RADAR Research and Development

Adams, J. L., D. J. Stensrud, 2005: Impact of tropical easterly waves on gulf surges during the North American Monsoon. Sixth Conference on Coastal Meteorology, San Diego, CA, USA, American Meteorological Society, 5.7.

Adams, J. L., D. J. Stensrud, 2007: Impact of tropical easterly waves on the North American monsoon. Journal of Climate, 20, 1219-1238.

The North American monsoon (NAM) is a prominent summertime feature over northwestern Mexico and the southwestern United States. It is characterized by a distinct shift in midlevel winds from westerly to easterly as well as a sharp, marked increase in rainfall. This maximum in rainfall accounts for 60%–80% of the annual precipitation in northwestern Mexico and nearly 40% of the yearly rainfall over the southwestern United States. Gulf surges, or coastally trapped disturbances that occur over the Gulf of California, are important mechanisms in supplying the necessary moisture for the monsoon and are hypothesized in previous studies to be initiated by the passage of a tropical easterly wave (TEW). Since the actual number of TEWs varies from year to year, it is possible that TEWs are responsible for producing some of the interannual variability in the moisture flux and rainfall seen in the NAM.

To explore the impact of TEWs on the NAM, four 1-month periods are chosen for study that represent a reasonable variability in TEW activity. Two continuous month-long simulations are produced for each of the selected months using the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model. One simulation is a control run that uses the complete boundary condition data, whereas a harmonic analysis is used to remove TEWs with periods of approximately 3.5 to 7.5 days from the model boundary conditions in the second simulation. These simulations with and without TEWs in the boundary conditions are compared to determine the impact of the waves on the NAM. Fields such as meridional moisture flux, rainfall totals, and surge occurrences are examined to define similarities and differences between the model runs. Results suggest that the removal of TEWs not only reduces the strength of gulf surges, but also rearranges rainfall over the monsoon region. Results further suggest that TEWs influence rainfall over the Southern Plains of the United States, with TEWs leading to less rainfall in this region. While these results are only suggestive, since rainfall is the most difficult model forecast parameter, it may be that TEWs alone can explain part of the inverse relationship between NAM and Southern Plains rainfall.

Bachmann, S. M., D. S. Zrnic, 2005: Spectral polarimetry for identifying and separating mixed biological scatterers. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, Amer. Meteor. Soc., P9R-5.

Bachmann, S. M., D. S. Zrnic, 2006: Spectral polarimetric VAD separates birds from insects (wind) velocities. Preprints, The 4th European Radar Conference, Barcelona, Spain, Meteocat, 96-100.

Bachmann, S. M., D. S. Zrnic, 2007: Spectral densities of polarimetric variables for retrieving winds and determining scatterer types. Preprints, The 23d Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, P2.13.

Available online at ://http://ams.confex.com/ams/pdfpapers/115197.pdf.

Bachmann, S., V. DeBrunner, D. Zrnic, M. Yeary, 2007: Spectral analysis of polarimetric weather radar data with multiple processes in a resolution volume. Preprints, The 32nd International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, USA, IEEE, ITT-L1.6. [Available from S. Bachmann, 120 David L. Boren Blvd., NWC Suite 4900, Norman, OK, USA, 73072.]

Bachmann, S., D. Zrnic, 2007: Adaptive technique to extract the intrinsic insects' backscatter differential phase from polarimetric spectra. Preprints, Conference on Radar Meteorology, Cairns, Australia, AMS, 11B.3.

Available online at ://http://ams.confex.com/ams/pdfpapers/122811.pdf.

Bachmann, S., V. DeBrunner, D. Zrnic, 2007: Detection of small aircraft with Doppler weather radar. Preprints, Statistical Signal Processing Workshop, Madison, WI, USA, IEEE, 1020. [Available from S. Bachmann, 120 David L. Boren Blvd., Suite 4900, Norman, OK, USA, 73072-7303.]

We present a method that can be performed in parallel to reflectivity estimation in weather radar and that allows one to detect small aircraft. Though small aircraft and large birds might produce comparable reflectivity signals their spectral signatures are considerably different. A small aircraft with propellers can be recognized from its spectrum via modulations produced by Doppler shifts from rotating parts. Generally such a spectrum has an elevated spectral floor compared to the spectrum of a resolution volume without an airplane. The spectral floor level is used for detection.

Bachmann, S., V. DeBrunner, D. Zrnic, M. Yeary, 2007: Adaptive technique for clutter and noise supression in weather radar exposes weak echoes over an urban area. Preprints, Statistical Signal Processing Workshop, Madison, WI, USA, IEEE, 1019. [Available from S. Bachmann, 120 David L. Boren Blvd., Suite 4900, Norman, OK, USA, 73072-7303.]

