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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Mid-Latitude Temperatures at 87 km: Results From Multi-Instrument Fourier Analysis

Using a novel Fourier fitting method we combine two years of mid-latitude temperature measurements at 87 km from the High Resolution Doppler Imager, the Colorado State University lidar, and the Peach Mountain Interferometer. After accounting for calibration bias, significant local-time variations on the order of 10 K were observed. Stationary planetary waves with amplitudes up to 10 K were observed during winter, with weaker wave amplitudes occurring during other seasons. Because of calibration biases among these instruments, we could estimate the annual mean temperature to no better than 193.5 plus or minus 8.5 K.

FOURIER ANALYSIS↗
DOE OSTI2024

Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer

A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined, and transversal temporal autocovariance functions (ACFs) are determined for deriving the dissipation and molecular destruction rates. These are fundamental loss terms in the TKE as well as the potential temperature and mixing ratio variance equations. These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless of whether 1 or 10 s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations in vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ϵ m ≃ 7 x 10 -4 g 2 kg −2 s −1 for mixing ratio and ϵ θ ≃ 1.6 x 10 -3 K 2 s −1 for potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts to ≃ 10 -2 m 2 s −3 . We also demonstrate that the vertical wind ACF coefficient k w ∝ $\overline{w'^{2}}$ and the TKE dissipation ϵ ∝ ($\overline{w'^{2}}$) 3/2 . For the molecular destruction rates, we show that ϵ m ∝ $\overline{m'^{2}}$ ($\overline{w'^{2}}$) 1/2 and ϵ θ ∝ $\overline{θ'^{2}}$ ($\overline{w'^{2}}$) 1/2 . These equations can be used for parameterizations of ϵ, ϵ m , and ϵ θ . All noise error bars are derived by error propagation and are small enough to compare the results with previous observations and large-eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large-eddy simulations.

dissipation rate↗
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 NTRS1986

Lidar remote sensing from space: NASA's plans in the Earth sciences

A multidisciplinary study of the Earth System to provide a better understanding of the complex interrelated processes involved in the system, the Earth Observing System (EOS), is being developed. Capabilities of the Space Station, both the polar orbiting platform and the lower inclination platforms, will be used to accommodate a number of large active and/or passive sensors. Two lidar instruments being considered as part of the Eos payload are the Lidar Atmospheric Sounder and Altimeter (LASA) and the Laser Atmospheric Wind Sounder (LAWS). The LASA instrument is separable into two portions: the atmospheric sounder component and the retroranging component. The LASA atmospheric sounder will sample the spatial distribution of several atmospheric parameters. The retroranging component will be used to determine the precise three-dimensional position of specifically placed retro-reflectors and to sense how these retro-reflectors change position over monthly to yearly time periods. The LAWS utilizes a lidar system capable of measuring the Doppler shift in the backscattered intensity to determine the wind velocity profile.

Curran, R. J.↗
NASA NTRS2005

Development of High Altitude UAV Weather Radars for Hurricane Research

A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.

Heymsfield, Gerald↗
NASA NTRS1994

Differential absorption lidar measurements of atmospheric water vapor using a pseudonoise code modulated AlGaAs laser

Lidar measurements using pseudonoise code modulated AlGaAs lasers are reported. Horizontal path lidar measurements were made at night to terrestrial targets at ranges of 5 and 13 km with 35 mW of average power and integration times of one second. Cloud and aerosol lidar measurements were made to thin cirrus clouds at 13 km altitude with Rayleigh (molecular) backscatter evident up to 9 km. Average transmitter power was 35 mW and measurement integration time was 20 minutes. An AlGaAs laser was used to characterize spectral properties of water vapor absorption lines at 811.617, 816.024, and 815.769 nm in a multipass absorption cell using derivative spectroscopy techniques. Frequency locking of an AlGaAs laser to a water vapor absorption line was achieved with a laser center frequency stability measured to better than one-fifth of the water vapor Doppler linewidth over several minutes. Differential absorption lidar measurements of atmospheric water vapor were made in both integrated path and range-resolved modes using an externally modulated AlGaAs laser. Mean water vapor number density was estimated from both integrated path and range-resolved DIAL measurements and agreed with measured humidity values to within 6.5 percent and 20 percent, respectively. Error sources were identified and their effects on estimates of water vapor number density calculated.

