Radar Operations Center

Norman, OK, United States

Radar Operations Center

Norman, OK, United States
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Richardson L.M.,Radar Corporation | Zitte W.D.,Radar Corporation | Lee R.R.,Radar Operations Center | Melnikov V.M.,University of Oklahoma | And 4 more authors.
Journal of Atmospheric and Oceanic Technology | Year: 2017

Clear-air Bragg scatter (CABS) is a refractivity gradient return generated by turbulent eddies that operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems can detect. The randomly oriented nature of the eddies results in a differential reflectivity (ZDR) value near 0 dB, and thus CABS can be used as an assessment of ZDR calibration in the absence of excessive contamination from precipitation or biota. An automated algorithm to estimate ZDR bias from CABS was developed by the Radar Operations Center and can be used to assess the calibration quality of the dual-polarized WSR-88D fleet. This technique supplements existing ZDR bias assessment tools, especially the use of other external targets, such as light rain and dry snow. The estimates of ZDR bias from CABS using a 1700-1900 UTC time window were compared to estimates from the light rain and dry snow methods. Output from the automated CABS algorithm had approximately the same amount of bias reported as the light rain and dry snow estimates (within ±0.1 dB). As the 1700- 1900 UTCtime windowappeared too restrictive, amodified version of the algorithmwas tested to detectCABS diurnally on a volume-by-volume basis (continuous monitoring). Continuous monitoring resulted in a two- to fourfold increase in the number of days with CABS detections. Results suggest estimates from CABS are viable for many sites throughout the year and provide an important addition to existing bias estimation techniques.


Richardson L.M.,Radar Operations Center | Richardson L.M.,Centuria Corporation | Cunningham J.G.,U.S. Air force | Zittel W.D.,Radar Operations Center | And 9 more authors.
Journal of Atmospheric and Oceanic Technology | Year: 2017

Studies have shown that echo returns from clear-air Bragg scatter (CABS) can be used to detect the height of the convective boundary layer and to assess the systematic differential reflectivity (ZDR) bias for a radar site. However, these studies did not use data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) or data from a large variety of sites. A new algorithm to automatically detect CABS from any operational WSR-88D with dual-polarization capability while excluding contamination from precipitation, biota, and ground clutter is presented here. Visual confirmation and tests related to the sounding parameters' relative humidity slope, refractivity gradient, and gradient Richardson number are used to assess the algorithm. Results show that automated detection of CABS in operational WSR-88D data gives useful ZDR bias information while omitting the majority of contaminated cases. Such an algorithm holds potential for radar calibration efforts and Bragg scatter studies in general.


News Article | November 22, 2016
Site: www.eurekalert.org

The Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma collaborate with the National Oceanic and Atmospheric Administration on weather and climate under the terms of a five-year, $95.3 million agreement with NOAA. CIMMS, the largest and second oldest research center at OU, supports NOAA with two of its next generation, long-term planning initiatives: Weather Ready Nation and Climate Adaptation and Mitigation. "The university is very excited by this new five-year agreement totaling over $95 million to support important weather and climate research on our campus in cooperation with the federal government," said OU President David L. Boren. "It underlines the importance of what is happening at our university. We are proud to be national leaders in this effort." CIMMS contributes to NOAA's enterprise-wide capabilities in science and technology, engagement and organization and administration in the following research areas: weather radar research and development; stormscale and mesoscale modeling research and development; forecast and warning improvements research and development; impacts of climate change related to extreme weather events; and societal and socioeconomic impacts of high impact weather systems. "CIMMS research improves our understanding of stormscale meteorological phenomena, weather radar and regional climate variations," said Interim Director Randy Peppler. "Our ultimate goal is to help NOAA produce better forecasts and warnings that save lives and protect property." CIMMS research affiliates or associates include: Oceanic and Atmospheric Research National Severe Storm Laboratory; Oceanic and Atmospheric Research Air Resources Laboratory; National Weather Service Radar Operations Center for the WSR-88D (NEXRAD) Program; National Weather Service/National Center for Environmental Protection Storm Prediction Center; National Weather Service Warning Decision Training Division; National Weather Service Norman Weather Forecast Office; and National Weather Service Training Center in Kansas City. CIMMS was established in 1978 through a memorandum of agreement between OU and NOAA. As a NOAA cooperative research institute, CIMMS supports scientists, engineers and students who conduct research, training and outreach in mesoscale weather, weather radar and regional-scale climate processes. For more information, contact cimms@nwc.ou.edu or visit http://cimms. .


Ivic I.R.,University of Oklahoma | Ivic I.R.,National Oceanic and Atmospheric Administration | Krause J.C.,Radar Operations Center | Krause J.C.,Centuria Corporation | And 6 more authors.
Journal of Atmospheric and Oceanic Technology | Year: 2014

A radar antenna intercepts thermal radiation from various sources, including the ground, the sun, the sky, precipitation, and man-made radiators. In the radar receiver, this external radiation produces noise that constructively adds to the receiver internal noise and results in the overall system noise. Consequently, the system noise power is dependent on the antenna position and needs to be estimated accurately. Inaccurate noise power measurements may lead to a reduction of coverage if the noise power is overestimated or to radar data images cluttered by noise speckles if the noise power is underestimated. Moreover, when an erroneous noise power is used at low to moderate signal-to-noise ratios, estimators can produce biased meteorological variables. Therefore, to obtain the best quality of radar products, it is desirable to compute meteorological variables using the noise power measured at each antenna position. An effective technique that achieves this by estimating the noise power in real time from measured powers at each scan direction and in parallel with weather data collection has been proposed. Herein, the effects of such radial-based noise power estimation on spectral moment estimates are investigated. © 2014 American Meteorological Society.


Melnikov V.M.,University of Oklahoma | Lee R.R.,Radar Operations Center | Langlieb N.J.,Radar Operations Center
IEEE Geoscience and Remote Sensing Letters | Year: 2012

It is shown that the scattering resonance effects in echoes from migrating birds are so strong that a 10% frequency deviation within S-band can result in more than 10-dB changes in reflectivity values. Differential reflectivity values from adjacent polarimetric WSR-88D weather radars operating at offset frequencies can differ by several decibels in clear air echoes. © 2012 IEEE.

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