We present an adaptive spectral technique for ground clutter and noise suppression in weather radar echoes. This technique is especially good for detecting weak echoes that are either submerged in noise or masked by the residuals from ground clutter if standard techniques for clutter suppression are used. Our technique is demonstrated on two clear air cases observed with Doppler weather radar on February 22, 2007 and March 6, 2007. Adaptively suppressed ground clutter and noise allow exposure of a feature over an urban area, which we interpret as a “bird highway” between two lakes and along the river.

Bachmann, S., D. Zrnic, V. DeBrunner, 2007: Polarimetric azimuthal spectral histogram exposes types of mixed scatterers and the cause for unexpected polarimetric averages. Preprints, International Conference on Image Processing, San Antonio, TX, USA, IEEE, TP-L4.5. [Available from S. Bachmann, 120 David L. Boren Blvd., Suite 4900, Norman, OK, USA, 73072-7303.]

Echoes detected by polarimetric weather radar in clear air contain signals from air and biological scatterers. Discriminating scatterer types from a composite echo is challenging due to variability in scatterers’ quantity, azimuthal dependences of their polarimetric properties, and uneven mixing in resolution volumes. We use polarimetric spectral densities to estimate volume’s content by constructing two dimensional (2D) histograms in Doppler velocity – polarimetric variable space. Assimilation of these histograms in azimuth results in a 3D azimuthal spectral histogram (3DASH). We use transparency for small occurrences to visualize 3D signatures of the dominant content. The scatterer types have distinguishable signatures in the 3DASH due to their diverse physical shapes, scattering properties, different headings, and speeds. The 3DASH helps understand averages over the resolution volume. Further in the 3DASH one can identify intrinsic polarimetric values/functions for different types of biological scatterers, which are necessary for scatterer classification algorithms.

Bachmann, S., D. Zrnic, 2007: Spectral Density of Polarimetric Variables Separating Biological Scatterers in the VAD Display. Journal of Atmospheric and Oceanic Technology, 24, 1186-1198.

Available online at ://http://ams.allenpress.com/archive/1520-0426/24/7/pdf/i1520-0426-24-7-1186.pdf.

Bachmann, S., D. Zrnic, C. Curtis, 2008: Identification and suppression of ground clutter contributions for phased array radar. Preprints, 24th Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, New Orleans, LA, USA, AMS, CD-ROM, 9A.4.

Available online at ://http://ams.confex.com/ams/pdfpapers/131493.pdf.

Bachmann, S., D. Zrnic, 2008: Three-dimentional attributes of clear-air scatterers observed with polarimetric weather radar. IEEE Geoscience Remote Sensing Letters, 5, .

Bachmann, S., D. Zrnic, 2008: Suppression of clutter residue in weather radar reveals birds’ corridors over urban area. IEEE Geoscience and Remote Sensing Letters, 5, .

Biggerstaff, M. I., D. R. MacGorman, W. D. Rust, C. Ziegler, J. M. Straka, T. J. Schuur, G. Carrie, K. Kuhlman, E. Rasmussen, P. Krehbiel, W. Rison, T. Hamlin, 2005: The role of storm dynamics on cloud electrification: The 29 May 2004 Tornadic Supercell Observed During TELEX. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, 15R.1.

Brandes, E. A., T. J. Schuur, A. V. Ryzhkov, G. Zhang, K. Ikeda, 2005: Rain Microphysics Retrieval with a Polarimetric WSR-88D. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, 9R.2.

Brandes, E. A., K. Ikeda, K. L. Elmore, A. V. Ryzhkov, T. J. Schuur, 2006: Aviation weather hazard detection with polarimetric radar. Preprints, 12th Conference on Aviation, Range, and Aerospace Meteorology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, 6.1.

Brown, R. A., B. A. Flickinger, E. Forren, D. M. Schultz, D. Sirmans, P. L. Spencer, V. T. Wood, C. L. Ziegler, 2005: Improved detection of severe storms using experimental fine-resolution WSR-88D measurements. Weather and Forecasting, 20, 3-14.

Doppler velocity and reflectivity measurements from WSR-88D (Weather Surveillance Radar - 1988 Doppler) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0° and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory's test-bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5° azimuthal spacing and 0.25 km range spacing,resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fine-resolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

Bruning, E., W. D. Rust, D. MacGorman, T. Schuur, J. Straka, P. Krehbiel, W. Rison, T. Hamlin, 2005: Polarimetric radar and electrical structure of a multicell storm. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P14R.9.