Rall, Jonathan A. R.↗
NASA NTRS1991

CLASS: Coherent Lidar Airborne Shear Sensor. Windshear avoidance

The coherent lidar airborne shear sensor (CLASS) is an airborne CO2 lidar system being designed and developed by Lockheed Missiles and Space Company, Inc. (LMSC) under contract to NASA Langley Research Center. The goal of this program is to develop a system with a 2- to 4-kilometer range that will provide a warning time of 20 to 40 seconds, so that the pilot can avoid the hazards of low-altitude wind shear under all weather conditions. It is a predictive system which will warn the pilot about a hazard that the aircraft will experience at some later time. The ability of the system to provide predictive warnings of clear air turbulence will also be evaluated. A one-year flight evaluation program will measure the line-of-sight wind velocity from a wide variety of wind fields obtained by an airborne radar, an accelerometer-based reactive wind-sensing system, and a ground-based Doppler radar. The success of the airborne lidar system will be determined by its correlation with the windfield as indicated by the onboard reactive system, which indicates the winds actually experienced by the NASA Boeing 737 aircraft.

Targ, Russell↗
DOE OSTI2020

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud resolving models (CRMs) to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (radar and lidar) products. CR-SIM allows direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multi-sensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar-lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate the application of CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are publicly available to the scientific community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Laser applications to atmospheric sciences: A bibliography

A bibliography is given of 1460 references of the applications of lasers to atmospheric sciences. The subjects covered include: aerosols; clouds; the distribution and motion of atmospheric natural and man-made constituents; winds; temperature; turbulence; scintillation; elastic, Raman and resonance scattering; fluorescence; absorption and transmission; the application of the Doppler effect and visibility. Instrumentation, in particular lidar, is included, also data handling, and interpretation of the data for meteorological processes. Communications, geodesy and rangefinding are not included as distinct areas. The application to the atmosphere is covered, but not the ocean or its surface.

Harris, F. S., Jr.↗
NASA NTRS1988

Wind measurements by electromagnetic probes

The emerging technology of electromagnetic probing of the atmosphere to measure winds used in a space vehicle ascent winds load calculations is presented. The frequency range, altitude, and resolution for the following probes are presented: lidars, microwave radars, and clear-air Doppler radars (popularly known as wind profilers). The electromagnetic probing of the atmosphere by clear-air radars and lasers is the new technology to supplement balloon-borne wind sensors used to determine ascent wind loads of space vehicles. The electromagnetic probes measure the wind velocity using the Doppler effect. This is the radar technology used in MSFC's Radar Wind Profiler, and is similar to the technology used in conventional Doppler systems except that the frequency is generally lower, antenna is bigger, and dwell time much longer. Designed for unattended and automated instrumentation in providing measurements of the wind in the troposphere, the profiler employs Doppler radar technology and is currently being put in operation at NASA Kennedy Space Center, Florida.

Susko, Michael↗
NASA NTRS1992

Coherent summation of spatially distorted laser Doppler signals by using a two-dimensional heterodyne detector array

Phase-sensitive coherent summation of individual heterodyne detector array signals was demonstrated for the enhanced detection of spatially distorted laser Doppler returns. With the use of a 2 x 2 heterodyne detector array, the phase and amplitude of a time-varying speckle pattern was detected, and the signal-to-noise ratio of the Doppler shift estimate was shown to be improved by a factor of 2, depending on the extent of spatial coherence loss. These results are shown to agree with a first-order analysis and indicate the advantage of coherent summation for both short-range laser Doppler velocimetry and long-range atmospheric coherent lidar.

Chan, Kin P.↗
NASA NTRS2001

Operational Performance of Sensor Systems Used to Determine Atmospheric Boundary Layer Properties as Part of the NASA Aircraft Vortex Spacing System Project

There has been a renewed interest in the application of remote sensor technology to operational aviation and airport-related activities such as Aircraft Vortex Spacing System (AVOSS). Radio Acoustic Sounding Systems (RASS), Doppler-acoustic sodars, Ultrahigh Frequencies (UHF) profilers and lidars have many advantages in measuring wind and temperature profiles in the lower atmospheric boundary layer since they can operate more or less continuously and unattended; however, there are limitations in their operational use at airports. For example, profilers deteriorate (limited altitude coverage or missing) in moderate or greater rain and can be affected by airplane targets in their field of view. Sodars can handle precipitation better but are affected by the high noise environments of airports and strong winds. Morning temperature inversions typically limit performance of RASS, sodars and profilers. Fog affects sonic anemometers. Lidars can have difficulties in clouds, fog or heavy precipitation. Despite their limitations these sensors have proven useful to provide wind and temperature profiles for AVOSS. Capabilities and limitations of these and other sensors used in the AVOSS program are discussed, parameter settings for the sensor systems are documented, and recommendations are made for the most cost-effective group of sensors for the future. The potential use of specially tuned dynamic forecast models and measurements from landing and departing aircraft are addressed.

