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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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34 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Targeted Observations of Blowing Snow during SAIL (SAIL-TOBS) Field Campaign Report

Blowing snow research at high-latitude U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility observatories and mobile campaigns demonstrated the need for ground truth during falling and blowing snow events. The purpose of the Targeted Observations of Blowing Snow during SAIL (SAIL-TOBS) field campaign was to affordably deploy additional instruments to observe mixed-phase and frozen hydrometeors, including falling and blowing snow, during the second winter of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign. Instruments included two installations of the Open Snowflake Camera for Research and Education (OSCRE), one at the Gothic, Colorado main site (second ARM Mobile Facility [AMF2]) and a second at the Kettle Ponds external field site in support of the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign. Two FlowCapt FC4 acoustic mass flux sensors were also deployed at AMF2 in proximity to OSCRE on top of the instrumented hill (Figure 1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessment of North Slope of Alaska (NSA) Snow Monitoring Arrays

Arrays of instruments for monitoring winter precipitation (snowfall) and snow cover on the ground installed in 2017 at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska (NSA) C1 and at Oliktok Point sites became operational in 2018. In 2022, the instruments from Oliktok Point were moved to NSA E12, about 5.4 km south of NSA C1, where two arrays now operate. The instrument arrays monitor wind speed and direction, snow depth at multiple locations, the horizontal flux of blowing snow, and the number and fall speed of hydrometeors. The arrays are monitored using digital cameras. Collectively, the instruments produce a wealth of data on falling and accumulated snow, but, as with any instrument array, some data are more reliable and accurate than others. In this document, we present our findings on the efficacy, accuracy, and reliability of each type of instrument. Overall, a key finding is that no single instrument provides sufficient information to determine the source of falling snow particles nor the cause of changes in snow depth. However, if used in concert, the instruments produce a reliable understanding of the processes affecting the snow cover depth distribution and the true winter precipitation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Rapid SACR Observations of Convection at Bankhead National Forest (RAPID) Field Campaign Report

Improving our representation of convective cell processes requires better quantification of convective clouds throughout their entire life cycle. This includes gaining a clearer understanding of the controls on key convective cloud properties, such as updraft intensity, particle size distributions, rainfall rates, and hydrometeor species. Our inability to improve convective cloud process modeling stems, in part, from a limited understanding of convective cell properties, particularly given how rapidly these storms evolve. This lack of detailed observations in the most intense and organized convective storms is especially significant, as large errors remain in representing these clouds, which are critical for severe weather prediction and Earth system model performance. Cloud and precipitation radars are essential tools for studying cloud microphysics and dynamics, particularly in deeper convective clouds. The recent U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s third Mobile Facility (AMF3) Bankhead National Forest (BNF) deployment provides a unique opportunity to investigate important land–atmosphere interactions, as well as the environmental controls on deep convective cloud processes, in a location favorable for frequent convection. We operate the X/Ka-band Scanning ARM Cloud Radar (X/Ka SACR) using a scan strategy optimized to capture these rapidly evolving clouds and their properties, thereby improving studies of deep convective cloud processes. This effort is strengthened by a complementary and coordinated partnership with ongoing university and multi-agency radar activities collocated in north Alabama—a unique opportunity to examine clouds and precipitation from a lifetime-centric perspective.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

BLOC Site - Radar Wind Profiler / Derived Data Reformatted

A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data are typically sampled and averaged hourly or sub-hourly (15-min) and usually have 60-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz system. Both a high-resolution, lower height coverage mode and a low-resolution, higher height coverage mode are used to collect the data.

17 WIND ENERGY↗
DOE OSTI2025

NANT Site - Radar Wind Profiler / Derived Data Reformatted

A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data are typically sampled and averaged hourly or sub-hourly (15-min) and usually have 60-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz system. Both a high-resolution, lower height coverage mode and a low-resolution, higher height coverage mode are used to collect the data.

17 WIND ENERGY↗
DOE OSTI2025

Spatiotemporal Variability in Wind Turbine Blade Leading Edge Erosion

Wind turbine blade leading edge erosion (LEE) reduces energy production and increases wind energy operation and maintenance costs. Degradation of the blade coating and ultimately damage to the underlying blade structure are caused by collisions of falling hydrometeors with rotating blades. The selection of optimal methods to mitigate/reduce LEE are critically dependent on the rates of coating fatigue accumulation at a given location and the time variance in the accumulation of material stresses. However, no such assessment currently exists for the United States of America (USA). To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. Time series analyses indicate that up to one-third of blade coating lifetime is exhausted in just 360 5-min periods in the Southern Great Plains (SGP). Conversely, sites in the Pacific Northwest (PNW) exhibit the same level of coating lifetime depletion in over three times as many time periods. Thus, it may be more cost-effective to use wind turbine deregulation (erosion-safe mode) for damage reduction and blade lifetime extension in the SGP, while the application of blade leading edge protective measures may be more appropriate in the PNW. Annual total precipitation and mean wind speed are shown to be poor predictors of blade coating lifetime, re-emphasizing the need for detailed modeling studies such as that presented herein.