Bruning, E. C., W. D. Rust, T. J. Schuur, D. R. MacGorman, P. R. Krehbiel, W. Rison, 2007: Electrical and Polarimetric Radar Observations of a Multicell Storm in TELEX. Monthly Weather Review, 135, 2525-2544.

On 28-29 June 2004 a multicellular thunderstorm west of Oklahoma City was probed as part of the Thunderstorm Electrification and Lightning Experiment (TELEX) field program. This study makes use of radar observations from the KOUN polarimetric WSR-88D, threedimensional lightning mapping data from the Oklahoma Lightning Mapping Array (LMA), and balloon-borne vector electric field meter (EFM) measurements. The storm had a low flash rate (30 flashes in 40 min). Four charge regions were inferred from a combination of LMA and EFM data. Lower positive charge near 4 km and mid-level negative charge from 4.5–6 km MSL (0 to -6.5°C) were generated in and adjacent to a vigorous updraft pulse. Further mid-level negative charge from 4.5–6 km MSL and upper positive charge from 6–8 km (-6.5 to -19°C) were generated later in quantity sufficient to initiate lightning as the updraft decayed. A negative screening layer was present near storm top (8.5 km MSL, -25°C). Initial lightning flashes were between lower positive and mid-level negative charge and started occurring shortly after a cell began lofting hydrometeors into the mixed phase region, where graupel was formed. A leader from the storm's first flash avoided a region where polarimetric radar suggested wet growth and the resultant absence of non-inductive charging of those hydrometeors. Initiation locations of later flashes that propagated into upper positive charge tracked the descending location of a polarimetric signature of graupel. As the storm decayed, electric fields greater than 160 kV m-1 exceeded the minimum threshold for lightning initiation suggested by the hypothesized runaway breakdown process at 5.5 km MSL, but lightning did not occur. The small spatial extent (≈100 m) of the large electric field may not have been sufficient to allow runaway breakdown to fully develop and initiate lightning.

Bruning, E. C., W. D. Rust, D. R. MacGorman, T. J. Schuur, P. R. Krehbiel, W. Rison, 2007: Temporal and Spatial Structure of Storm Charge and Kinematics in the 26 May 2004 Supercell Storm During TELEX. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, International Commission on Atmospheric Electricity, 229-232. [Available from 1313 Halley Circle, 1313 Halley Circle, Norman, OK, USA, 73069.]

Cao, Q., G. Zhang, T. J. Schuur, A. V. Ryzhkov, E. Brandes, K. Ikeda, 2006: Characterization of rain microphysics and polarimetric signatures based on disdrometer and radar observations. Preprints, IGARRS 2006, Denver, CO, USA, Institute of Electrical and Electronics Engineers, 02_11A05.

Cao, Q., G. Zhang, E. Brandes, T. Schuur, A. Ryzhkov, K. Ikeda, 2008: Analysis of video disdrometer and polarimetric radar data to characterize rain microphysics in Oklahoma. Journal of Applied Meteorology and Climatology, 47, 2238-2255.

Cheong, B. L., R. D. Palmer, T. Y. Yu, C. Curtis, 2005: Refractivity Measurements from Ground Clutter Using the National Weather Radar Testbed Phased Array Radar. Proc. 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P1R.10.

Cheong, B., R. Palmer, C. Curtis, K. Hondl, P. Heinselman, D. Zrnic, D. Forsyth, R. Murnan, R. Reed, R. Vogt, M. Foster, 2007: Real-time implementation of refractivity retrieval: Partnership between the University of Oklahoma, National Severe Storms Laboratory, and the Radar Operations Center. Preprints, 33rd Conference on Interactive Information and Processing Systems, San Antonio, TX, USA, American Meteorological Society, CD-ROM, P8B.8.

