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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Comparison of vertical velocities analyzed by a numerical model and measured by a VHF wind profiler

The use of wind profilers for measuring vertical velocities in the troposphere and lower stratosphere is potentially of great interest for verification of forecasts, diagnosis of mesoscale circulations, and studies of wave motions. The studies of profiler vertical velocities to date have shown that the observed patterns of ascent and subsidence are reasonable when compared to the synoptic conditions. However, difficulties arise when a direct verification of the profiler vertical winds is sought. Since no other technique can measure the vertical velocities over the same height range and with the same claimed accuracy as the profilers, direct comparisons are impossible. The only alternative is to compare the measurements to analyzed vertical velocity fields. Here, researchers compare vertical measurements made with the SOUSY VHF radar over a period of 11 days at the beginning of November 1981 to the analyzed vertical velocities produced by the European Center for Medium-range Weather Forecasting (ECMWF) model for grid points near the radar site.

Larsen, M. F.↗
NASA NTRS1998

Design and Performance of a Miniature Lidar Wind Profiler (MLWP)

The directional velocity of the wind is one of the most critical components for understanding meteorological and other dynamic atmospheric processes. Altitude-resolved wind velocity measurements, also known as wind profiles or soundings, are especially necessary for providing data for meteorological forecasting and overall global circulation models (GCM's). Wind profiler data are also critical in identifying possible dangerous weather conditions for aviation. Furthermore, a system has yet to be developed for wind profiling from the surface of Mars which could also meet the stringent requirements on size, weight, and power of such a mission. Obviously, a novel wind profiling approach based on small and efficient technology is required to meet these needs. A lidar system based on small and highly efficient semiconductor lasers is now feasible due to recent developments in the laser and detector technologies. The recent development of high detection efficiency (50%), silicon-based photon-counting detectors when combined with high laser pulse repetition rates and long receiver integration times has allowed these transmitter energies to be reduced to the order of microjoules per pulse. Aerosol lidar systems using this technique have been demonstrated for both Q-switched, diode-pumped solid-state laser transmitters (lambda = 523 nm) and semiconductor diode lasers (lambda = 830 nm); however, a wind profiling lidar based on this technique has yet to be developed. We will present an investigation of a semiconductor-laser-based lidar system which uses the "edge-filter" direct detection technique to infer Doppler frequency shifts of signals backscattered from aerosols in the planetary boundary layer (PBL). Our investigation will incorporate a novel semiconductor laser design which mitigates the deleterious effects of frequency chirp in pulsed diode lasers, a problem which has limited their use in such systems in the past. Our miniature lidar could be used on a future Mars lander and perhaps find its own niche in terrestrial applications due to its potential low cost an small size.

Cornwell, Donald M., Jr.↗
NASA NTRS1993

Wind persistence from 2-18 km using a wind profiler

Existing techniques for quantifying the effects of temporal wind variability on launch vehicles employ very limited sets of wind profile pairs derived from rising balloons. Variability due to spatial differences between the drifting balloon and a vehicle trajectory are traditionally ignored. The authors developed a technique to extract high quality wind profiles at frequent time intervals from a Doppler Radar Wind Profiler. This technique was applied to a limited number of data sets gathered from December 1990 through March 1992 at the Kennedy Space Center using the NASA 50 Mhz Wind Profiler. The authors then used these derived wind profiles to demonstrate techniques for quantifying the effects of temporal and spatial variability.

Wilfong, Timothy L.↗
NASA NTRS2014

Transition Marshall Space Flight Center Wind Profiler Splicing Algorithm to Launch Services Program Upper Winds Tool

NASAs LSP customers and the future SLS program rely on observations of upper-level winds for steering, loads, and trajectory calculations for the launch vehicles flight. On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds and provide forecasts to the launch team via the AMU-developed LSP Upper Winds tool for launches at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station. This tool displays wind speed and direction profiles from rawinsondes released during launch operations, the 45th Space Wing 915-MHz Doppler Radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP, and output from numerical weather prediction models.The goal of this task was to splice the wind speed and direction profiles from the 45th Space Wing (45 SW) 915-MHz Doppler radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP at altitudes where the wind profiles overlap to create a smooth profile. In the first version of the LSP Upper Winds tool, the top of the 915-MHz DRWP wind profile and the bottom of the 50-MHz DRWP were not spliced, sometimes creating a discontinuity in the profile. The Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) created algorithms to splice the wind profiles from the two sensors to generate an archive of vertically complete wind profiles for the SLS program. The AMU worked with MSFC NE personnel to implement these algorithms in the LSP Upper Winds tool to provide a continuous spliced wind profile.The AMU transitioned the MSFC NE algorithms to interpolate and fill data gaps in the data, implement a Gaussian weighting function to produce 50-m altitude intervals in each sensor, and splice the data together from both DRWPs. They did so by porting the MSFC NE code written with MATLAB software into Microsoft Excel Visual Basic for Applications (VBA). After testing the new algorithms in stand-alone VBA modules, the AMU replaced the existing VBA code in the LSP Upper Winds tool with the new algorithms. They then tested the code in the LSP Upper Winds tool with archived data. The tool will be delivered to the 45 WS after the 50-MHz DRWP upgrade is complete and the tool is tested with real-time data. The 50-MHz DRWP upgrade is expected to be finished in October 2014.

Space launch↗
DOE OSTI2021

Radar - ANL Wind Profiler, Walla Walla - Raw Data

**Winds** 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 typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature** To measure atmospheric temperature, a radio acoustic sound system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60-m up to 3.5k m for the 449 MHz.

17 WIND ENERGY↗
NASA NTRS1989

Progress in the use of wind profiling radars for Shuttle launch support

The use of wind profiling radars during Space Shuttle launches is examined. The way in which wind measurements are used in the launch process is described, including monitoring the day of launch winds, flight simulations, and the improvement of the data base which provides the mean winds and monthly variability of wind profiles. Results are presented from tests of two profilers conducted during March and April, 1985. The wind profiling characteristics of three profilers are listed and the winds provided by the profilers are compared to Jimsphere winds.

Smith, Steve A.↗
DOE OSTI2020

Sonic Detection and Ranging (SODAR) Wind Profiler Instrument Handbook

The SODAR (Sonic Detection and Ranging) wind profiler measures wind profiles and backscattered signal strength between (nominally) 15 meters (m) and 500 m. It operates by transmitting acoustic energy into the atmosphere and measuring the strength and frequency of backscattered energy. The strength of the backscattered signal is determined by the strength of temperature inhomogeneities with size on the order of 10 centimeters (cm). Assuming the scattering elements in the atmosphere are moving with the mean wind, the horizontal wind field can be derived. The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Mobile Facility (AMF) has a system developed by Scintec, Inc. that transmits a sequence of frequencies to enhance signal determination.

17 WIND ENERGY↗
NASA NTRS1989

Analysis of wind profile temporal variability

The modulus of the maximum wind change is used here to assess wind change at the Shuttle launch site at Kennedy Space Center. Empirical and theoretical distributions of the maximum wind change are presented, and the effect of wind profile smoothing on wind change distributions is analyzed. The capability of wind profile systems to measure extreme wind change is described.

Adelfang, Stanlay I.↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON8 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON7 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON5 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON4 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON2 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON6 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON3 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON1 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗
DOE OSTI2021

Sodar - Vaisala Triton Wind Profiler, AON9 - Raw Data

This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.

17 WIND ENERGY↗