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DOE OSTI2021

Data Product: Ka ARM Zenith Radar (KAZR), in CfRadial format: precipitation mode, corrected

The KAZRCFRCOR Value Added Product (VAP) performs several corrections to the ingested KAZR data and also creates a significant detection mask for each radar mode. The VAP computes gaseous attenuation as a function of time and radial distance from the radar antenna, based on ambient relative humidity, and corrects observed reflectivities for that effect. KAZR reflectivities are also corrected in the antenna ‘nearfield’ range to compensate for the near-field antenna pattern and gain. KAZRCFRCOR also dealiases mean Doppler velocities, to correct velocities whose magnitudes exceed the radar’s Nyquist velocity. This dataset contains the 'kazrpr' (precipitation) mode output from this VAP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Data Product: Ka ARM Zenith Radar (KAZR), in CfRadial format: general mode, corrected

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗

DOE OSTI2023

SPRUCE Climate Warming and Elevated CO2 Rapidly Alter Peatland Soil Carbon Sources and Stability: Supporting Data

This data set reports a suite of complementary biogeochemical analyses of peat samples from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment. Results were collected using quantitative molecular analysis of bulk soil carbon to assess the stability of soil organic carbon following whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (eCO2). Targeted soil organic carbon components include solvent-extractable compounds (alkanoic acids, alkanols, alkanes, steroids, and terpenoids), ester-bound hydrolysable biopolymers (cutin and suberin markers), lignin phenols, and pyrogenic carbon. Bulk peat samples were analysed by Soxhlet extraction and solid phase separation for solvent-extractable compounds, alkaline hydrolysis to extract hydrolysable biopolymers, copper (II) oxide oxidation to extract lignin phenols and benzene polycarboxylic acids (BPCAs) as an approximation of pyrogenic carbon. Samples were analysed by gas chromatography (GC) equipped with a flame ionization detector (GC-FID) and compound identification was performed on GC coupled to mass selective detector (MS) for solvent-extractable compounds, ester-bound hydrolysable biopolymers and lignin phenols, and high-performance liquid chromatograph (HPLC) for pyrogenic carbon. Results are presented in Ofiti et al. (accepted). The experimental work was conducted on samples collected in August 2018 at the SPRUCE climate manipulation experiment in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Samples were collected and later analysed in a 10 cm increments over 0 to 50 cm depth and 25 cm intervals from 50 to 75 cm. Samples were analyzed for lignin phenols over 0 to 30 cm depth. This data set contains one file in comma separate (*.csv) format. This dataset contains data used to produce: Ofiti, N.O.E., Schmidt, M.W.I., Abiven, S., Hanson, P.J., Iversen, C.M., Wilson, R.M., Kostka, J.E., Wiesenberg, G.L.B., Malhotra, A. 2023. Climate warming and elevated CO2 rapidly alter peatland soil carbon sources and stability. Nat Commun 14, 7533. https://doi.org/10.1038/s41467-023-43410-z.

SPRUCE experiment, Marcell Experimental Forest, so↗

DOE OSTI2026

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗

DOE OSTI2022

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Measuring stellar populations, dust attenuation and ionized gas at kpc scales in 10010 nearby galaxies using the integral field spectroscopy from MaNGA

As one of the three major experiments of the fourth-generation Sloan Digital Sky Survey (SDSS-IV), the Mapping Nearby Galaxies at Apatch Point Observatory (MaNGA) survey has obtained high-quality integral field spectroscopy (IFS) with a resolution of 1–2 kpc for ∼ 10 4 galaxies in the local universe during its six-year operation from July 2014 through August 2020. It is crucial to reliably measure the physical properties of the different components in each spectrum before one can use the data for any scientific study. In the past years we have made lots of efforts to develop a novel technique of full spectral fitting, which estimates a model-independent dust attenuation curve from each spectrum, thus allowing us to break the degeneracy between dust attenuation and stellar population properties when fitting the spectrum with stellar population synthesis models. We have applied our technique to the final data release of MaNGA, and obtained measurements of stellar population properties and emission line parameters, as well as the kinematics and dust attenuation of both stellar and ionized gas components. In this paper we describe our technique and the content and format of our data products. The whole dataset is publicly available in Science Data Bank with the link https://doi.org/10.57760/sciencedb.j00113.00088 .

Physics↗

DOE OSTI2021

Data Product: Ka ARM Zenith Radar (KAZR), in CfRadial format: moderate sensitivity mode, corrected

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2022

Spiner

Spiner is a library for storing, indexing, and interpolating multidimensional data in a performance-portable way. It’s intended to run on CPUs, GPUs and everything in-between. You can create a table on a CPU, copy it to a GPU, and interpolate on it in a GPU kernel, for example. Spiner also defines (via hdf5) a file format that bundles data together with instructions for interpolating it. This means you don’t have to specify anything to start interpolating, simple load the file and evaluate where you want.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Compact Steep Spectrum Radio Sources with Enhanced Star Formation Are Smaller Than 10 kpc

Compact steep spectrum (CSS) radio sources are active galactic nuclei (AGN) that have radio jets propagating only on galactic scales, defined as having projected linear size (LS) of up to 20 kpc. CSS sources are generally hosted by massive early-type galaxies with little ongoing star formation; however, a small fraction are known to have enhanced star formation. Using archival data from the Faint Images of the Radio Sky at Twenty cm survey, the Very Large Array Sky Survey, and the Sloan Digital Sky Survey, we identify a volume-limited sample of 166 CSS sources at z < 0.2 with L 1.4 GHz > 10 24 W Hz -1 . Comparing the star formation rates and linear sizes of these CSS sources, we find that the ≈14% of CSS sources with specific star formation rates above 0.01 Gyr -1 all have LS < 10 kpc. We discuss the possible mechanisms driving this result, concluding that it is likely the excess star formation in these sources occurred in multiple bursts and ceased prior to the AGN jet being triggered.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