Pryor, Sara C. (ORCID:0000000348473440)↗
DOE OSTI2026

Response of marine post-frontal clouds to Gulf Stream variability

Understanding how Gulf Stream variation influences cloud morphology is critical for evaluating cloud feedback in the western North Atlantic Ocean and beyond, where mesoscale air-sea interactions dominate. This study investigates the impact of altered mean sea surface temperature (SST) and SST gradients on post-frontal cloud characteristics during cold-air outbreaks, using the Weather Research and Forecasting (WRF) model. Three sensitivity experiments are conducted: a control simulation (default SST), Plus4 (uniform SST increase of 4 K), and Gradplus (SST gradient enhanced by 25 %, centered around mean SST). Results reveal distinctly different responses in boundary layer dynamics and cloud macro-physics. In Plus4, a warmer and moister boundary layer reduces total cloud cover but promotes larger cloud sizes and elongated cloud streets, with diminished liquid water and enhanced ice-phase hydrometeors. Conversely, Gradplus amplifies impacts in the upwind colder SST regions, yielding a drier, colder boundary layer, weaker energy transport, and higher liquid water path but reduced ice water content and cloud lines. Tracer analysis highlights that SST modifications alter airmass sources near cloud tops due to the entrainment of ambient air, with Plus4 amplifying boundary layer contributions to cloud-top regions. These findings underscore the spatially varying effects of SST gradients and mean SST on cloud organization and microphysics, emphasizing the need to resolve ocean-atmosphere coupling in global models to improve the prediction of marine cloud feedback under warming scenarios.

AIR-SEA INTERACTION↗
DOE OSTI2024

Multifrequency radar observations of marine clouds during the EPCAPE campaign

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was a year-round campaign conducted by the US Department of Energy at the Scripps Institution of Oceanography in La Jolla, CA, USA, with a focus on characterizing atmospheric processes at a coastal location. The ground-based prototype of a new Ka-, W-, and G-band (35.75, 94.88, and 238.8 GHz) profiling atmospheric radar, named CloudCube, which was developed at the Jet Propulsion Laboratory, took part in the experiment during 6 weeks in March and April 2023. This article describes the unique data sets that were obtained during the field campaign from a variety of marine clouds and light precipitation. These are, to the best of the authors' knowledge, the first observations of atmospheric clouds using simultaneous multifrequency measurements including 238.8 GHz. These data sets therefore provide an exceptional opportunity to study and analyze hydrometeors with diameters in the millimeter- and submillimeter size range that can be used to better understand cloud and precipitation structure, formation, and evolution. The data sets referenced in this article are intended to provide a complete, extensive, and high-quality collection of G-band data in the form of Doppler spectra and Doppler moments. In addition, Ka-band and W-band reflectivity and Ka-, W-, and G-band reflectivity ratio profiles are included for several cases of interest on 6 different days.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators

Abstract. Supercooled liquid clouds are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We take advantage of the Macquarie Island Cloud and Radiation Experiment (MICRE) to perform an analysis of observed and simulated cloud processes over the Southern Ocean in a region and season dominated by supercooled liquid clouds. Using a single-column version of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), we compare two different cloud microphysical schemes to ground-based observations of cloud, precipitation, and radiation over a 2.5-month period (1 January–17 March 2017). Both schemes are able to reproduce aspects of the cloud and radiation observations during MICRE to within the uncertainty of the data when the thermodynamic profile is prescribed with relaxation. There are differences in water mass and representation of reflectivity between the schemes. A sensitivity study of the cloud microphysics schemes, one a bulk one-moment scheme and the other a two-moment scheme with prediction of mass and number, indicates that several key processes create differences between the schemes. Surface radiative fluxes and total water path are highly sensitive to the formation and fall speed of precipitation. The prediction of hydrometeor number with the two-moment scheme yields a better comparison with observed reflectivity and radiative fluxes, despite predicting higher liquid water contents than observed. With the two-moment scheme, we are also able to test the sensitivity of the results to the input of liquid cloud condensation nuclei (CCN) and ice nuclei (IN). The cloud properties and resulting radiative effects are found to be sensitive to the CCN and IN concentrations. More CCN and IN increase liquid and ice water paths, respectively. Thus, both the dynamic environment and aerosols, integrated through the cloud microphysics, are important for properly representing Southern Ocean cloud radiative effects.

58 GEOSCIENCES↗
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 OSTI2025

rwpvertvel

The 915-Mhz Radar Wind Profiler (RWP) has been configured to point vertically and operate in precipitation mode so as to measure Doppler velocity in the vertical direction, tracking the motion of hydrometeors as they fall, and enabling the calculation of vertical air motion within clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Co-Polarization Mode (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross Mode (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross-Polarization Model (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

minimpl (b1)

The micropulse lidar (MPL) is a ground-based, optical, remote-sensing system designed primarily to determine the altitude of clouds; however, it is also used for detection of atmospheric aerosols. The physical principle is the same as for radar. Pulses of energy are transmitted into the atmosphere; the energy scattered back to the transceiver is collected and measured as a time-resolved signal, thereby detecting clouds and aerosols in real time. From the time delay between each outgoing pulse and the backscattered signal, the distance to the scatterer is inferred. Post-processing of the lidar return characterizes the extent and properties of aerosols or other particles in a region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

thermocldphase

ARM VAP deriving the thermodynamic phase of water in clouds.

cloud↗