High-resolution, near-surface refractivity measurements have the potential of becoming an important tool for operational forecasting and general scientific studies. Access to measured refractivity fields with high spatial and temporal resolution near the surface opens a new paradigm for understanding the convective processes within the boundary layer. It has been shown via advanced physical models that surface refractivity plays an important role in con vective processes and, therefore, is expected to be valuable for forecasting of the initiation and intensity of convective precipitation. For this project, the refractivity field is retrieved remotely using S-band radars by measuring the returned phase from ground clutter. Pioneering work of Fabry et. al. [J. Atmos. Oceanic Technol., 14, 978-987, 1997] has demonstrated the usefulness of this technique. By adopting this refractivity retrieval concept, an independent real-time software platform has been developed. The software was written with a modular design for portability and will be tested during the spring 2007 storm season on two radars in Oklahoma. Both the National Weather Radar Testbed (Phased Array), maintained by the National Severe Storm Laboratory (NSSL), and the WSR-88D weather radar near Oklahoma City (KTLX), supported by the Radar Operations Center (ROC), will be used for this study. Using the raw Level-I time series data from the radars, the modular software platform will be used to process the data in real-time for refractivity fields, which will be sent to the Norman Weather Forecast Office (WFO) for evaluation. Working closely with the WFO forecasters, qualitative assessment procedures will be followed to evaluate the usefulness of the refractivity fields for operational forecasting.

Cheong, B. L., R. D. Palmer, C. D. Curtis, T. Y. Yu, D. S. Zrnic, D. Forsyth, 2007: Refractivity measurements from ground clutter using the National Weather Radar Testbed phased array Radar. Preprints, The 23rd Conference on Interactive Information Processing Systems(IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, American Meteorological Society, CD-ROM, 8A.3A.

Chilson, P. B., R. D. Palmer, M. Teshiba, A. V. Ryzhkov, T. J. Schuur, 2006: Combined observations of precipitation using wind profilers and polarimetric weather radars. Preprints, 7th International Symposium on Tropospheric Profiling Needs and Technologies, Boulder, CO, USA, National Center for Atmospheric Research, 6.1-O.

Chilson, P. B., G. Zhang, T. J. Schuur, A. V. Ryzhkov, L. Kanofsky, M. Teshiba, Q. Cao, M. Van Every, 2007: Coordinated in-situ and remote sensing precipitation measurements at the Kessler Farm Field Laboratory in central Oklahoma. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, American Meteorological Society, P8A.4.

Conway, J. B., D. Nealson, J. J. Stagliano, A. V. Ryzhkov, D. S. Zrnic, 2005: A New C-band Polarimetric Radar with Simultaneous Transmission for Hydrometeor Classification and Rainfall Measurements. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P12R.14.

Conway, J. B., A. Ryzhkov, D. Mitchell, P. Zhang, L. Venkatramani, J. L. Alford, D. Nelson, 2007: Examination of tornadic signatures observed at very close range using simultaneous dual-polarization radar at C band. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P10.2.

Curtis, C. D., T. Y. Yu, 2007: Beam multiplexing on the NWRT: looking ahead. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, CD-ROM, 7.9.

Beam multiplexing is a weather radar scanning strategy that utilizes the electronic beam steering capability of a phased array antenna. When scanning with a parabolic dish antenna, contiguous samples are collected and processed. With beam multiplexing, the time between transmitted pulses or groups of pulses at a particular beam location is increased which reduces the correlation between samples. Because the samples are less correlated, fewer pulses are transmitted to achieve the same level of errors. The dead time between collections at a given beam location can be used to acquire data at other beam locations so that the radar is in constant use. Decreasing VCP update times is the primary advantage compared to transmitting contiguous pulses, but beam multiplexing also introduces new challenges that need to be considered.

A simple beam multiplexing strategy has been implemented on the National Weather Radar Testbed (NWRT). Weather radar time-series data were collected and analyzed using the phased array radar (PAR) which confirmed earlier theoretical predictions about reductions in VCP times. Because of limitations in the currently implemented approach, we are looking ahead to new approaches that fully realize the potential of beam multiplexing. This paper will introduce the fundamental concepts of beam multiplexing, discuss the advantages and drawbacks, and describe a new approach that addresses some of the limitations of the current strategy.

Available online at ://http://ams.confex.com/ams/pdfpapers/117073.pdf.

Dodson, A., S. Van Cooten, K. Howard, J. Zhang, X. Xu, 2008: Assessing Vertical Profiles of Reflectivity (VPR's) To Detect Extreme Rainfall: Implications for Flash Flood Monitoring and Prediction. Preprints, 22nd Conference on Hydrology- Session 1, Weather To Climate Scale Hydrological Forecasting, New Orleans, LA, USA, AMS, CD-ROM, 1.5.

Tropical Storm Barry moved across the state of Florida from Tampa to Jacksonville on June 2 and then became extratropical as it moved northeast along the coastlines of Georgia, South Carolina and North Carolina from June 3 to June 4, 2007. Rainfall reports from gauges located within the surveillance areas of the Wakefield, Virginia (AKQ), Raleigh-Durham, North Carolina (RDU), and Morehead City, North Carolina (MHX), NEXRAD sites were collected and processed to document hourly rainfall rates associated with the system. In addition to the gauge data, atmospheric soundings from six area upper air observing sites were archived and analyzed to determine the response of atmospheric conditions, specifically freezing level, precipitable water, and atmospheric instability, as the system affected the region.

