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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CACTI CSAPR2 Taranis Retrievals

Taranis is an end-to-end processing chain for radar data written in Python with C extension for computation performance. Features include: masking for quality control, specific differential phase (Kdp), attenuation correction for reflectivity factor (Z) and differential reflectivity (Zdr) in rain, and additional geophysical retrievals. Retrievals are mostly drawn from literature or open-source software when appropriate, and have been tested, tuned, and modified to work with one another cohesively rather than using isolated off-the-shelf algorithms. Incorporated algorithms include hydrometeor (echo) identification, rain water content, raindrop mass-weighted mean diameter (gamma size distribution assumption), and rainfall rate (QPE). Taranis data sets exist for CSAPR2 PPI, HSRHI, and sector RHI scans. Cartesian-gridded data sets were also produced as well as a near-surface rain rate retrieval. More details can be found in the README.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ACE-ENA: Fast Liquid Water Content

These data were collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic field campaign as part of ARM Aerial Facility deployment (ACE-ENA, https://www.arm.gov/research/campaigns/aaf2017ace-ena). The ARM Aerial Facility Gulfstream-1 was deployed at Lajes Air Base (IATA: TER, ICAO: LPLA), on Terceira Island in the Azores, Portugal, for the two Intensive Observation Periods from June 20 through July 22, 2017 (IOP#1) and from January 11 through February 22, 2018 (IOP#2). The G-1 aircraft performed 20+19 research flights over the ARM Eastern North Atlantic (ENA) site and Atlantic Ocean to measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50 Hz, 10 Hz, and 1 Hz.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CACTI: Fast Liquid Water Content

These data were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI; https://www.arm.gov/research/campaigns/amf2018cacti ) field campaign in the Sierras de Córdoba mountain range of north-central Argentina as part of the ARM Aerial Facility (AAF) deployment. The ARM Aerial Facility Gulfstream-1 was operated from Las Higueras Airport (IATA: RCU, ICAO: SAOC), Río Cuarto, Córdoba, Argentina, for the Intensive Observation Period (IOP) from Nov. 1 through Dec. 15, 2018. The G-1 aircraft performed 22 research flights over the first ARM Mobile Facility (AMF1) location in the Sierras de Córdoba mountain range to measure atmospheric state and turbulence, cloud water content and droplet size distributions, aerosol precursor gases, and aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50Hz, 10Hz, and 1Hz.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

KAZR-based snowfall rates during SAIL

This data set provides KAZR radar based retrievals of snowfall rates for the two cold periods of the SAIL campaign (NOV 2021- APR 2022 and NOV 2022 - APR 2023).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ERA5-Land Data for LASSO-CACTI Overview Paper

The European Centre for Medium-Range Weather Forecasts (ECMWF) generated a soil reanalysis dataset for the land component of the fifth generation of European ReAnalysis (ERA5), referred to as ERA5-Land. This is a model-generated dataset, with the original version available for the period 1950 to present. The version archived in this DOE ARM product is a subset of the data is for the period of the CACTI field campaign plus several preceding months, specifically from August 1, 2018 through March 22, 2019 with hourly intervals. The ARM copy is also a sub-region of the original global product; the ARM copy is for -60 to -5 °N by -105 to -30 °W. Only variables necessary to drive the WRF-Hydro model are included, which are the 2-m temperature and specific humidity, 10-m wind components, surface pressure, rain rate, and downward surface short and longwave radiation. These data have been obtained from the Copernicus Data Store.

10m wind u-component↗
DOE OSTI2024

NPFTURBULENCE: Turbulent Parameters by airborne measurements

The original data were collected during the field campaign of “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence) over the Atmospheric Radiation Measurement (ARM) user facility's Southern Great Plains (SGP) atmospheric observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a comprehensive collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe. For user convenience, the current data set includes several parameters commonly used in turbulent research for normalization and/or scaling: atmospheric boundary-layer height, surface conditions, convective scales for temperature, and velocity, etc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NPFTURBULENCE: Fast Response Temperature by Airborne Measurements

The original data were collected during the field campaign of the “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence; https://www.arm.gov/publications/programdocs/doe-sc-arm-25-004.pdf ) over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration and size distribution. The current dataset presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current dataset were the fine wire thermocouple probe, Pitot-static system (part of the UAS control), and infrared gas analyzer sensor for H2O and CO2 (LI-840A). All parameters used in the temperature calculations (static and dynamic pressure, absolute humidity in form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature↗
DOE OSTI2024

The BIRDIES Experiment: Measuring Beryllium Isotopes to Resolve Dynamics in the Stratosphere

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.