Zak, J. Allen↗
NASA NTRS2001

Facility for Atmospheric Remote Sensing (FARS) Cirrus Measurements for FIRE III

From our Facility of Atmospheric Remote Sensing (FARS) in Salt Lake City, Utah, we have since December 1986 collected ground-truth data from cirrus clouds for aiding in satellite cloud detection algorithm testing and improvement, the development of cirrus radiative parameterizations, and basic cloud physics research. This research program has involved data regularly collected with a polarization ruby (0.694 micrometer) lidar system and a suit of passive (visible, infrared, and microwave) radiometers, although a number of comprehensive cloud case studies using the full compliment of remote sensors (i.e., 95 GHz polarimetric Doppler radar and high-resolution dual-wavelength Polarization Diversity Lidar, PDL) have also been obtained. Since our program began, a total of approximately 3,200 hours of lidar/radiometer data have been collected, resulting in a uniquely comprehensive, and climatologically-representative, high cloud dataset. In this report, we highlight our research accomplishments over the period of performance of this grant.

Sassen, Kenneth↗
NASA NTRS1990

Two-frequency lidar technique for mesospheric Na temperature measurements

This paper describes a new two-frequency lidar for measuring Na temperature profiles. The laser oscillator is tuned to the two operating frequencies by observing the Doppler-free structure of the Na D2 fluorescence spectrum in a vapor cell. The lidar technique and initial observations of the temperature profile between 82 and 102 km are described. Absolute temperature accuracies at the Na layer peak of better than + or - 3 K with a vertical resolution of 1 km and an integration period of approximately 5 min were achieved.

She, C. Y.↗
NASA NTRS2011

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

Busnardo, David M.↗
NASA NTRS1995

High Spectral Resolution Lidar measurements of extinction and particle size in clouds

The spectral width of light backscattered from molecules is increased due to Doppler shifts caused by the thermal motion of the molecules. The thermal motion of aerosol and cloud particles is much slower and the backscatter spectrum is nearly unchanged. The University of Wiconsin High Spectral Resolution Lidar (RSRL) measures optical properties of the atmosphere by separating the Doppler-broadened molecular backscatter return from the unbroadened aerosol return. The molecular backscatter cross section can be calculated from the molecular density profile. Thus, observing the magnitude of the measured molecular signal relative to the computed profile allows unambiguous measurement of the atmospheric extinction profile. The ratio of the aerosol return to the molecular return along with the computed molecular cross section provides direct measurement of the aerosol backscatter cross section.

Eloranta, E. W.↗
NASA NTRS2011

A Comparison of Snow Depth on Sea Ice Retrievals Using Airborne Altimeters and an AMSR-E Simulator

A comparison of snow depths on sea ice was made using airborne altimeters and an Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) simulator. The data were collected during the March 2006 National Aeronautics and Space Administration (NASA) Arctic field campaign utilizing the NASA P-3B aircraft. The campaign consisted of an initial series of coordinated surface and aircraft measurements over Elson Lagoon, Alaska and adjacent seas followed by a series of large-scale (100 km ? 50 km) coordinated aircraft and AMSR-E snow depth measurements over portions of the Chukchi and Beaufort seas. This paper focuses on the latter part of the campaign. The P-3B aircraft carried the University of Colorado Polarimetric Scanning Radiometer (PSR-A), the NASA Wallops Airborne Topographic Mapper (ATM) lidar altimeter, and the University of Kansas Delay-Doppler (D2P) radar altimeter. The PSR-A was used as an AMSR-E simulator, whereas the ATM and D2P altimeters were used in combination to provide an independent estimate of snow depth. Results of a comparison between the altimeter-derived snow depths and the equivalent AMSR-E snow depths using PSR-A brightness temperatures calibrated relative to AMSR-E are presented. Data collected over a frozen coastal polynya were used to intercalibrate the ATM and D2P altimeters before estimating an altimeter snow depth. Results show that the mean difference between the PSR and altimeter snow depths is -2.4 cm (PSR minus altimeter) with a standard deviation of 7.7 cm. The RMS difference is 8.0 cm. The overall correlation between the two snow depth data sets is 0.59.

Cavalieri, D. J.↗