NOAA's National Severe Storms Laboratory (NSSL) Q2 System (www. nmq.nssl.noaa.gov) produces Vertical Profiles of Reflectivity (VPR) every five minutes for each continental United States (CONUS) NEXRAD site. These VPRs are used in the production of five-minute multi-sensor Quantitative Precipitation Estimates (QPE) to provide constantly updated relationships between radar reflectivity factor, Z, and rain rate, R (Z-R). VPRs were archived for June 3 and 4 for AKQ, RDU, and MHX. The VPRs were analyzed to quantify radar reflectivity trends over the course of the storm event. These trends were then correlated with rainfall rates, atmospheric sounding data, and surface observations, to investigate the characteristics of the VPRs associated with the highest rainfall rates. Results of this analysis indicate VPRs associated with the highest hourly rainfall rates observed with the storm system occurred as VPRs lost a concentrated area of high reflectivities around the atmospheric freezing level. Additionally, the gradient of radar reflectivities above and below this dissipating high reflectivity area diminished. Atmospheric soundings and surface map analysis indicated the air mass characteristics were acquiring tropical characteristics as surface dew points and atmospheric water content were increasing, wind directions transitioned from westerly to an easterly fetch off the Atlantic Ocean, and the atmospheric freezing level was rising. As the storm system moved away from the Carolinas, VPRs began to regain a concentrated area of high reflectivities around the atmospheric freezing level and the gradient of radar reflectivities began to increase once again above and below the area of higher reflectivities.

To quantify the implications of these VPR characteristics on the accuracy of the Q2 system's five-minute multi-sensor Quantitative Precipitation Estimates (QPE), the Q2 statistical verification tools were used to evaluate the performance of the system during the periods of the most intense rainfall. The Q2 system has recently implemented a tropical rain Z-R when VPRs and atmospheric sounding data meet criteria which have been identified by NSSL scientists as common factors in intense rainfall events. The VPRs observed through this June, 2007 storm event, were consistent with their findings. Results of this assessment show the Q2 tropical Z-R relationship produced highly accurate precipitation estimates which are available at a 1 km grid mesh resolution every five minutes. Additionally, the dynamic VPR system captured the air mass changes which occurred during the event. This feature provides improved information on a storm's environment to determine appropriate radar Z-R adjustments. This case demonstrates the ability to increase the accuracy of precipitation estimates especially in ungauged locations which can improve NOAA and our nation's flash flood monitoring and prediction programs.

Available online at ://http://ams.confex.com/ams/88Annual/techprogram/paper_135143.htm.

Doviak, R. J., 2005: A phased-array radar for weather research and education. Proc. XXVIIIth General Assembly of International Union Radio Science (URSI), New Delhi, India, URSI, CD-ROM, FP.8. [Available from Dick Doviak, NSSL, 120 David Boren Blvd, Norman, OK, USA, 73072-7327.]

The National Severe Storms Laboratory has assembled the first agile-beam phased-array Doppler radar for weather research and education. This National Weather Radar Testbed (NWRT) will support testing of ideas to observe weather, and other objects. Mechanically steered beams inefficiently use radar resources, and are limited in providing timely and added information on weather (e.g., the NWRT could directly measure crossbeam wind). Because the NWRT’s beam can be electronically steered to observe only weather of interest, rapid observations can be made, and/or the radar could serve other purposes (e.g., tracking aircraft, etc.), while conserving spectral space.

Doviak, R. J., G. Zhang, 2006: Crossbeam Wind Measurements with Phased_Array Doppler Weather Radar. Extended Abstracts, Fourth European Conference on Radar in Meteorlogy and Hydrology, Barcelona, Spain, Many, 1-4. [Available from Dick Doviak, NSSL, 120 David Boren Blvd, Norman, OK, USA, 73072-7327.]

Doviak, R. J., M. Fang, V. Melnikov, G. Zhang, 2008: Theoretical and practical considerations in using spectrum width data. Extended Abstracts, European Conference on Radar Meteorology - 2008, Helsinki, Finland, Vaisala, CD-ROM, 2.4.

Dubois, J. A., P. L. Spencer, 2005: Computing divergence from a surface network: Comparison of the triangle and pentagon methods. Weather and Forecasting, 20, 596-608.

