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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Design and performance measurements of an airborne aerosol backscatter lidar

The global winds measurement application of coherent Doppler lidar requires intensive study of the global climatology of atmospheric aerosol backscatter at infrared wavelengths. An airborne backscatter lidar is discussed, which has been developed to measure atmospheric backscatter profiles at CO2 laser wavelengths. The instrument characteristics and representative flight measurement results are presented.

Menzies, Robert T.↗
NASA NTRS1992

Doppler lidar wind measurement with the edge technique

The edge technique is a new and powerful method for measuring small frequency shifts. Range resolved lidar measurements of winds can be made with high accuracy and high vertical resolution using the edge technique to measure the Doppler shift of an atmospheric backscattered signal from a pulsed laser. The edge technique can be used at near-infrared or visible wavelengths using well developed solid state lasers and detectors with various edge filters. In the edge technique, the laser frequency is located on the steep slope of the spectral response function of a high resolution optical filter. Due to the steep slope of the edge, very small frequency shifts cause large changes in measured signal. The frequency of the outgoing laser pulse is determined by measuring its location on the edge of the filter. This is accomplished by sending a small portion of the beam to the edge detection setup where the incoming light is split into two channels - an edge filter and an energy monitor channel. The energy monitor signal is used to normalize the edge filter signal for magnitude. The laser return backscattered from the atmosphere is collected by a telescope and directed through the edge detection setup to determine its frequency (location on the edge) in a similar manner for each range element. The Doppler shift, and thus the wind, is determined from a differential measurement of the frequency of the outgoing laser pulse and the frequency of the laser return backscattered from the atmosphere. We have conducted simulations of the performance of an edge lidar system using an injection seeded pulsed Nd:YAG laser at 1.06 microns. The central fringe of a Fabry-Perot etalon is used as a high resolution edge filter to measure the shift of the aerosol return.

Korb, C. Laurence↗
NASA NTRS1992

Multi-wavelength Airborne Lidar Intercomparisons of Aerosol and Cirrus Backscatter over the Pacific Ocean

Airborne CO2 and Nd:YAG lidar instruments were flown on the NASA DC-8 research aircraft during two extended missions over the Pacific. The objectives during these flights were to characterize aerosol backscatter levels at infrared wavelengths in relatively pristine regions of the troposphere, and to observe cloud effects on lidar signals. In addition, the three wavelength Nd:YAG data were processed using independent temperature profile information, in order to deduce the Rayleigh scattering component of the total backscatter at each wavelength. The data can be used to better understand the capabilities of various airborne or Earth-orbiting lidar designs to provide backscatter information from aerosols and clouds, or to provide Doppler or DIAL information from aerosol and cloud backscatter.

Menzies, Robert T.↗
NASA NTRS1997

Comparison of Lidar Backscatter with Particle Distribution and GOES-7 Data in Hurricane Juliette

Measurements of calibrated backscatter, using two continuous wave Doppler lidars operating at wavelengths 9.1 and 10.6 micrometers were obtained along with cloud particle size distributions in Hurricane Juliette on 21 September 1995 at altitude approximately 11.7 km. Agreement between backscatter from the two lidars and with the cloud particle size distribution is excellent. Features in backscatter and particle number density compare well with concurrent GOES-7 infrared images.

Jarzembski, Maurice A.↗
NASA NTRS2017

Observation of Polar Mesosphere Summer Echoes using the Northernmost MST Radar at Eureka (80 deg N)

