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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The fall, recovery, classification, and initial characterization of the Hamburg, Michigan H4 chondrite

Abstract The Hamburg meteorite fell on January 16, 2018, near Hamburg, Michigan, after a fireball event widely observed in the U.S. Midwest and in Ontario, Canada. Several fragments fell onto frozen surfaces of lakes and, thanks to weather radar data, were recovered days after the fall. The studied rock fragments show no or little signs of terrestrial weathering. Here, we present the initial results from an international consortium study to describe the fall, characterize the meteorite, and probe the collision history of Hamburg. About 1 kg of recovered meteorites was initially reported. Petrology, mineral chemistry, trace element and organic chemistry, and O and Cr isotopic compositions are characteristic of H4 chondrites. Cosmic ray exposure ages based on cosmogenic 3 He, 21 Ne, and 38 Ar are ~12 Ma, and roughly agree with each other. Noble gas data as well as the cosmogenic 10 Be concentration point to a small 40–60 cm diameter meteoroid. An 40 Ar‐ 39 Ar age of 4532 ± 24 Ma indicates no major impact event occurring later in its evolutionary history, consistent with data of other H4 chondrites. Microanalyses of phosphates with LA‐ICPMS give an average Pb‐Pb age of 4549 ± 36 Ma. This is in good agreement with the average SIMS Pb‐Pb phosphate age of 4535.3 ± 9.5 Ma and U‐Pb Concordia age of 4535 ± 10 Ma. The weighted average age of 4541.6 ± 9.5 Ma reflects the metamorphic phosphate crystallization age after parent body formation in the early solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Impact of pellet preparation on reflectance measurements of ammonium sulfate by single-angle reflectance spectroscopy

The optical constants, n and k, are required to model the reflection, refraction and transmission of light at the first surface interface of a material, as well as its propagation through the material; here n corresponds to the real component and k the imaginary component of the refractive index. Several different spectroscopic methods have been used to determine the n and k values for different materials, including single angle reflectance spectroscopy and ellipsometry. The single-angle reflectance method quantitatively records the specular reflectance R(v) from a plane parallel face of the material and uses the Kramers-Kronig transform to extract the n and k values. For most compounds, however, it is difficult to obtain a single crystal or high-quality window of sufficient planarity and of the appropriate dimensions (several mm) to make the measurement. For this reason, we further investigate the use of pressed pellets of neat powdered substances to measure optical constants of these substances using the single-angle reflectance method. We have found that surface roughness can significantly influence the measured quantitative reflectance spectrum R(v) and, consequently, the derived n and k parameters. A collaborative study between Defence Research and Development Canada (DRDC) - Valcartier Research Center and Pacific Northwest National Laboratory (PNNL) has been carried out using different pellets of neat ammonium sulfate [(NH4)2SO4] to show how parameters such as the relative fraction of particle sizes for the component powder along with the grinding process of the pure compound all can affect the reflectance spectrum used to derive the optical constants. All pressed pellets were characterized by single-angle reflectance spectroscopy.

Diaz, Emmanuela↗
DOE OSTI2025

Cold-air outbreaks in the continental US: Connections with stratospheric variations

Mid-latitude Northern Hemisphere extreme cold events continue to occur despite overall winter warming trends. These events have been linked to weakened stratospheric polar vortex (SPV) states. In this study, we analyze both the upper and lower polar stratosphere for links to extreme winter cold and snow in the continental US, finding two SPV variations of interest. The first features an upper-level vortex displaced toward western Canada and linked to northwestern US severe winter weather. The second features a weakened upper-level vortex displaced toward the North Atlantic and linked to central-eastern US severe winter weather. Both variations feature lower-level stretched vortices and stratospheric wave reflection. Since 2015, a northwestward shift in severe winter weather across the US is concurrent with an increase in the frequency of the westward-focused variation relative to the eastward-focused variation and a shift to more negative phases of the El Niño–Southern Oscillation.