Two methods for creating gridded fields of divergence from irregularly spaced wind observations are evaluated by sampling analytic fields of cyclones and anticyclones of varying wavelengths using a surface network. For the triangle method, which requires a triangular tessellation of the station network and assumes that the wind varies linearly within each triangle, divergence estimates are obtained directly from the wind observations and are assumed valid at triangle centroids. These irregularly spaced centroid divergence estimates then are analyzed to a grid using a Barnes analysis scheme. For the pentagon method, which requires a pentagonal tessellation of the station network and assumes that the wind varies quadratically within each pentagon, divergence estimates also are obtained directly from the wind observations and are valid at the station lying within the interior of each pentagon. These irregularly spaced divergence estimates then are analyzed to a grid using the same Barnes analysis scheme.
It is found that for errorless observations, the triangle method provides better analyses than the pentagon method for all wavelengths considered, despite the more restrictive assumption by the triangle method regarding the wind field. For well-sampled wavelengths, however, the preanalyzed divergence estimates at the interior stations of pentagons are found to be superior to those at triangle centroids. When random, Gaussian errors are added to the observations, all advantages of the pentagon method over the triangle method are found to disappear.

Ellis, S. M., M. Dixon, G. Meymaris, S. Torres, J. Hubbert, 2005: Radar range and velocity ambiguity mitigation: Censoring methods for the SZ-1 and SZ-2 phase coding algorithms. Preprints, 21st International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, USA, American Meteorological Society, 19.3.

Emersic, C., D. MacGorman, T. Schuur, N. Lund, C. Payne, E. Bruning, 2007: Lightning activity relative to the microphysical and kinematic structure of storms during a thunder-snow episode on 29-30 November 2006. Preprints, 2007 Fall Meeting, San Francisco, CA, USA, American Geophysical Union, AE43A-01.

We have examined lightning activity relative to the microphysical and kinematic structure of a winter thunderstorm complex (a thunder-snow episode) observed east of Norman, Oklahoma during the evening of 29-30 November 2006. Polarimetric radar provided information about the type of particles present in various regions of the storms. The Lightning Mapping Array (LMA) recorded VHF signals produced by developing lightning channels. The times of arrival of these lightning signals across the array were then used to reconstruct the location and structure of lightning, and these reconstructions were overlaid with radar data to examine the relationship between lightning properties and storm particle types.

Four storms in this winter complex have been examined. It was inferred from lightning structure that, in their mature stage, all cells we examined had a positive tripole electrical structure (an upper positive charge center, a midlevel negative charge center, and a lower positive charge center). The storms began with lightning activity in the lower dipole (lower positive and midlevel negative regions), but this evolved into lightning activity throughout the tripole structure within approximately 15-20 minutes. In the longer lived storms, the mature stage lasted for approximately 1.5-2 hours. During this stage, the lower positive charge region was situated less than 5 km above ground, the midlevel negative charge region was typically above 5 km, and the upper positive charge region was located at an altitude of less than 10 km in all the storm cells analyzed. The charge regions descended over approximately the last 30 minutes of lightning activity, the lower charge regions eventually reaching ground. This resulted in the loss of the lower positive charge center and the subsequent diminishment of the lower negative charge center.

Fang, M., R. J. Doviak, 2005: Corrections to and considerations of the spectrum width equation. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P4R.2.

Fang, M., J. Zhang, J. K. Williams, J. A. Craig, 2008: Three-Dimensional Mosaic of the Eddy Dissipation Rate Fields from WSR-88Ds. Extended Abstracts, The 88th AMS annual conference, New Orleans, LA, USA, AMS, P4.5. [Available from Ming Fang, 408C, Wadsack Dr., Norman, OK, USA, 73072.]

A national 3-D mosaic of Eddy Dissipation Rate (EDR) is being developed, prototyped, and evaluated through collaboration between the National Center for Atmospheric Research (NCAR) and NOAA’s National Severe Storms Lab (NSSL) under the auspices of the FAA Aviation Weather Research Program’s Turbulence and Advanced Weather Radar Techniques (AWRT) Research Teams. The EDR field is an indicator of in-cloud turbulence intensity derived from individual WSR-88Ds’ spectrum width data by the NEXRAD Turbulence Detection Algorithm (NTDA), which was developed at NCAR by the Turbulence Research Team. The NTDA software has been delivered to the National Weather Service and will be implemented operationally on all WSR-88Ds beginning in the spring of 2008, providing EDR and associated confidence data as a polar-grid Level III field. A national 3-D mosaic of the EDR field will provide a high-resolution, rapid update, in-cloud turbulence product for use in aviation safety decision support products. In particular, the Turbulence Research Team plans to incorporate it into a new rapid-update version of the Graphical Turbulence Guidance product, which will directly address convective turbulence for the first time.

