Results for “wind profile” — Page 6

NASA NTRS1985

Radar wind profilers

Continuous, automated measurement of tropospheric wind profiles with UHF and VHF Doppler radars has been demonstrated. Ground-based networks of these radars will be available as part of a global wind measurement system, and remote single stations could be built to further complement a spaceborne measurement device. A number of ground-based wind profilers will be in place by the time a space system is tested so the global wind measurement system should be designed with these ground-based profilers providing part of the picture.

Strauch, R. G.↗

DOE OSTI2025

WREF Halo Streamline scanning lidar / Derived data / High-frequency wind profiles

This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by the UC Davis scanning Lidar. The wind components (expressed as zonal, meridional and vertical) are retrieved through the algorithm of Paschke et al. (2015). The quality control of the radial wind speed is performed following the algorithm of Goring & Nikora (2002).

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NASA NTRS1985

Use of ground-based wind profiles in mesoscale forecasting

A brief review is presented of recent uses of ground-based wind profile data in mesoscale forecasting. Some of the applications are in real time, and some are after the fact. Not all of the work mentioned here has been published yet, but references are given wherever possible. As Gage and Balsley (1978) point out, sensitive Doppler radars have been used to examine tropospheric wind profiles since the 1970's. It was not until the early 1980's, however, that the potential contribution of these instruments to operational forecasting and numerical weather prediction became apparent. Profiler winds and radiosonde winds compare favorably, usually within a few m/s in speed and 10 degrees in direction (see Hogg et al., 1983), but the obvious advantage of the profiler is its frequent (hourly or more often) sampling of the same volume. The rawinsonde balloon is launched only twice a day and drifts with the wind. In this paper, I will: (1) mention two operational uses of data from a wind profiling system developed jointly by the Wave Propagation and Aeronomy Laboratories of NOAA; (2) describe a number of displays of these same data on a workstation for mesoscale forecasting developed by the Program for Regional Observing and Forecasting Services (PROFS); and (3) explain some interesting diagnostic calculations performed by meteorologists of the Wave Propagation Laboratory.

Schlatter, Thomas W.↗

NASA NTRS1991

Wind profile perturbation analysis for STS

Two case studies of the relationship between STS ascent structural loads and wind profile characteristics are described. In the first case study, a wind profile with relatively weak winds is used to demonstrate the importance of launch vehicle velocity relative to the air and its effect on loads. In the second study, a pair of wind profiles is used to show how the determination of load exceedances is strongly influenced by the wind load persistence allowances for the baseline and two day-of-launch (DOL) steering commands called I-LOADs. Characteristics of the wind profiles and associated trajectory variable and wind-sensitive load indicators are examined. Energy spectra of in-plane and out-of-plane wind component and a load indicator are presented. An analysis of load indicator sensitivity to wind perturbation energy in the 1600-6400 m wavelength band for baseline and DOL I-LOAD is described.

Adelfang, S. I.↗

NASA NTRS1979

Modified power law equations for vertical wind profiles

In an investigation of windpower plant siting, equations are presented and evaluated for a wind profile model which incorporates both roughness and wind speed effects, while retaining the basic simplicity of the Hellman power law. These equations recognize the statistical nature of wind profiles and are compatible with existing analytical models and recent wind profile data. Predictions of energy output based on the proposed profile equations are 10% to 20% higher than those made with the 1/7 power law. In addition, correlation between calculated and observed blade loads is significantly better at higher wind speeds when the proposed wind profile model is used than when a constant power model is used.

Spera, D. A.↗

DOE OSTI2021

Radar - ANL Wind Profiler with RASS, Yakima - 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.

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DOE OSTI2021

Radar - ANL Wind Profiler with RASS, Goldendale - 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↗

DOE OSTI2021

Radar - ESRL Wind Profiler with RASS, Prineville - 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↗

DOE OSTI2021

Radar - ESRL Wind Profiler with RASS, Troutdale - 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↗

DOE OSTI2021

Radar - ESRL Wind Profiler with RASS, Condon - 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 NTRS2011

Quality-Controlled Wind Data from the Kennedy Space Center 915 Megahertz Doppler Radar Wind Profiler Network

The National Aeronautics and Space Administration s (NASA) Kennedy Space Center (KSC) has installed a five-instrument 915-Megahertz (MHz) Doppler Radar Wind Profiler (DRWP) system that records atmospheric wind profile properties. The purpose of these profilers is to fill data gaps between the top of the KSC wind tower network and the lowest measurement altitude of the KSC 50-MHz DRWP. The 915-MHz DRWP system has the capability to generate three-dimensional wind data outputs from approximately 150 meters (m) to 6,000 m at roughly 15-minute (min) intervals. NASA s long-term objective is to combine the 915-MHz and 50-MHz DRWP systems to create complete vertical wind profiles up to 18,300 m to be used in trajectory and loads analyses of space vehicles and by forecasters on day-of-launch (DOL). This analysis utilizes automated and manual quality control (QC) processes to remove erroneous and unrealistic wind data returned by the 915-MHz DRWP system. The percentage of data affected by each individual QC check in the period of record (POR) (i.e., January to April 2006) was computed, demonstrating the variability in the amount of data affected by the QC processes. The number of complete wind profiles available at given altitude thresholds for each profiler in the POR was calculated and outputted graphically, followed by an assessment of the number of complete wind profiles available for any profiler in the POR. A case study is also provided to demonstrate the QC process on a day of a known weather event.