Science & Technology - Other Topics↗
DOE OSTI2021

Rapid retreat of the southwestern Laurentide Ice Sheet during the Bølling-Allerød interval

The timing of Laurentide Ice Sheet deglaciation along its southwestern margin controlled the evolution of large glacial lakes and has implications for human migration into the Americas. Accurate reconstruction of the ice sheet’s retreat also constrains glacial isostatic adjustment models and is important for understanding ice-sheet sensitivity to climate forcing. Despite its significance, retreat of the southwestern Laurentide Ice Sheet (SWLIS) is poorly constrained by minimum-limiting 14 C data. We present 26 new cosmogenic 10 Be exposure ages spanning the western Interior Plains, Canada. Using a Bayesian framework, we combine these data with geomorphic mapping, 10 Be, and high-quality minimum-limiting 14 C ages to provide an updated chronology. This dataset presents an internally consistent retreat record and indicates that the initial detachment of the SWLIS from its convergence with the Cordilleran Ice Sheet began by ca. 15.0 ka, concurrent with or slightly prior to the onset of the Bølling-Allerød interval (14.7–12.9 ka) and retreated >1200 km to its Younger Dryas (YD) position in ~2500 yr. Ice-sheet stabilization at the Cree Lake Moraine facilitated a meltwater drainage route to the Arctic from glacial Lake Agassiz within the YD, but not necessarily at the beginning. Our record of deglaciation and new YD constraints demonstrate deglaciation of the Interior Plains was ~60% faster than suggested by minimum 14 C constraints alone. In conclusion, numerical modeling of this rapid retreat estimates a loss of ~3.7 m of sea-level equivalent from the SWLIS during the Bølling-Allerød interval.

58 GEOSCIENCES↗
DOE OSTI2021

C-FOG: Life of Coastal Fog

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp . An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

58 GEOSCIENCES↗
DOE OSTI2021

Examining the Impacts of Great Lakes Temperature Perturbations on Simulated Precipitation in the Northeastern United States

Most inland water bodies are not resolved by general circulation models, requiring that lake surface temperatures be estimated. Given the large spatial and temporal variability of the surface temperatures of the North American Great Lakes, such estimations can introduce errors when used as lower boundary conditions for dynamical downscaling. Lake surface temperatures (LSTs) influence moisture and heat fluxes, thus impacting precipitation within the immediate region and potentially in regions downwind of the lakes. For this study, the Advanced Research version of the Weather Research and Forecasting Model (WRF-ARW) was used to simulate precipitation over the six New England states during a 5-yr historical period. The model simulation was repeated with perturbed LSTs, ranging from 10°C below to 10°C above baseline values obtained from reanalysis data, to determine whether the inclusion of erroneous LST values has an impact on simulated precipitation and synoptic-scale features. Results show that simulated precipitation in New England is statistically correlated with LST perturbations, but this region falls on a wet–dry line of a larger bimodal distribution. Wetter conditions occur to the north and drier conditions occur to the south with increasing LSTs, particularly during the warm season. Additionally, the precipitation differences coincide with large-scale anomalous temperature, pressure, and moisture patterns. Care must therefore be taken to ensure reasonably accurate Great Lakes surface temperatures when simulating precipitation, especially in southeastern Canada, Maine, and the mid-Atlantic region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗
DOE OSTI2021

Updated distribution maps of predominant Culex mosquitoes across the Americas

Abstract Background Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s. Since these estimates were made, there have been many more documented observations of mosquitoes and new methods have been developed for species distribution modeling. Moreover, mosquito distributions are affected by environmental conditions, which have changed since the 1980s. This calls for updated estimates of these distributions to understand the risk of emerging and re-emerging mosquito-borne diseases. Methods We used contemporary mosquito data, environmental drivers, and a machine learning ecological niche model to create updated estimates of the geographical range of seven predominant Culex species across North America and South America: Culex erraticus , Culex nigripalpus , Culex pipiens , Culex quinquefasciatus , Culex restuans , Culex salinarius , and Culex tarsalis . Results We found that Culex mosquito species differ in their geographical range. Each Culex species is sensitive to both natural and human-influenced environmental factors, especially climate and land cover type. Some prefer urban environments instead of rural ones, and some are limited to tropical or humid areas. Many are found throughout the Central Plains of the USA. Conclusions Our updated contemporary Culex distribution maps may be used to assess mosquito-borne disease risk. It is critical to understand the current geographical distributions of these important disease vectors and the key environmental predictors structuring their distributions not only to assess current risk, but also to understand how they will respond to climate change. Since the environmental predictors structuring the geographical distribution of mosquito species varied, we hypothesize that each species may have a different response to climate change. Graphical abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Country-level land carbon sink and its causing components by the middle of the twenty-first century