The EDR mosaic has been developed using NTDA data from 20 radars covering the Chicago to Washington DC region that are being generated at NCAR and transferred to NSSL in real-time. A mosaic scheme previously developed by the AWRT Research Team for creating 3-D reflectivity mosaics was used as a starting point, but differences between EDR and reflectivity has required a number of adjustments; in addition, the 3-D mosaic scheme was modified to utilize the confidence values produced by the NTDA. The prototype regional 3-D in-cloud turbulence mosaic was evaluated based on comparisons with EDR values obtained from an automated measurement and reporting system on United Airlines aircraft. Continuing evaluation and tuning efforts are expected to lead to enhancements in the current mosaic scheme and establishment of a methodology that will eventually be used in the operational national 3-D in-cloud turbulence mosaic.

Fang, M., R. J. Doviak, P. Zhang, 2008: An Analytical Expression For Doppler Spectra Related to TerminalVelocity With Non-uniform Drop Size Distribution. Extended Abstracts, The 88th AMS annual meeting, New Orleans, LA, USA, AMS, P2.27. [Available from Ming Fang, 408C, Wadsack Dr., Norman, OK, USA, 73072.]

Starting from the correlation function and neglecting other spectrum broadening mechanisms, an analytical expression for the Doppler spectrum is related to the drop’s terminal velocity and size distribution if there is a unique relationship between drop’s diameter and its terminal velocity. The derivation does not require drop size distribution to be homogeneous. This generalized expression reduces to previously derived expression if drop size distribution is uniform.

Fang, M., R. J. Doviak, 2008: WSR-88D Observed Spatial Spectra of Turbulence in Precipitation. Extended Abstracts, The 88th AMS annual meeting, New Orleans, LA, USA, AMS, 12.6. [Available from Ming Fang, 408C, Wadsack Dr., Norman, OK, USA, 73072.]

Different algorithms are designed to isolate the turbulent component from radar measured Doppler velocity. Spatial spectra along the quasi-horizontal direction are then obtained in stratiform rain, storms and squall lines. The slope of horizontal spectra in stratiform rain and storms is close to -5/3 on a log-log graph up to at least scales of 10 km and 7 km respectively. The spectrum in a squall line has a steeper slope than -5/3 up to scales at least 17 km. The scales at low wave number end on the spectra are so large that the spectra could not be due to three-dimensional isotropic turbulence but to two-dimensional turbulence.

Fast, J. D., R. K. Newsom, K. J. Allwine, Q. Xu, P. Zhang, J. H. Copeland, J. Sun, 2007: Using NEXRAD wind retrievals as input to atmospheric dispersion models. Extended Abstracts, Seventh Symposium on the Urban Environment, San Diego, CA, USA, Amer. Meteor. Soc., 8.2.

Available online at ://http://ams.confex.com/ams/7Coastal7Urban/techprogram/paper_127244.htm.

Fast, J. D., R. K. Newsom, K. J. Allwine, Q. Xu, P. Zhang, J. Copeland, J. Sun, 2008: An evaluation of two NEXRAD wind retrieval methedologies and their use in atmospheric dispersion models. Journal of Applied Meteorology and Climatology, 47, 2351-2371.

Forsyth, D. E., J. F. Kimpel, D. S. Zrnic, R. Ferek, J. F. Heimmer, T. J. McNellis, J. E. Crain, A. M. Shapiro, R. J. Vogt, W. Benner, 2005: The National Weather Radar Testbed (Phased-Array). Extended Abstracts, 32nd Confernce on Radar Meteorology, Alburqueue, NM, USA, American Meteorological Society, CD-ROM, 12R.3.

A new national asset for weather radar research is operational in Norman, Oklahoma. This project was developed as a result of a partnership between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the United States Navy's Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma's Electrical and Computer Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, the Tri-Agencies' (Department of Commerce, Defense and Transportation) Radar Operations Center, the Federal Aviation Administration's Technical Center and Basic Commerce and Industries, Inc This project involved converting a Navy SPY-1 phased array antenna system into a weather research tool. The National Weather Radar Testbed (NWRT) provides the first phased array radar available on a full-time basis to the meteorological research community.
The NWRT became operational in September 2003, but initial problems delayed data collection until May 2004. In this paper, we will describe data quality improvements, recent upgrades, and future plans.

