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At least 163 records · Page 9

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross Mode (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗

W-Band ARM Scanning Cloud Radar (WSACR) 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross-Polarization Model (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). Beamwidths at Ka and W bands are roughly matched at 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies that are unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the Ka-SACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the W-SACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ration.

54 ENVIRONMENTAL SCIENCES↗

Measured electric field intensities near electric cloud discharges detected by the Kennedy Space Center's Lightning Detection and Ranging System, LDAR

For a summer thunderstorm, for which simultaneous, airborne electric field measurements and Lightning Detection and Ranging (LDAR) System data was available, measurements were coordinated to present a picture of the electric field intensity near cloud electrical discharges detected by the LDAR System. Radar precipitation echos from NOAA's 10 cm weather radar and measured airborne electric field intensities were superimposed on LDAR PPI plots to present a coordinated data picture of thunderstorm activity.

Poehler, H. A.↗

Market Assessment of Forward-Looking Turbulence Sensing Systems

In recognition of the importance of turbulence mitigation as a tool to improve aviation safety, NASA's Aviation Safety Program developed a Turbulence Detection and Mitigation Sub-element. The objective of this effort is to develop highly reliable turbulence detection technologies for commercial transport aircraft to sense dangerous turbulence with sufficient time warning so that defensive measures can be implemented and prevent passenger and crew injuries. Current research involves three forward sensing products to improve the cockpit awareness of possible turbulence hazards. X-band radar enhancements will improve the capabilities of current weather radar to detect turbulence associated with convective activity. LIDAR (Light Detection and Ranging) is a laser-based technology that is capable of detecting turbulence in clear air. Finally, a possible Radar-LIDAR hybrid sensor is envisioned to detect the full range of convective and clear air turbulence. To support decisions relating to the development of these three forward-looking turbulence sensor technologies, the objective of this study was defined as examination of cost and implementation metrics. Tasks performed included the identification of cost factors and certification issues, the development and application of an implementation model, and the development of cost budget/targets for installing the turbulence sensor and associated software devices into the commercial transport fleet.

Kauffmann, Paul↗

Report on the Radar/PIREP Cloud Top Discrepancy Study

This report documents the results of the Applied Meteorology Unit's (AMU) investigation of inconsistencies between pilot reported cloud top heights and weather radar indicated echo top heights (assumed to be cloud tops) as identified by the 45 Weather Squadron (45WS). The objective for this study is to document and understand the differences in echo top characteristics as displayed on both the WSR-88D and WSR-74C radars and cloud top heights reported by the contract weather aircraft in support of space launch operations at Cape Canaveral Air Station (CCAS), Florida. These inconsistencies are of operational concern since various Launch Commit Criteria (LCC) and Flight Rules (FR) in part describe safe and unsafe conditions as a function of cloud thickness. Some background radar information was presented. Scan strategies for the WSR-74C and WSR-88D were reviewed along with a description of normal radar beam propagation influenced by the Effective Earth Radius Model. Atmospheric conditions prior to and leading up to both launch operations were detailed. Through the analysis of rawinsonde and radar data, atmospheric refraction or bending of the radar beam was identified as the cause of the discrepancies between reported cloud top heights by the contract weather aircraft and those as identified by both radars. The atmospheric refraction caused the radar beam to be further bent toward the Earth than normal. This radar beam bending causes the radar target to be displayed erroneously, with higher cloud top heights and a very blocky or skewed appearance.

Wheeler, Mark M.↗

Microburst wind structure and evaluation of Doppler radar for airport wind shear detection

The horizontal and vertical structure of airflow within microbursts has been determined using Doppler weather radar data from the Joint Airport Weather Studies (JAWS) Project. It is shown that the downdraft typically associated with microbursts is about 1 km wide and begins to spread horizontally at a height below 1 km. The median time from initial divergence at the surface to maximum differential wind velocity across the microburst is five minutes. The height of maximum differential velocity is about 75 m, and the median velocity differential is 22 m/s over an average distance of 3.1 km. The outflow of the air is asymmetric, averaging twice as strong along the maximum axis compared to the mininum axis. Some technical requirements for a radar system to detect microbursts and to provide aircraft with early warnings of the onset of windshear are identified.

Wilson, J. W.↗

Gravity waves and convection in Colorado during July 1983

The dynamics of gravity-wave/convective-cell interaction is studied using NOAA data collected in NE Colorado during July and August 1983. The pressure fields measured with microbarographs, the tropospheric wind profiles obtained with a UHF wind profiler radar, and precipitation data collected with a 10-cm weather radar for four events (A, B, C, and D) are analyzed. The four disturbances are detected through a substantial depth of the troposphere. It is observed that in event A the wave and convective cells appear to be locked together; in event B, the wave and convective cells commence about the same time, but the wave velocities differ from the cell velocities; and in events C and D, the waves move faster than the maximum wind in the jet and faster than the convective cells. It is suggested that events A and B are generated by wind shear in the jet stream, and the excitation of events C and D depends on mechanisms such as vertical convective motion and acceleration in the jet flow.

Einaudi, F.↗

UNRAVEL: A Robust Modular Velocity Dealiasing Technique for Doppler Radar

Unfold Radar Velocity (UNRAVEL) is an open-source modular Doppler velocity dealiasing algorithm for weather radars. UNRAVEL is an algorithm that does not need external reference velocity data, making it easily applicable. The proposed algorithm includes 11 core modules and 2 dealiasing strategies. UNRAVEL is an iterative algorithm. The goal is to build the dealiasing results starting with the strictest possible continuity tests in azimuth and range and, after each step, relaxing the parameters to include more results from a progressively growing number of reference points. UNRAVEL also has modules that perform 3D continuity checks. Thanks to this modular design, the number of dealiasing strategies can be expanded in order to optimize the dealiasing results. While the first driver dealiases Doppler velocity from each tilt independently from one another, the second driver also performs a three-dimensional continuity check of the velocity using successive elevations. The proposed dealiasing algorithm is tested using severe weather data from an S-band Doppler radar that have been aliased to mimic aliased radial velocity patterns that would be observed by a C-band Doppler radar. Artificially aliasing S-band data permits creation of a reference to which the performance of various dealiasing techniques can be compared. Comparisons show that UNRAVEL consistently outperforms other established dealiasing algorithms for the test period selected in this work.