Abstract Background Countries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink and its involving processes by natural ecosystems remain difficult to quantify. Methods Using a transient traceability framework, we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5. Results The top 20 countries with highest C sink have the potential to sequester 62 Pg C in total, among which, Russia, Canada, USA, China, and Brazil sequester the most. This C sink consists of four components: production-driven change, turnover-driven change, change in instantaneous C storage potential, and interaction between production-driven change and turnover-driven change. The four components account for 49.5%, 28.1%, 14.5%, and 7.9% of the land C sink, respectively. Conclusion The model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions, especially for countries where net primary production (NPP) likely increases substantially and inherent residence time elongates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Effects of fire and fire-induced changes in soil properties on post-burn soil respiration

Boreal forests cover vast areas of land in the northern hemisphere and store large amounts of carbon (C) both aboveground and belowground. Wildfires, which are a primary ecosystem disturbance of boreal forests, affect soil C via combustion and transformation of organic matter during the fire itself and via changes in plant growth and microbial activity post-fire. Wildfire regimes in many areas of the boreal forests of North America are shifting towards more frequent and severe fires driven by changing climate. As wildfire regimes shift and the effects of fire on belowground microbial community composition are becoming clearer, there is a need to link fire-induced changes in soil properties to changes in microbial functions, such as respiration, in order to better predict the impact of future fires on C cycling. We used laboratory burns to simulate boreal crown fires on both organic-rich and sandy soil cores collected from Wood Buffalo National Park, Alberta, Canada, to measure the effects of burning on soil properties including pH, total C, and total nitrogen (N). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and its resulting changes in soil properties on soil respiration. Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events. We found that burning increased pH and caused small decreases in C:N in organic soil. Overall, respiration per gram total (post-burn) C in burned soil cores was 16% lower than in corresponding unburned control cores, indicating that soil C lost during a burn may be partially offset by burn-induced decreases in respiration rates. Simultaneously, burning altered how remaining C cycled, causing an increase in the proportion of C represented in the modeled slow-cycling vs. fast-cycling C pool as well as an increase in fast-cycling C decomposition rates. Together, our findings imply that C storage in boreal forests following wildfires will be driven by the combination of C losses during the fire itself as well as fire-induced changes to the soil C pool that modulate post-fire respiration rates. Moving forward, we will pair these results with soil microbial community data to understand how fire-induced changes in microbial community composition may influence respiration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effectiveness of Residue and Tillage Management on Runoff Pollutant Reduction from Agricultural Areas

