projected SLR will have little effect on the maximum inundation depth and extent if storm surge changes are not taken into account; meanwhile, it will influence the inundation duration at downstream locations. In conclusion, this modeling framework can be also applied at other coastal watersheds to evaluate the projected climate change impacts on the compound flooding induced by extreme climate events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate warming enhances microbial network complexity and stability

Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. Furthermore, these results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.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

Subsidence Measurements at the Teller 27 Field Site, Seward Peninsula, Alaska, 2021

In September 2021, differential GPS (dGPS) points were collected in areas of visual subsidence in the Teller watershed near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway on the Seward Peninsula of Alaska. This study aimed to understand how structural permafrost loss is affecting meter-scale ground elevation. As ice thaws, heaving and slumping of the landscape creates new microtopographical features on the landscape that may alter surface hydrology and soil moisture and thus plant community composition and biogeochemical cycling. The Teller 27 field site is underlain with discontinuous permafrost, so the landscape features a variety of permafrost features. We collected ground elevations from eight subsidence areas in two forms: 1) Transects were sampled laterally through areas of ground subsidence to capture the high edges and low spots where the earth slumped. 2) The circumference of the subsidence area was sampled in order to measure the ground area affected by subsidence. These data were collected with an Emlid Reach RS2 dGPS and a base station. This dataset includes one *.csv of dGPS locations of the eight subsidence locations and one *.kml of measurement locations.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

Vegetation Warming Experiment: Environmental conditions, Utqiagvik (Barrow), Alaska, 2019

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 19 June – 25 September, 2019. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017–2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic "Vegetation Warming Experiment" data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots.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

Vegetation Warming Experiment: Environmental conditions, Utqiagvik (Barrow), Alaska, 2021

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 19 June - 17 September, 2021. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017-2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic "Vegetation Warming Experiment" data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots. 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

Vegetation Warming Experiment: Environmental Conditions, Utqiagvik (Barrow), Alaska, 2017

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 22 June - 17 September, 2017. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017-2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic Vegetation Warming Experiment data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots. 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

Vegetation Warming Experiment: Environmental Conditions, Utqiagvik (Barrow), Alaska, 2018

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 16 June - 24 September, 2018. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017-2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic "Vegetation Warming Experiment" data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots.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 OSTI2023

Co-located temperature and electrical resistivity measurements for permafrost mapping, Teller 27, Teller 47 and Kougarok 64, Seward Peninsula, Alaska, late summers of 2018, 2019, 2021, and 2022

This data set contains co-located shallow soil (0.8m below ground level) and electrical resistivity at various depth extracted from Electrical Resistivity Tomography (ERT) measurements. Data were acquired at three watersheds on the southern Seward Peninsula during the late summers of 2018, 2019, 2021, and 2022. The three watersheds are located along the Nome-Teller Highway at mile markers 27 and 47, and along Kougarok Road mile marker 64. The co-located temperature and electrical resistivity data were used to (1) map the spatial extend of near surface permafrost, and (2) for supervised classification of permafrost bodies. This dataset contains .csv, .txt, .srv files and flmd reporting format with data dictionary. Find information about the .srv files at "https://e4d-userguide.pnnl.gov/e4d_guide/elec/e4d_e4d-survey.html". 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

Radiocarbon age at Teller and Kougarok field sites, Seward Peninsula, Alaska

With extreme climate warming in the Arctic, there is increasing focus on permafrost stability and improving understanding of the impacts of thawing permafrost. Understanding the stability of carbon in Arctic permafrost supports our understanding of the global carbon cycle. Organic (plant / wood) samples were collected from varying depths and landscape features at the Teller 33, Teller 47, Teller 51, Kougarok 64, and Kougarok 86 field sites on the Seward Peninsula, Alaska in the summers of 2014, 2017, 2019, and 2021. Carbon 13 and 14 isotopes were measured to find radiocarbon age for collected samples. We also report fraction modern and delta 14C. This dataset contains a *.csv file of radiocarbon measurements and a *.kml file of measurement locations. 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).

EARTH SCIENCE > CLIMATE INDICATORS > PALEOCLIMATE ↗
DOE OSTI2023

Arctic shrub size and leaf traits, northern Alaska, summer 2017 (Version 2.0)

This data package contains leaf and size trait and environmental data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and climate gradient in northern Alaska. The trait data were collected in summer 2017 and include leaf area, specific leaf area, leaf nitrogen concentration, leaf delta 15N, leaf delta 13C, shrub height, aboveground biomass, and the ratio of root biomass to aboveground biomass. These raw data support a submitted manuscript that examines the intraspecific variations of size, leaf and root traits of shrubs across the graminoid-dominated nutrient-poor arctic tundra and reveals the environmental drivers of deciduous shrub traits in tundra ecosystems (Fraterrigo et al., submitted). Data are presented by site (n=5) and patch (shrub or sedge plot) in separate csv files. The location data are provided in the “plot coordinates” file; all other files contain the data in the file title. Detailed methods are in the submitted manuscript. A companion data package contains root trait data collected simultaneously from the same plots (Fraterrigo and Chen, 2020). See the "Related references" section for more information.2023/07/20 Update: The latest version of this dataset publication is version 2.0. The latest version of the data package was updated to correct the leaf size trait.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Black carbon-climate interactions regulate dust burdens over India revealed during COVID-19

India as a hotspot for air pollution has heavy black carbon (BC) and dust (DU) loadings. BC has been identified to significantly impact the Indian climate. However, whether BC-climate interactions regulate Indian DU during the premonsoon season is unclear. Here, using long-term Reanalysis data, we show that Indian DU is positively correlated to northern Indian BC while negatively correlated to southern Indian BC. We further identify the mechanism of BC-dust-climate interactions revealed during COVID-19. BC reduction in northern India due to lockdown decreases solar heating in the atmosphere and increases surface albedo of the Tibetan Plateau (TP), inducing a descending atmospheric motion. Colder air from the TP together with warmer southern Indian air heated by biomass burning BC results in easterly wind anomalies, which reduces dust transport from the Middle East and Sahara and local dust emissions. The premonsoon aerosol-climate interactions delay the outbreak of the subsequent Indian summer monsoon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of data uncertainty on cold season threshold-based climate indices

Climate indices are used to reduce the complex climate system and its changes to simple measures. The data basis – whether observational data or climate model data – to which the climate indices are applied, is usually subject to uncertainties. For threshold-based climate indices, the data uncertainty influences the threshold value, and, hence, the uncertainty can influence the values for the climate index. What the actual impacts of these uncertainties are on threshold-based climate indices is examined in this paper. The focus is not only on the climate model uncertainty, but also on the observational data uncertainty. The general sensitivity of each of the chosen climate indices to arbitrary changes in the threshold is studied. This shows a higher sensitivity of indices assessing extremes (ice days, heavy precipitation days) to changes in the threshold than indices that integrate a quantity over a given time interval (coldsum, consecutive days). For assessing an ensemble of climate model data with respect to their ability to reproduce the index values for current climate, the reference data uncertainty is applied to the chosen threshold-based climate indices by changing their threshold value by its corresponding uncertainty. It is shown that the climate model uncertainty can be within the range of the reference data uncertainty. When using threshold-based climate indices to assess changes in future climate periods, uncertainties should always be taken into account and ideally corrected in an appropriate way. This is especially important for indices that assess extremes.

54 ENVIRONMENTAL SCIENCES↗