47 OTHER INSTRUMENTATION↗

Radar-Enabled Recovery of the Sutters Mill Meteorite, a Carbonaceous Chondrite Regolith Breccia

Doppler weather radar imaging enabled the rapid recovery of the Sutter's Mill meteorite after a rare 4-kiloton of TNT-equivalent asteroid impact over the foothills of the Sierra Nevada in northern California. The recovered meteorites survived a record high-speed entry of 28.6 kilometers per second from an orbit close to that of Jupiter-family comets (Tisserand's parameter = 2.8 +/- 0.3). Sutter's Mill is a regolith breccia composed of CM (Mighei)-type carbonaceous chondrite and highly reduced xenolithic materials. It exhibits considerable diversity of mineralogy, petrography, and isotope and organic chemistry, resulting from a complex formation history of the parent body surface. That diversity is quickly masked by alteration once in the terrestrial environment but will need to be considered when samples returned by missions to C-class asteroids are interpreted.

Radar↗

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, Kenneth R.↗

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, K. Robert↗

A general interactive system for compositing digital radar and satellite data

Reynolds and Smith (1979) have considered the combined use of digital weather radar and satellite data in interactive systems for case study analysis and forecasting. Satellites view the top of clouds, whereas radar is capable of observing the detailed internal structure of clouds. The considered approach requires the use of a common coordinate system. In the present investigation, it was decided to use the satellite coordinate system as the base system in order to maintain the fullest resolution of the satellite data. The investigation is concerned with the development of a general interactive software system called RADPAK for remapping and analyzing conventional and Doppler radar data. RADPAK is implemented as a part of a minicomputer-based image processing system, called Atmospheric and Oceanographic Image Processing System. Attention is given to a general description of the RADPAK system, remapping methodology, and an example of satellite remapping.

Ghosh, K. K.↗

An approach to estimate the areal rain-rate distribution from spaceborne radar by the use of multiple thresholds

Estimates of rain rate derived from a spaceborne weather radar will be most reliable over an intermediate range of values. In forming an area average of the rain rate, an alternative to the averaging of the high-resolution estimates, irrespective of their individual accuracies, is a multiple threshold approach. The method is based on the fact that the fractional area above a particular rain-rate threshold R(j) is related to the cumulative distribution of rain rates evaluated at R(j). Varying the threshold over the effective dynamic range of the radar yields the cumulative distribution function over this range. To obtain the distribution at all rain rates, a lognormal or gamma test function is selected such that the mean-square error between the test function and the measured values is minimized. Once the unknown parameters are determined, the first-order statistics of the areawide rain-rate distribution can be found. Tests of the method with data from the SPANDAR radar provide comparisons between it and the single threshold and the direct averaging approaches.

Meneghini, R.↗

Elliptical storm cell modeling of digital radar data

A model for spatial distributions of reflectivity in storm cells was fitted to digital radar data. The data were taken with a modified WSR-57 weather radar with 2.6-km resolution. The data consisted of modified B-scan records on magnetic tape of storm cells tracked at 0 deg elevation for several hours. The MIT L-band radar with 0.8-km resolution produced cross-section data on several cells at 1/2 deg elevation intervals. The model developed uses ellipses for contours of constant effective-reflectivity factor Z with constant orientation and eccentricity within a horizontal cell cross section at a given time and elevation. The centers of the ellipses are assumed to be uniformly spaced on a straight line, with areas linearly related to log Z. All cross sections are similar at different heights (except for cell tops, bottoms, and splitting cells), especially for the highest reflectivities; wind shear causes some translation and rotation between levels. Goodness-of-fit measures and parameters of interest for 204 ellipses are considered.

Altman, F. J.↗

Doppler radar results

The topics are covered in viewgraph form and include the following: (1) a summary of radar flight data collected; (2) a video of combined aft cockpit, nose camera, and radar hazard displays; (3) a comparison of airborne radar F-factor measurements with in situ and Terminal Doppler Weather Radar (TDWR) F-factors for some sample events; and (4) a summary of wind shear detection performance.

Bracalente, Emedio M.↗

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products.

Goodman, Steven J.↗

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. The GLM will help address the National Weather Service requirement for total lightning observations globally to support warning decision-making and forecast services. Science and application development along with pre-operational product demonstrations and evaluations at NWS national centers, forecast offices, and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in 2016. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

Goodman, Steven J.↗

Update on the NASA ER-2 Doppler radar system (EDOP)

An update on the development status of EDOP, a dual-beam Doppler weather radar to be flown on the NASA ER-2 aircraft, is presented. The EDOP system is an X-band Doppler radar with a dual-beam configuration in the ER-2 nose, such that one beam is nadir pointing and the other at an angle of 35 deg forward of the nadir. The dual beams, as used on ELDORA, directed at, e.g., 20 deg fore and aft of the normal to the fuselage, require only a linear rather than L-shaped flight pattern to compute air motions. On the ER-2, EDOP will essentially map out high-resolution time-height sections of reflectivity and vertical hydrometeor velocity from the nadir beam. Flying EDOP with other ground-based and airborne radars will also provide a more complete picture of the overall 3D precipitation and hydrometeor structure of storms.

Heymsfield, Gerald M.↗