58 GEOSCIENCES↗
DOE OSTI2025

Application of PRIM for understanding patterns in carbon dioxide model-observation differences

Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.

Gerken, Tobias [James Madison Univ., Harrisonburg,↗
DOE OSTI2025

Computational Prediction of Infrasound Arrival Times and Directions from Stationary and Moving Impulsive Sources

This report addresses the need to predict infrasound signal arrival times and back azimuths at monitoring stations, enabling more focused and efficient searches within recorded waveform data. The primary challenge is estimating expected signal arrival windows for stationary and moving acoustic sources, such as chemical explosions, volcanic eruptions, meteoroids, and spacecraft re-entry events. To address this challenge, a reproducible methodology is described that uses simplified propagation speeds for boundary layer, tropospheric, stratospheric, and thermospheric atmospheric waveguides. While the Python source code itself is not freely available, this document provides detailed, step-by-step instructions, and equations enabling users to replicate and adapt the method independently. The method reliably predicts signal arrival intervals and back azimuths, thereby supporting rapid detection and accurate interpretation of infrasound events. Results demonstrate that this method effectively identifies plausible signal arrival intervals and directions, facilitating faster event detection and more reliable interpretation. This methodology directly supports atmospheric monitoring, planetary defense, and forensic analysis of explosive atmospheric events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

E3SMv3 ‘Nephele’ Perturbed Parameter Ensemble Value-Added Product for ENA, SGP, NSA, and Global Means

Processed output from the E3SMv3 Nephele perturbed parameter ensemble (PPE). This product contains global means of present-day (using 2010 aerosol forcings) and preindustrial (using 1850 aerosol forcings) monthly and daily global-mean quantities, as well as hourly mean quantities at the E3SMv3 model grid cell closest to the ENA, SGP, and NSA ARM sites. In this PPE, the E3SMv3 model was run for 27 months in an atmosphere-only configuration with free tropospheric winds nudged to reanalysis. Each ensemble member represents a unique combination of 25 model parameter values (in the microphysics, convective microphysics, and aerosol schemes) that were perturbed randomly and simultaneously. The E3SMv3 default configuration is included as member 0. See https://doi.org/10.22541/essoar.174907165.57104591/v1 (in review) for more information on the Nephele PPE and the perturbed parameters.

Model atmospheric temperature↗
DOE OSTI2026

Numerical Water Tracers in the Atmospheric Component of the Energy Exascale Earth System Model: Implementation and Changes in Moisture Origin

Numerical water tracers are implemented in the Energy Exascale Earth System Model version 2. Simulations performed with the water‐tag‐enabled model for both pre‐industrial and future greenhouse gas concentrations reveal a marked increase in the role of mid‐latitude and southern subtropical regions as exporters of atmospheric moisture—to the extratropical upper troposphere and the tropical free troposphere. For the latter, the northward shift of the Intertropical Convergence Zone increases cross‐hemispheric transport of subtropical water vapor to the Northern Hemisphere. In the polar regions, most of the lower tropospheric moistening instead arises from increases in local evaporation. These findings illustrate the utility of the water tags, underscore critical changes in global hydrologic cycle, and provide insight into atmospheric dynamics under future climate scenarios. For applications when a global grid is desired, we additionally propose a novel statistical reconstruction, based on copula modeling, of the joint distribution of origin of water vapor, which reduces the number of tracers from order $\mathcal{O}\left({n}^{2}\right)$to order $\mathcal{O}(n)$, substantially ameliorating the considerable computational cost of water tracers. This statistical reconstruction is particularly beneficial to the interpretation of the relationship between latitude and longitude of origin of moisture over the tropical oceans and in the lower troposphere over land.

copula modeling↗
DOE OSTI2025

Turbulent Parameters by airborne measurements over BNF in March 2025

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 10 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Atmosphere↗
DOE OSTI2025