We investigate long-term Polar Mesosphere Summer Echoes (PMSEs) observations conducted by the northern most geographically located MST radar at Eureka (80 deg N, 86 deg W). While PMSEs are a well recognized summer phenomenon in the polar regions, previous calibrated studies at Resolute Bay and Eureka using 51.5 MHz and33 MHz radars respectively, showed that PMSE backscatter signal strengths are relatively weak in the polar cap sites, compared to the auroral zone sites (Swarnalingam et al., 2009b; Singer et al., 2010). Complications arise with PMSEs in which the echo strength is controlled by the electrons, which are, in turn, influenced by heavily charged ice particles as well as the variability in the D-region plasma. In recent years, PMSE experiments were conducted inside the polar cap utilizing a 51 MHz radar located at Eureka. In this paper, we investigate calibrated observations, conducted during 2009-2015. Seasonal and diurnal variations of the backscatter signal strengths are discussed and compared to previously published results from the ALOMAR radar, which is a radar of similar design located in the auroral zone at Andenes, Norway (69 deg N, 16 deg E). At Eureka, while PMSEs are present with a daily occurrence rate which is comparable to the rate observed at the auroral zone site for at least two seasons, they show a great level of inter-annual variability. The occurrence rate for the strong echoes tends to be low. Furthermore, comparison of the absolute backscatter signal strengths at these two sites clearly indicates that the PMSE backscatter signal strength at Eureka is weak. Although this difference could be caused by several factors, we investigate the intensity of the neutral air turbulence at Eureka from the measurements of the Doppler spectrum of the PMSE backscatter signals. We found that the level of the turbulence intensity at Eureka is weak relative to previously reported results from three high latitude sites.

Swarnalingam, N.↗
NASA NTRS1987

Airborne microwave Doppler measurements of ocean wave directional spectra

A technique is presented for measuring ocean wave directional spectra from aircraft using microwave Doppler radar. The technique involves backscattering coherent microwave radiation from a patch of sea surface which is small compared to dominant ocean wavelengths in the antenna look direction, and large compared to these lengths in the perpendicular (azimuthal) direction. The mean Doppler shift of the return signal measured over short time intervals is proportional to the mean sea surface velocity of the illuminated patch. Variable sea surface velocities induced by wave motion therefore produce time-varying Doppler shifts in the received signal. The large azimuthal dimension of the patch implies that these variations must be produced by surface waves traveling near the horizontal antenna look direction thus allowing determination of the direction of wave travel. Linear wave theory is used to convert the measured velocities into ocean wave spectral densities. Spectra measured simultaneously with this technique and two laser profilometers, and nearly simultaneous with this technique and two laser profilometers, and nearly simultaneous with a surface buoy, are presented. Applications and limitations of this airborne Doppler technique are discussed.

Plant, W. J.↗
NASA NTRS1999

Analysis of Lidar Remote Sensing Concepts

Line of sight velocity and measurement position sensitivity analyses for an orbiting coherent Doppler lidar are developed and applied to two lidars, one with a nadir angle of 30 deg. in a 300 km altitude, 58 deg. inclination orbit and the second for a 45 deg. nadir angle instrument in a 833 km altitude, 89 deg. inclination orbit. The effect of orbit related effects on the backscatter sensitivity of a coherent Doppler lidar is also discussed. Draft performance estimate, error budgets and payload accommodation requirements for the SPARCLE (Space Readiness Coherent Lidar) instrument were also developed and documented.

Spiers, Gary D.↗
NASA NTRS1982

Beta experiment

A focused laser doppler velocimeter (LDV) system was developed for the measurement of atmospheric backscatter (beta) from aerosols at infrared wavelengths. A Doppler signal generator was used in mapping the coherent sensitive focal volume of a focused LDV system. System calibration data was analyzed during the flight test activity scheduled for the Beta system. These analyses were performed to determine the acceptability of the Beta measurement system's performance.

