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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Model data for a watershed-scale study in the Portage River Basin (OH) examining the effects of subsurface drainage on the hydrologic response of an agricultural watershed.

This study builds on Rathore et al. (2024, WRR) and investigates the role of artificial tile-drainage on various aspects of watershed hydrological response, with a particular focus on peakflow. The model-data for the original modeling-focused paper (Rathore et al., 2024, WRR) is archived at Rathore et al. (2024, ESS-DIVE). Hence, this model-data archive provides scripts that are specific to this study that includes model updates, processing and analysis scripts. For details and models files of original model, readers are referred to Rathore et al. (2024, ESS-DIVE). The key difference between the model configuration in this study and Rathore et al. (2024, WRR) is that the tile drains are applied to the entire domain, to study the impact of tile-drains on different aspects of hydrological response. Additional scenario considering intensified precipitation after a dry period was also simulated. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗
DOE OSTI2025

BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies Fireball Database

Fireballs (bolides) are high-energy luminous phenomena produced when meteoroids and small asteroids enter Earth’s atmosphere at hypersonic speeds, often resulting in fragmentation or complete disintegration accompanied by significant energy release. The resulting bolide light curves capture temporal brightness variations as these objects traverse increasingly dense atmospheric layers, providing essential information on meteoroid entry dynamics, fragmentation behavior, and atmospheric energy deposition processes. The Center for Near-Earth Object Studies’ (CNEOS) continuously expanding fireball database offers a globally comprehensive archive of bolide events, including light curves and associated metadata. Events associated with infrasound detections allow direct correlations between acoustic signatures and light curve features, therefore enabling detailed analyses of fragmentation dynamics and energy deposition. Here, we introduce Bolide Light-curve Analysis and Discrimination Explorer (BLADE), a robust and high-fidelity framework specifically designed to analyze bolide light curves for objects detected from space. BLADE incorporates a processing pipeline integrating Savitzky–Golay filtering, prominence-based peak detection, and gradient analysis, enabling systematic identification and classification of fragmentation events and their associated energy release characteristics. Preliminary results demonstrate that BLADE reliably distinguishes distinct bolide behaviors, providing an objective, scalable methodology for characterization and analysis of large bolide light curve data sets. This foundational work establishes a novel pathway for advanced bolide research, with promising applications in planetary defense and global atmospheric monitoring. Future research should adopt an integrative approach combining CNEOS optical data with complementary infrasound measurements, further clarifying relationships between bolide energy deposition and acoustic signatures, thus refining our understanding of meteoroid and asteroid atmospheric entry processes.

Asteroids↗
DOE OSTI2026

Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits

This repository contains the simulation outputs and processing scripts associated with the study of winter wheat traits across the United States, utilizing the Ecosys agroecosystem model. The dataset includes model results for both rainfed and irrigated winter wheat systems, supporting the findings presented in the manuscript titled "Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits." Data includes the original Ecosys simulation outputs (archived in .db format within the compressed .zip files) and extracted analysis data (stored in .pkl files for efficient processing). Python code for data processing and figure generation is provided in a Jupyter notebook. External Observational Datasets should refer to the following official repositories for the input and validation data used in this study. The eddy covariance data from the AmeriFlux network (https://ameriflux.lbl.gov/). Climate-forcing data of NLDAS-2 from NASA LDAS (https://ldas.gsfc.nasa.gov/nldas/nldas-2-forcing-data). Soil data from the Gridded Soil Survey Geographic Database (gSSURGO), available at (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database). Crop yields, planting and harvest dates from the USDA public databases (https://quickstats.nass.usda.gov/; https://webapp.rma.usda.gov/apps/actuarialinformationbrowser/CropCriteria.aspx). Satellite-derived SLOPE GPP data from ORNL DAAC (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1786). Land use and crop progress information from the USDA Crop Data Layer and Crop Progress and Condition Gridded Layers (https://www.nass.usda.gov/Research_and_Science/). The Ecosys model code is available online at https://github.com/jinyun1tang/ECOSYS.

Wheat↗
DOE OSTI2025

A Curated Dataset of Regional Meteor Events with Simultaneous Optical and Infrasound Observations (2006–2011)

We present a curated, openly accessible dataset of 71 regional meteor events simultaneously recorded by optical and infrasound instrumentation between 2006 and 2011. These events were captured during an observational campaign using the all-sky cameras of the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. Each entry provides optical trajectory measurements, infrasound waveforms, and atmospheric specification profiles. The integration of optical and acoustic data enables robust linkage between observed acoustic signals and specific points along meteor trajectories, offering new opportunities to examine shock wave generation, propagation, and energy deposition processes. This release fills a critical observational gap by providing the first validated, openly accessible archive of simultaneous optical–infrasound meteor observations that supports trajectory reconstruction, acoustic propagation modeling, and energy deposition analyses. By making these data openly available in a structured format, this work establishes a durable reference resource that advances reproducibility, fosters cross-disciplinary research, and underpins future developments in meteor physics, atmospheric acoustics, and planetary defense.