Dryden, Rachel L.↗

NASA NTRS1982

Sensitivity analysis of the space shuttle to ascent wind profiles

A parametric sensitivity analysis of the space shuttle ascent flight to the wind profile is presented. Engineering systems parameters are obtained by flight simulations using wind profile models and samples of detailed (Jimsphere) wind profile measurements. The wind models used are the synthetic vector wind model, with and without the design gust, and a model of the vector wind change with respect to time. From these comparison analyses an insight is gained on the contribution of winds to ascent subsystems flight parameters.

Smith, O. E.↗

NASA NTRS2017

Changes in Jupiter's Zonal Wind Profile Preceding and During the Juno Mission

We present five epochs of WFC3 HST Jupiter observations taken between 2009-2016 and extract global zonal wind profiles for each epoch. Jupiter's zonal wind field is globally stable throughout these years, but significant variations in certain latitude regions persist. We find that the largest uncertainties in the wind field are due to vortices or hot-spots, and show residual maps which identify the strongest vortex flows. The strongest year-to-year variation in the zonal wind profiles is the 24 deg N jet peak. Numerous plume outbreaks have been observed in the Northern Temperate Belt and are associated with decreases in the zonal velocity and brightness. We show that the 24 deg N jet peak velocity and brightness decreased in 2012 and again in late 2016, following outbreaks during these years. Our February 2016 zonal wind profile was the last highly spatially resolved measurement prior to Juno s first science observations. The final 2016 data were taken in conjunction with Juno's perijove 3 pass on 11 December 2016, and show the zonal wind profile following the plume outbreak at 24 deg N in October 2016.

Jupiter↗

NASA NTRS2004

Simulation of Wind Profile Perturbations for Launch Vehicle Design

Ideally, a statistically representative sample of measured high-resolution wind profiles with wavelengths as small as tens of meters is required in design studies to establish aerodynamic load indicator dispersions and vehicle control system capability. At most potential launch sites, high- resolution wind profiles may not exist. Representative samples of Rawinsonde wind profiles to altitudes of 30 km are more likely to be available from the extensive network of measurement sites established for routine sampling in support of weather observing and forecasting activity. Such a sample, large enough to be statistically representative of relatively large wavelength perturbations, would be inadequate for launch vehicle design assessments because the Rawinsonde system accurately measures wind perturbations with wavelengths no smaller than 2000 m (1000 m altitude increment). The Kennedy Space Center (KSC) Jimsphere wind profiles (150/month and seasonal 2 and 3.5-hr pairs) are the only adequate samples of high resolution profiles approx. 150 to 300 m effective resolution, but over-sampled at 25 m intervals) that have been used extensively for launch vehicle design assessments. Therefore, a simulation process has been developed for enhancement of measured low-resolution Rawinsonde profiles that would be applicable in preliminary launch vehicle design studies at launch sites other than KSC.

Adelfang, S. I.↗

NASA NTRS1985

Experimental radar Doppler wind profile measurements at Kennedy Space Center

A wind profile radar demonstration project was sponsored by the Space Transportation System (STS) Program Office to study the feasibility of incorporating continuous, high time resolution radar wind data into STS operations. This project required wind profile radars to be deployed in the vicinity of the Shuttle launch site into an environment quite unlike typical VHF profiler sites. Two 50 MHz radars were operated at the Kennedy Space Center in environments that were noisy in terms of RFI, large stationary ground clutter sources, non-stationary clutter sources, and heavy local aircraft traffic. Processing compensation for these operational constraints magnified design limitations of the research-level radars used in the demonstration. This report addresses the importance of system design for unique or particular applications with reference to finite radiation patterns, zero-Doppler processing, radar frequency, and beam pointing.

Jost, R. J.↗

NASA NTRS1981

Sensitivity analysis of the Space Shuttle to ascent wind profiles

This paper presents a parametric sensitivity analysis of the Space Shuttle Ascent flight to the wind profile. Engineering systems parameters are obtained by flight simulations using wind profile models and samples of detailed (Jimsphere) wind profile measurements. The wind models used are the synthetic vector wind model, with and without the design gust, and a model of the vector wind change with respect to time. From these comparison analyses an insight is gained on the contribution of winds to ascent subsystems flight parameters.

Smith, O. E.↗

NASA NTRS1986

The real-time use of wind profilers in nowcasting

The program for Regional Observing and Forecasting Services (PROFS) has been using wind profile data in experimental forecast applications for over two years, mostly in the form of real-time color displays on the PROFS forecast workstation. The most ambitious test of the workstation to date, the 1985 PROFS Real-Time Experiment (RT-85), ran from 15 May to 23 August, 1985. The use of wind profiler products during this and previous experiments is described. Data from the experimental profiler network in Colorado and from the profiler in Oklahoma are in the form of hourly averages. Arriving data frequently contain errors whose origins range from interference by aircraft in the beams to highway truck traffic. Most of the irregularities are apparent through visual inspection of profiler wind observations plotted on a time-height cross section, but this method of quality control is inadequate if the intended uses of the data involve numerical calculations.

Smith, T. L.↗

DOE OSTI2021

Radar - ESRL Wind Profiler with RASS, Wasco Airport - 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↗