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This dataset contains data from a NOAA Radar Wind Profiler located on Block island. Data can be found at https://psl.noaa.gov/data/obs/datadisplay/ with the following filters: Active Sites: bid Instrument: 915 MHz Wind Profiler Product: Radar 915MHz Sub-Hourly Weber Wuertz Wind
We present here the methodology and results of the Operational Acceptance Test (OAT) performed on the new Kennedy Space Center (KSC) 50-MHz Doppler Radar Wind Profiler (DRWP). On day-of-launch (DOL), space launch vehicle operators have used data from the DRWP to invalidate winds in prelaunch loads and trajectory assessments due to the DRWP's capability to quickly identify changes in the wind profile within a rapidly-changing wind environment. The previous DRWP has been replaced with a completely new system, which needs to undergo certification testing before being accepted for use in range operations. The new DRWP replaces the previous three-beam system made of coaxial cables and a copper wire ground plane with a four-beam system that uses Yagi antennae with enhanced beam steering capability. In addition, the new system contains updated user interface software while maintaining the same general capability as the previous system. The new DRWP continues to use the Median Filter First Guess (MFFG) algorithm to generate a wind profile from Doppler spectra at each range gate. DeTect (2015) contains further details on the upgrade. The OAT is a short-term test designed so that end users can utilize the new DRWP in a similar manner to the previous DRWP during mission operations at the Eastern Range in the midst of a long-term certification process. This paper describes the Marshall Space Flight Center Natural Environments Branch's (MSFC NE's) analyses to verify the quality and accuracy of the DRWP's meteorological data output as compared to the previous DRWP. Ultimately, each launch vehicle program has the responsibility to certify the system for their own use.
The radar wind profiler (RWP) is an active remote-sensing instrument that can routinely, and virtually unattended, observe wind and turbulence in the troposphere through scattering from clear-air irregularities of the atmospheric refractive index (Gage and Balsley 1978). The principle of Doppler radars in general is based on sending electromagnetic pulses in the vertical and several tilted directions (vertical and oblique beams) and measuring the signal that is scattered back by atmospheric turbulence at all heights and received at the antenna. The RWPs provides measurements of backscattered signal strength and wind profiles nominally between 0.1 km and 6 km. The RWP operation assumes that the wind field is homogeneous over the spatial separation of the antenna beams, which is a safe assumption under stable atmospheric conditions. However, the wind may be different between the beams due to significant changes in the wind field, resulting in erroneous wind calculations. Therefore, the radial measurements are averaged over a sufficient time period to validate the assumption of homogeneity.
Wind Profiler with Radio Acoustic Sounding System (RASS) data.
Wind Profiler with Radio Acoustic Sounding System (RASS) data.
Wind Profiler with Radio Acoustic Sounding System (RASS) data.
Wind Profiler with Radio Acoustic Sounding System (RASS) data.
Wind Profiler with Radio Acoustic Sounding System (RASS) data.
This paper documents the methodology and results of analyses used to certify the Kennedy Space Center (KSC) Tropospheric Doppler Radar Wind Profiler (TDRWP) as input to launch commit evaluations for the National Aeronautics and Space Administration’s (NASA) Space Launch System Program (SLSP). These analyses, and the requirements that they address, were designed by the Marshall Space Flight Center Natural Environments Branch (MSFC NE) to certify that the TDRWP provides data of sufficient accuracy and resolution for SLSP, and that the instrument provides enough reliability to support Day-of- Launch Initialization Loads Update (DOLILU) operations. On day-of-launch (DOL), space launch vehicle operators have used data from wind profilers to reverse a previous GO call in prelaunch loads and trajectory assessments due to the profiler’s capability to quickly identify changes in the wind profile within a rapidly changing wind environment. Certification of the TDRWP would allow SLSP to use DOL wind data generated by the TDRWP to design the vehicle trajectory and to verify trajectory and load constraints during the countdown for launch commit decision.
These data provide vertical mean profiles of wind and direction (30 min time step and 10 m range gate).
The data provide vertical mean profiles of wind and temperature.
Accurate, global profiling of wind velocity is highly desired by NASA, NOAA, the DOD/DOC/NASA Integrated Program Office (IPO)/NPOESS, DOD, and others for many applications such as validation and improvement of climate models, and improved weather prediction. The most promising technology to deliver this measurement from space is Doppler Wind Lidar (DWL). The NASA/NOAA Global Tropospheric Wind Sounder (GTWS) program is currently in the process of generating the science requirements for a space-based sensor. In order to optimize the process of defining science requirements, it is important for the scientific and user community to understand the nature of the wind measurements that DWL can make. These measurements are very different from those made by passive imaging sensors or by active radar sensors. The purpose of this paper is to convey the sampling characteristics and data product trade-offs of an orbiting DWL.
Three major potential sources of errors that influence the performance of the proposed LIDAR wind profiling systems are accounted for in the following simulation studies. First, the coherent CO2 laser system proposed by NOAA/ERL for the WINDSAT requires distributions of 10 microns size aerosol concentrations throughout the atmosphere to determine the Doppler shifted backscatter signal. Second, atmospheric influences such as clouds and precipitation affect the LIDAR system's ability to obtain complete vertical wind profiles. In this study, experiments are reported on in which the complete wind profiles are only available in model generated cloud-free regions down to model cloud tops. Third, constraints on the available power required for the expected operational lifetime duration of a LIDAR system govern the number of pulses which can be used to sample a 300 km square area.
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by a Streamline XR Doppler Lidar operated by the University of Virginia and deployed at the MLBS site. 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 Foken et al. (2004).
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by a Streamline XR Doppler Lidar operated by Lawrence Livermore National Laboratory and deployed at the Tree Tops site (1.5 km South-West of MLBS site). 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 Foken et al. (2004).
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.
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.