astrometry↗
DOE OSTI2026

HostSub_GP: Precise Galaxy Background Subtraction in Transient Long-slit Spectroscopy with Gaussian Processes

We present a novel host galaxy subtraction technique in long-slit spectroscopy for extragalactic transients. Unlike classic methods which generally estimate the background using simple interpolation of local galaxy flux in the 2D spectrum, our approach leverages multi-band archival images of the host galaxies to model the background emission from the galaxy in the 2D spectrum. Such imaging encodes the wavelength-dependent galaxy profile along the slit, and is readily accessible through wide-field imaging surveys. We construct a smooth prior for the 2D galaxy profile with a Gaussian process (GP) based on these reference images, and use another GP to model the correlated deviations from the prior in the observed spectrum. This enables accurate inference of the galaxy flux blended with the transient. On synthetic long-slit data of a spiral galaxy extracted from a Multi Unit Spectroscopic Explorer hyper-spectral cube, the GP method remains robust as long as the host galaxy is spatially resolved and consistently outperforms classic methods. We apply the method to archival Keck spectra of two real transients, SN 2019eix and AT 2019qiz, to further demonstrate how the method uniquely recovers weak spectral features amid strong galaxy contamination, enabling refined constraints on the properties of both transients. We have released the software implementation, HostSub_GP, a scalable toolkit that leverages JAX, with an MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

ARM Lead Mentor Selection Process

The Atmospheric Radiation Measurement (ARM) Program was created in 1989 with funding from the U.S. Department of Energy (DOE) to develop several highly instrumented ground stations to study cloud-formation processes and their influence on radiative transfer. This scientific infrastructure provides for fixed sites, mobile facilities, an aerial facility, and a data archive available for use by scientists worldwide through the ARM Climate Research Facility—a scientific user facility. The ARM Climate Research Facility currently operates more than 300 instrument systems that provide ground-based observations of the atmospheric column. To keep ARM at the forefront of climate observations, the ARM infrastructure depends heavily on instrument scientists and engineers, known as Mentors. Mentors must have an excellent understanding of instrumentation theory and operation for their instrument areas and have comprehensive knowledge of critical scale-dependent atmospheric processes. They must also possess the technical and analytical skills to develop new data retrievals that provide innovative approaches for creating research-quality data sets. The ARM Facility seeks the best overall qualified candidate, or team when appropriate, that can fulfill Mentor requirements in a timely manner. The roles and responsibilities of the ARM Instrument Operations Manager are provided in Appendix A. The key role and responsibilities and detailed responsibilities of ARM Lead Mentors are provided in Appendix B and Appendix C, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

User Guide: A Curated Dataset of Regional Meteor Events with Simultaneous Optical and Infrasound Observations

This user guide supports a curated dataset of 71 meteor events recorded between 2006 and 2011 in Southwestern Ontario, Canada. Each event was simultaneously observed by ground-based optical cameras and an infrasound array, providing a rare opportunity to examine meteor trajectories and acoustic signals from the same atmospheric entry events. The dataset includes raw and processed optical data, meteor trajectories, photometric light curves, infrasound waveforms, and atmospheric specifications relevant for acoustic modeling. The archive is structured to support reproducible research in meteor physics, atmospheric acoustics, and shock wave analysis. It is organized following transparent file naming conventions and structured folders to facilitate scientific reuse, comparison, and integration across research domains. The dataset is freely available on Zenodo, doi: 10.5281/zenodo.15868512.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River watershed during SPLASH, 2021–2023

Abstract. From autumn 2021 through summer 2023, scientists from the National Oceanic and Atmospheric Administration (NOAA) and partners conducted the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in the East River watershed of Colorado. One objective of SPLASH was to observe the transfer of energy between the atmosphere and the surface, which was done at several locations. Two remote sites were chosen that did not have access to power utilities. These were along the valley floor near the East River in the vicinity of the unincorporated town of Gothic, Colorado. Energy balance measurements were made at these locations using autonomous, single-level flux towers referred to as atmospheric surface flux stations (ASFSs). The ASFSs were deployed on 28 September 2021 at the Kettle Ponds Annex site and on 12 October 2021 at the Avery Picnic site and operated until 19 July and 21 June 2023, respectively. Measurements included basic meteorology; upward and downward longwave and shortwave radiative fluxes and subsurface conductive flux, each at 1 min resolution; 3-D winds from a sonic anemometer and H2O/CO2 from an open-path gas analyzer, both at 20 Hz from which sensible, latent heat, and CO2 fluxes were derived; and profiles of soil properties in the upper 0.5 m (both sites) and temperature profiles through the snow (at Avery Picnic), each reported between 10 min and 6 h. The system uptime was 97 % (Kettle Ponds) and 90 % (Avery Picnic), and collectively 1184 d of data was obtained between the stations. The purpose of this article is to document the ASFS deployment at SPLASH, to document the data acquisition and post-processing of measurements, and to serve as a guide for interested users of the data sets, which are archived at Zenodo (https://doi.org/10.5281/zenodo.10313363, Cox et al., 2023b; https://doi.org/10.5281/zenodo.10327409, Cox et al., 2023c; https://doi.org/10.5281/zenodo.10313894, Cox et al., 2023d; https://doi.org/10.5281/zenodo.10307825, Cox et al., 2023e; https://doi.org/10.5281/zenodo.10310520, Cox et al., 2023f) with the Creative Commons Attribution 4.0 International license.