Highlights No-till and no-till residue systems were effective in reducing runoff particulate and total nutrients but increased dissolved nutrients. Maintaining >30% residue cover reduced most runoff constituents, irrespective of no-till or tillage. No-till-residue prevented runoff nutrient losses and benefitted farm revenue by avoiding tillage. Abstract. Reduced tillage management conservation practices (No-till and Reduced-till) are widely adopted in agriculture; however, understanding their overall effectiveness for water quality protection is challenging. A meta-analysis was conducted to understand and quantify the effectiveness of residue and tillage management on runoff, sediment, and nutrient losses from agricultural fields. Annual runoff and the associated sediment, and nutrient (nitrogen and phosphorus) loads were compiled from 60 peer reviewed research articles published across the United States and Canada. A total of 1575 site-years of data were categorized into tillage (<30% surface cover), no-tillage (<30% surface cover), tillage with residue (>30% surface cover), no-tillage with residue (>30% surface cover), and pasture management. No-tillage, no-tillage-residue, and tillage-residue managements were evaluated for their effectiveness in reducing runoff, nutrients, and sediment loads compared to tillage. Synthesized and surveyed corn yield data were used to evaluate the economic cost effectiveness of no-tillage-residue management with respect to tillage. Across the site years (1968-2019) studied, median runoff depth for no-tillage and no-tillage-residue were 84% and 70% greater than tillage and tillage-residue management, respectively. No-tillage-residue management had up to 86% less sediment losses than tillage systems, on average, for both >30% and <30% surface cover. No-tillage-residue management was most effective, with a positive performance effectiveness of 65% to 90% in controlling sediments, particulate, and total nutrient losses in runoff compared to tillage. Cost effectiveness analysis revealed the benefits of no-tillage-residue management in reducing nutrient loads and increasing net-farm revenue by avoiding tillage operational costs. Except for dissolved phosphorus, no-tillage-residue management cost effectiveness for sediments and nutrient loads ranged from negative $6 to negative $102 per every Mg or kg of load reduction, indicating it had both economic and environmental benefits compared to tillage management. Overall, these results indicate that over the long-term, no-tillage and tillage, combined with greater than 30% residue cover, can effectively reduce sediment and nutrient losses. This work highlights the importance of crop residues on the soil surface to reduce runoff losses, even in no-tillage systems. Keywords: Conservation tillage, No-tillage, Residue cover, Tillage, Water quality.

Agriculture↗
DOE OSTI2022

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. Methods: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ) and ground-level ozone (O 3 ), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ longterm exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. Results: Among the 151105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM 2.5 (1.70 µg/m 3 ), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO 2 . We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O 3 for hospital admission, ICU admission and death, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

SubTER ZTEM (Z-Axis Tipper Electromagnetic) Survey Results, Mineral Mountains Area, Utah

This data was acquired as part of the Subsurface Science, Technology and Engineering Research, and Development (SubTER) Crosscut which is a collaboration across the Department of Energy offices involved in research activities in energy production/extraction, subsurface storage, and environmental remediation. The contents of this zip contains the ZTEM survey measured and processed results for the Mineral Mountains area, Utah. The data were acquired through subcontract to Geotech Inc of Aurora, ON, Canada and their narrative report is included. There are also two readme.txt file included that further describe the data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Subsurface redox potential and water level at the Elkhorn Slough NERR

This resource contains various hydrological, and geochemical data from Elkhorn Slough National Estuarine Research Reserve from the years 2020 and 2021. These data have been used to assess how continuous measurements of environmental variables. The data can be used to understand processes at timescales over which biochemical transformations can happen. Especially, the data were used to explain the local subsurface hydrology, and its implication, in an experimental transect in a coasta estuary. Water level and water temperature were measured in-situ with Solinst pressure transducer loggers (Ontario, Canada). Redox potential was collected using in-situ, redox sensors (Paleoterra, The Netherlands) connected to CR1000X Campbell data loggers (Logan, Utah). Meteorological data was gathered from the Elkhorn Slough meteorological station.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

WHONDRS Surface Water Chemistry and Organic Matter Characterization along the St. Lawrence River's Inland to Coastal Gradient, Eastern North America (v2)

This dataset supports a broader study examining the inland (Lake Ontario) to coastal (North Atlantic Ocean) geochemistry gradient along the St. Lawrence River in Canada and the United States. The St. Lawrence River is unique in that it contains the convergence of multiple water masses with distinct water signatures that mix only slightly as the river flows downstream. The dataset provides dissolved organic carbon (DOC) and organic matter characterization data generated from surface water. Samples were collected by researchers on board the Lampsilis research vessel (l’Université du Québec à Trois-Rivières) and small boats (St. Lawrence River Institute of Environmental Sciences, Cornwall) at 94 locations across and along the St. Lawrence River to capture longitudinal and transverse variation. Related data were collected and will be published separately in collaboration with the MicrEAU Laboratory (François Guillemette; l’Université du Québec à Trois-Rivières) and the Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; and (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. The data package was originally published in November 202. It was updated in April 2025 (v2; modified files). See the change history section in the readme for details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Improving the Estimation of the Atmospheric Water Vapor Pressure Using Interpretable Long Short-Term Memory Networks: Dataset, Python code, and trained models