Source record↗
DOE OSTI2025

Sea spray aerosol production flux retrieval based on Doppler lidar measurements

Supermicron sea spray aerosols (SSA) play a crucial role in stratocumulus cloud microphysics and drizzle formation. However, our understanding of SSA's spatiotemporal distribution, production mechanisms, and fluxes in the marine boundary layer remains limited. This study introduces a novel approach to determine supermicron SSA production flux and number concentration at various heights above the ocean surface. Our method leverages Doppler lidar data, specifically attenuated backscatter and vertical velocity, collected at a 105 m range gate during the Eastern Pacific Clouds and Aerosols for Precipitation Experiment (EPCAPE) at Scripps Pier, La Jolla, California. To focus on nascent SSA, we analyzed data from periods with wind directions between 225° and 315° and wind speeds exceeding 4 m s −1 . Cloud and precipitation events were excluded using relative humidity, backscatter thresholds, and 2D Video Disdrometer observations. Results show that calculated supermicron SSA number concentrations at 105 m ranged from 0.26 to 2.93 cm −3 for surface wind speeds between 4 and 6 ms −1 . When exceeding the method's Limit of Detection, estimated production fluxes ranged from 0.20 to 1.53 cm −2 s −1 . This methodology has potential for application in various oceanic locations, likely enhancing our understanding of SSA's role in atmospheric processes and climate interactions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Atmospheric correlation-time measurements and effects on coherent Doppler lidar

The time for which the backscatter from an ensemble of atmospheric aerosol particles remains coherent was studied by using a pulsed TEA CO2 lidar with coherent detection. Experimental results are compared with predictions by using model pulse shapes appropriate for TEA CO2 laser transmitters. The correlation time of the backscatter return signal is important in studies of atmospheric turbulence and its effects on optical propagation and backscatter. Techniques for its measurement are discussed and evaluated.

Ancellet, Gerard M.↗
DOE OSTI2025

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗
DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Convective amplification of Type 1 irregularities in the equatorial electrojet

Wave propagation and refraction of Type 1 irregularities in the equatorial electrojet were investigated. Quantitative calculation of wave refraction in a model electrojet showed that the direction of wave refraction must change sign at one altitude. Waves propagating with the electrons rotate their wave vectors upwards in the upper electrojet and downwards in the lower electrojet during the day, and vice versa at night. Furthermore, the altitude region of largest linear growth rate is also the one with the weakest refraction rate. Consequently, computations of the ray-path integrated wave growth shows that this region would dominate the backscatter spectrum from the electrojet if linear theory were valid, and it is further noted that the maximum amplitude wave should have phase velocities exceeding the ion acoustic speed. It was concluded that propagation alone, without inclusion of nonlinear effects, cannot explain backscatter observations of a constant Doppler frequency shift given by the ion acoustic speed.

Lee, K.↗
NASA NTRS1973

Convective amplification of type I irregularities in the equatorial electrojet.

Wave propagation and refraction of 'type I' irregularities in the equatorial electrojet are investigated. Quantitative calculation of wave refraction in a model electrojet shows that the direction of wave refraction must change sign at one altitude. Waves propagating with the electrons rotate their wave vectors upward in the upper electrojet and downward in the lower electrojet during the day, and vice versa at night. Furthermore, the altitude region of largest linear growth rate is also the one with the weakest refraction rate. Consequently, computations of the ray-path integrated wave growth show that this region would dominate the backscatter spectrum from the electrojet if linear theory were valid, and it is further noted that the maximum amplitude wave should have phase velocities exceeding the ion acoustic speed. It is therefore concluded that propagation alone, without inclusion of nonlinear effects, cannot explain backscatter observations of a constant Doppler frequency shift given by the ion acoustic speed.

Lee, K.↗
NASA NTRS1986

LDA measurement of the passage flow field in a 3-D airfoil cascade

Three-dimensional internal flow computational models are currently being developed to predict the flow through turbomachinery blade rows. For these codes to be of quantitative value, they must be verified with data obtained in experiments which model the fundamental flow phenomena. In this paper, the complete three-dimensional flow field through a subsonic annular cascade of cambered airfoils is experimentally quantified. In particular, detailed three-dimensional data are obtained to quantify the inlet velocity profile, the cascade passage velocity field, and the exit region flow field. The primary instrumentation for acquiring these data is a single-channel Laser Doppler Anemometer operating in the backscatter mode, with chordwise distributions of airfoil surface static pressure taps also utilized. Appropriate data are correlated with predictions from the MERIDL/TSONIC codes.

Stauter, R. C.↗