SPRUCE Methane Transport in Plants at S1 Bog, Marcell Experimental Forest, Minnesota, 2017-2019

This data set contains measurements of methane (CH4) transport by plants (both ground-layer and trees) and diffusion, as well as whole-plot emissions, taken in September 2018 and June 2019 in S1 Bog outside of the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experimental enclosures. Additionally, CH4 and carbon dioxide (CO2) stable isotope data in porewater and atmospheric emissions were taken in July 2017 in the SPRUCE enclosures to explore the relative magnitude of CH4 oxidation. Episodic ebullition rates for S1 Bog are taken from Gill et al. (2017). Methane transport is an important component of many ecosystem models of peatlands. The results were compared to two methane models that have been developed for the SPRUCE project, ELM-SPRUCE (Earth Land Model) and TECO_SPRUCE (Terrestrial ECOsystem model). This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

SPRUCE Aboveground Vegetation Coverage in Root Ingrowth Core Plots, Marcell Experimental Forest, Minnesota, August 2022

This dataset contains vegetation survey measurements from root ingrowth core plots (Määttä et al. 2025) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. Vegetation surveys were conducted in 0.25 meter2 plots containing root ingrowth cores on August 8th and 9th, 2022 (2022-08-08 to 2022-08-09). The warming and elevated carbon dioxide (CO2) treatments in the dataset include the full treatment gradient: +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +2.25 degrees C (+0 and +500 ppm), +4.5 degrees C (+0 and +500 ppm elevated CO2), +6.75 degrees C (+0 and +500 ppm) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows. This dataset includes measurements of the height and absolute coverage (%) for each vascular plant and moss species, as well as organic litter and dead overstory vascular plants, and the distance from the grid center to the nearest tree and the species of the nearest tree. These data were used as species-specific aboveground plant metadata for assessing the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

DOE OSTI2025

SPRUCE Measurements of Fine Root Production and Chemistry from Root Ingrowth Cores, Marcell Experimental Forest, Minnesota, 2022-2023

This dataset contains fine root production and tissue chemistry measurements from root ingrowth cores. Ingrowth cores were deployed in peat from June 28, 2022 to June 24, 2023 (2022-06-28 to 2023-06-24) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. The warming and elevated carbon dioxide (CO2) treatments in this dataset include +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +4.5 degrees C (+0 and +500 ppm elevated CO2) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows, as well as +2.25 degrees C (+0 and +500 ppm) and +6.75 degrees C (+0 and +500 ppm) for hollows from minimum 10 cm depth from the peat surface. Measurements include root average diameter, root length, root biomass, and root tissue nitrogen (%N and δ15N) and carbon (%C and δ13C) concentration per plant functional type and microtopographical feature. Root length and biomass are standardized to 10 cm depth. These data were used to assess the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

DOE OSTI2026

SPRUCE Peat Core Sample Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B05LW. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > TERRESTRI↗

DOE OSTI2025

SPRUCE: Shrub-Layer Vegetation Biomass Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗

DOE OSTI2022

Leaf-area index of Oak-Hickory Forest at Missouri Ozark (MOFLUX) site: 2007–2022

This data set contains measurements of leaf-area index (LAI) at the Missouri Ozark (MOFLUX) site during growing seasons from 2007-2022. The MOFLUX site is located in the University of Missouri Baskett Forest, a second growth oak-hickory forest situated in the Ozark Border Region of central Missouri, USA. MOFLUX is part of the AmeriFlux network (site ID: US-MOz) and an eddy covariance tower marks the middle of the site (Figure 1). During 2003, 24 circular vegetation plots (each 0.08 hectares) were established within a ~250 meter (m) radius around the tower. The plots were situated 50 m apart along 5 linear transects radiating out from the flux tower base in southeast, south, southwest, west, and northwest directions. There were 5 plots per transect except for the northwest one, which had only 4 due to the presence of a small pond at the terminus. At weekly intervals during the growing season, leaf-area index measurements were taken within each vegetation plot on the 5 transects running from the central flux tower. A plant canopy analyzer (model LAI-2000 Li-Cor Inc., Lincoln NE) was used to make the LAI measurements. We collected samples to enable measurement of the mean LAI of each transect. LAI observations are useful for understanding vegetation phenology, and to aid in the interpretation of ecosystem gas exchange. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

DOE OSTI2024

Responses of Drying-rewetting (Transient Soil Moisture) and Steady State Soil Moisture Incubation on Soil Organic Carbon Dynamics in Three US Soils, 2017

This data set contains measurements of soil characteristics (aggregate size distribution and mean size, total aggregate associated carbon, extractable organic C, and microbial biomass C), microbial respiration, and soil metabolite concentrations from a transient and steady soil moisture incubation experiment using soils of different textures (sandy, loamy, and clayey). The study investigated mechanisms driving the Birch effect (increased carbon mineralization pulses with wetting following a drying period) in differing soil textures. Three different soils of distinctly different textures were collected from 0-15cm depth in Georgia (sandy, 2017-05-01), Missouri (loamy, 2017-06-14), and Texas (clayey, December 2017). Soils were incubated for 140 days with destructive harvests done on days 1, 29, 33, 56, 112, 116, and 140 in transient soil moisture incubation and on days 1, 33, 116, and 140 in steady state soil moisture incubation. This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

1-Methyladenosine concentration↗