CHELAX-BNF: Turbulent Parameters by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 through June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Aircraft Integrated Meteorological Measurement Sys↗
DOE OSTI2025

CHELAX-BNF: Fast Response Temperature by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 to June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current data set were the fine wire thermocouple probe, the Aircraft Integrated Meteorological Measurement System (AIMMS-30), the Pitot-static system (part of UAS flight control), and the infrared gas analyzer sensor for H2O and CO2 (LI-840). All parameters used in temperature calculations (static pressure, True Air Speed, and absolute humidity in the form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature, fast response↗
DOE OSTI2025

Fast Response Temperature by airborne measurements over BNF

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 9 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current data set were the fine wire thermocouple probe, the Aircraft Integrated Meteorological Measurement System (AIMMS-30), the Pitot-static system (part of UAS flight control), and the infrared gas analyzer sensor for H2O and CO2 (LI-840). All parameters used in temperature calculations (static pressure, True Air Speed, and absolute humidity in form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature, fast response↗
DOE OSTI2026

Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability

Accurate estimation of convective boundary layer height (CBLH) is vital for weather, climate, and air quality modeling. Machine learning (ML) shows promise in CBLH prediction, but input parameter selection often lacks physical grounding, limiting generalizability. This study introduces a novel ML framework for CBLH prediction, integrating thermodynamic constraints and the diurnal CBLH cycle as an implicit physical guide. Boundary layer growth is modeled as driven by surface heat fluxes and atmospheric heat absorption represented with the low tropospheric stability, using the diurnal cycle as input and output. TPOT and AutoKeras are employed to select optimal models, validated against Doppler lidar-derived CBLH data, achieving an R 2 of 0.84 across untrained years. Comparisons of eddy covariance (ECOR) and energy balance Bowen ratio (EBBR) flux measurements show the same prediction capability. Models trained on the ARM SGP C1 site with ECOR data and tested at E37 and E39 yield R 2 values of 0.79 and 0.81, respectively, demonstrating their adaptability. The ML model trained with all sites' data slightly enhances the performance compared with ML models trained over single-site data. The interquartile range for predicted CBLH is consistently narrower than that for DL-derived CBLH, reflecting lower variability in predicted CBLH compared to DL-derived CBLH, which is influenced by additional factors, which are not well represented with the model inputs. The model's generalizability across multiple sites at the ARM SGP site demonstrates its potential for transfer to greater distances, offering a scalable approach for enhancing boundary layer parameterization in atmospheric models.

Chu, Yufei [Stony Brook Univ., NY (United States)]↗
DOE OSTI2025

Unraveling Electronic Effects that Influence the Bimolecular Chemistry of Fluorinated Criegee Intermediates

Ozonolysis is important for the removal of unsaturated volatile organic compounds emitted into the Earth's atmosphere. The alkene + ozone reaction (alkene ozonolysis) forms a carbonyl oxide – a Criegee intermediate (CI). CIs are interesting from an atmospheric chemistry perspective. They are implicated in enhancing the oxidizing capacity of the troposphere and in secondary organic aerosol formation. CIs may participate in bimolecular reactions with trace atmospheric vapors like water and methanol. Here, the chemistry of the two isomers of CFHOO and of CF 3 CHOO with water, water dimer, and methanol is explored. The present study confirms that the syn-conformer is the minimum energy structure for both CIs and that the reactions of anti-CFHOO display slightly lower activation energies cf. syn-CFHOO, thus promoting faster reaction. For both syn- and anti-CFHOO, the energy barrier in the pathway to adding water, water dimer, or methanol is lower—and the overall reaction exoergicity greater—than for the corresponding reactions involving the nonfluorinated analogue, CH 2 OO. Here, the corresponding bimolecular reaction rates are thus predicted to be faster for CFHOO than CH 2 OO. Similar reactivity trends are found when comparing the same reactions of syn-CF 3 CHOO, cf. syn-CH 3 CHOO, but not when comparing the energetics of the reactions involving anti-CF 3 CHOO cf. anti-CH 3 CHOO.

Guidry, Lily M. [University of Louisiana at Lafaye↗