Cox, Christopher J. (ORCID:0000000322037173)↗
DOE OSTI2025

Electrical Resistivity Tomography data from 2016 to 2018 at the Lower Montane site in the East River Watershed, Colorado

This dataset contains time-lapse Electrical Resistivity Tomography (ERT) data along a transect located on the northeast-facing hillslope at the lower montane site (Pumphouse site) in the upper East River Watershed. The monitoring dataset covers the period from November 2, 2016, to August 6, 2018. In addition, the archive also contains a baseline dataset from October 9, 2016. The ERT transect consisted of 128 electrodes with an electrode spacing of 1.25 m. The acquisition system was located in the middle of the transect, about 50 m on one side, and included an MPT (Multi-Phase Technologies) ERT system, a mini computer, and batteries with solar panels. Acquisition occurred daily under normal circumstances. The first 16 electrodes (from the upper end of the transect) could not be used after the cable was damaged during the 2017–2018 winter. Also, due to multiple failures in the power system, the temporal resolution of the data is much lower in 2018 compared to 2016 and 2017. The data have been processed and used in Dafflon et al., 2023, and the baseline dataset was used in Falco et al., 2019 (see reference list). This archive contains the measurements (ER.zip containing csv files) for each of the 326 acquisition times and a filtered version where only electrodes 17 to 128 are included (ERT_sm.zip containing csv files). The archive also contains the baseline dataset and two acquisitions with full reciprocals (ERT_RB.zip containing csv files), as well as all the raw MPT files (ERT_raw_MTP.zip). The geometry (electrode position and elevation) is provided in Universal Transverse Mercator (UTM) 13N Geoid2012AB in the file named ERT_Location.csv. The archive contains 1 *.csv data files, four *.zip files, and three metadata *.csv files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Automating Anomaly Detection for Target systems at Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory, produces the world’s most intense pulse neutrons beams. An accelerated proton beam is directed into a mercury target to generate neutrons via spallation. The target system accounted for over 40% of the overall downtime of the facility in 2022. Thus, early detection in anomalies in the target systems can enable taking corrective actions to avoid failures and reduce downtime. Fault prognostics and anomaly detection in accelerators, both at SNS and outside, has largely focused on the beam side. This paper presents one the first studies exploring leveraging machine learning to automate the detection of anomalies in the target system. The target system consists of over 30 different interconnected subsystems, and the present work focuses on the mercury process system as a use case. Analyzing data from 28 process variables from 2022 and 2023, tree-based and reconstruction-based algorithms are employed to detect anomalies in archived data. The algorithms detected previously unreported anomalies, several of which were deemed alert worthy by human experts, particularly those found by reconstruction-based algorithms. Using data from each production run in the accelerator increased the generalizability of the models in time. Efforts are now underway to implement a workflow for incorporating human feedback to update the models and evaluating performance on unseen data. The models will eventually be integrated into the existing System Tracking and Reliability system with a web interface for automated anomaly detection and reporting along with a pathway for incorporating human feedback for model updates.

Raj, Anant [ORNL] (ORCID:0000000306711244)↗
DOE OSTI2026

Vanderbilt CMS Heavy-Ion Tier-2 Facility (Final Report)

The CMS experiment at the LHC at CERN in Geneva, Switzerland spends a portion of its running time colliding heavy ions. These heavy ion collisions are a key probe of a state of matter known as a Quark Gluon Plasma, which is a state of matter found in the very early universe 10s of microseconds after the big bang. These collision data are recorded by the CMS experiment and then undergo several stages of refinement to extract physics properties of the collisions from the raw data recorded by the various detector subsystems in CMS. In addition, copies of these datasets are stored on tape archival storage for data preservation. This award funds the deployment, maintenance, and operation of a computing facility at Vanderbilt University which processes, stores, and analyzes these collision data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗
DOE OSTI2026

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗
DOE OSTI2024

Open Source Synergy: Developing and Validating PMU Data Analysis Techniques Using Open Source Tools and Datasets

This paper presents an exploration into the development and validation of data analysis approaches for Phasor Measurement Units (PMUs) using open-source datasets and tools. Various methods for event detection, event classification, frequency response, and oscillation analysis were tested. We leverage the capabilities of Archive Walker (AW), the Frequency Response Analysis Tool (FRAT), and the Oscillation Baselining and Analysis Tool (OBAT), all open-source tools, for efficient processing and analysis of synchrophasor data. The open-source Transmission Signature Library (TSL) dataset was employed as a dataset for a comprehensive evaluation to assess the performance and reliability of the proposed methods.

PMU, event analysis, oscillation, Frequency Respon↗
DOE OSTI2026

Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”

This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.

Dissolved organic matter↗
DOE OSTI2024

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

54 ENVIRONMENTAL SCIENCES↗