Atmospheric water vapor pressure is an essential meteorological control on land surface and hydrologic processes. It is not as frequently observed as other meteorologic conditions, but often inferred through the August–Roche–Magnus formula by simply assuming dew point and daily minimum temperatures are equivalent or by empirically correlating the two temperatures using an aridity correction. The performance of both methods varies considerably across different regions and during different time periods; obtaining consistently accurate estimates across space and time remains a great challenge. We applied an interpretable Long Short-Term Memory (iLSTM) network conditioned on static, location specific attributes to estimate daily vapor pressure for 83 FLUXNET sites in the United States and Canada. This data package includes all raw data of the 83 FLUXNET sites, input data for model training/validation/test, trained models and results, and python codes for the manuscript "Improving the Estimation of the Atmospheric Water Vapor Pressure Using an Interpretable Long Short-term Memory Network". Specifically, it consists of five parts. - First, "1_Daymet_data_83sites.zip" includes raw data downloaded from Daymet for the 83 sites used in the paper according to their longitude and latitude, in which vapor pressure is used. It also includes a pre-processed CSV data file combining all data from the 83 sites which is specifically used for the paper. - Second, "2_Fluxnet2015_data_83sites.zip" includes raw half hourly data of the 83 sites downloaded from FLUXNET2015 data portal, pre-processed daily data of the 83 sites, a CSV file including combined pre-processed daily data of the 83 sites, and a CSV file including the information (site ID, site name, latitude, longitude, data available period) of the 83 sites. - Third, "3_MODIS_LAI_data_83sites_raw.zip" includes raw leaf area index (LAI) data downloaded from the AppEEARs data portal. - Fourth, "4_Scripts.zip" includes all scripts related to model training and post-processing of a trained model, and a jupyter notebook showing an example for model post-processing. Two typo errors in files titled "run2get_args.py" and "postprocess.py" were corrected on March 27, 2024 to avoid confusions. - Finally, "Trained_models_and_results.zip" includes three folders and three files with suffix ".npy", and each folder corresponds to one file with suffix ".npy" with the same title. Each of the three folders include all trained models associated with one iLSTM model configuration (35 models for each configuration, details are described in the paper). Each file with suffix ".npy" includes the post-processed results of the corresponding 35 models under one iLSTM model configuration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Pan-Arctic daily streamflow at 0.5-degree resolution

Data was derived using daily runoff from models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) that have been routed through the Model for Scale Adaptive River Transport (MOSART) routing model to represent streamflow at individual streamflow gage locations. Data from 750 streamflow gage locations are represented, which are indexed by gage id according to the metadata.csv file. Streamflow gage location sites were based on gage records downloaded from the United States Geological Survey (USGS), National Water Data (HYDAT) Archive from Canada, and the State Hydrological Institute of Russia. Data are available from 11 Earth System Models (ESMs) in total at a daily timestep with a duration of 1920-2099 (1850-2014 for E3SM only). The spatial domain of the modeled data is 0.5 degree resolution. Earth System Models and Units of mean daily streamflow are presented in cubic meters per second (cms). Data files consist of 11 Earth System Model mean daily streamflow output per gage location in .csv format, 1 metadata file in .csv format and 1 Readme file in .docx format (13 files in total). These data were used to benchmark CMIP6 modeled representations of streamflow against gage records.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of fire on chemical properties and respiration of boreal forest soils

We collected both organic-rich and sandy soil cores from 12 sites (site_location_and_texture.csv) within Wood Buffalo National Park, Alberta, Canada. Laboratory burns were conducted by exposing intact soil cores to 60 kW m^-2 in a mass loss calorimeter to simulate boreal forest crown fires in order to measure the effects of burning (temp_data.csv) on soil properties including pH, total C, and total nitrogen (N) (metadata.csv). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and burn-induced changes in soil properties on soil respiration (soil_moisture_at_end_of_incubation.csv; soil_mass_at_end_of_incubation.csv; respiration_data.csv). Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events.

54 ENVIRONMENTAL SCIENCES↗