Forsyth, D. E., J. F. Kimpel, D. S. Zrnic, R. Ferek, J. F. Heimmer, T. J. McNellis, J. E. Crain, A. M. Shapiro, R. J. Vogt, W. Benner, 2006: Status report on the National Weather Radar Testbed (Phased-Array). Extended Abstracts, 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, 11.1.

The National Weather Radar Testbed (NWRT) is operational in Norman, Oklahoma. This project was developed as a result of a partnership between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the United States Navy's Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma's Electrical and Computing Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, the Tri-Agencies' (Department of Commerce, Defense and Transportation) Radar Operations Center, the Federal Aviation Administration's Technical Center and Basic Commerce and Industries, Inc Using a Navy SPY-1A phased array antenna system, the NWRT provides the first phased array radar available on a full-time basis to the meteorological research community.
The NWRT became operational in September 2003, and first data were collected in May 2004. Several data sets have been collected during the limited 2005 storm season. Current efforts are concentrated on improving the scanning speed through beam-multiplexing and preparing the system for remote operations. In this paper, we will describe the present status, research progress, and plans how to exploit the unique capabilities of electronic beam steering on the NWRT.

Forsyth, D. E., J. F. Kimpel, D. S. Zrnic, R. Ferek, J. F. Heimmer, T. McNellis, J. E. Crain, A. M. Shapiro, R. J. Vogt, W. Benner, 2005: Progress Report on the National Weather Radar Testbed (Phashed-Array).. Preprints, 21st International Conference on Interactive Information Processing Systems for Meteorology, Ocenography, and Hydrology, San Diego, CA, USA, American Meteorological Society, CD-ROM, 19.5.

A new national asset for weather radar research is operational in Norman, Oklahoma. This project was developed as a result of a partnership between the National Oceanic and Atmospheric Administration’s National Severe Storms Laboratory, the United States Navy’s Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma’s Electrical Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, the Tri-Agencies' (Department of Commerce, Defense and Transportation) Radar Operations Center, the Federal Aviation Administration’s Technical Center and Basic Commerce and Industries, Inc This project involved converting a Navy SPY-1 phased array antenna system into a weather research tool. The National Weather Radar Testbed (NWRT) provides the first phased array radar available on a full-time basis to the meteorological research community.

The NWRT became operational in September 2003, but problems with the velocity channel delayed initial data collection until May 2004. Our initial efforts have been focused on ensuring that the data is of high quality. Qualitative comparisons with a WSR-88D (KTLX-Twin Lakes, OK) appear to be similar. In this paper, we will describe data quality improvements, recent upgrades, future plans and present some examples of the first tornadic data set obtained with this new national facility.

Forsyth, D. E., J. F. Kimpel, D. S. Zrnic, R. Ferek, J. F. Heimmer, T. McNellis, J. E. Crain, A. M. Shapiro, R. J. Vogt, W. Benner, 2007: Update on the National Weather Radar Testbed (Phased-Array). Preprints, The 23d Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, American Meteorological Society, CD-ROM, 7.4.

The National Weather Radar Testbed (NWRT) is now functioning as a research tool in Norman, Oklahoma. The NWRT was developed as a result of a partnership between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the United States Navy's Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma's Electrical and Computing Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, the Tri-Agencies' (Department of Commerce, Defense and Transportation) Radar Operations Center, the Federal Aviation Administration's Technical Center and Basic Commerce and Industries, Inc.. Using a Navy SPY-1A phased array antenna system, the NWRT provides the first phased array radar available on a full-time basis to the meteorological research community and for testing of the concept of a multifunction phased array radar (MPAR) system.

Again, only a few data sets were collected during the 2006 storm season due to the limited amount of severe weather. Current efforts are concentrated on improving the scanning speed through beam-multiplexing and over-sampling. We have also implemented remote operations in preparation of our move to the National Weather Center. In this paper, we will describe the present status, research progress including eight second volume scans, and plans on making the NWRT a national resource.

Forsyth, D. E., J. F. Kimpel, D. S. Zrnic, R. Ferek, J. F. Heimmer, T. McNellis, J. E. Crain, a. M. Shapiro, R. J. Vogt, W. Benner, 2007: Update on the National Weather Radar Testbed (Phased-Array). Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, American Meteorological Society, CD-ROM, 7.2.

The National Weather Radar Testbed (NWRT) is now functioning as a research tool in Norman, Oklahoma. The NWRT was developed as a result of a partnership between the National Oceanic and Atmospheric Administration’s National Severe Storms Laboratory, the United States Navy’s Office of Naval Research, Lockheed Martin Corporation, the University of Oklahoma’s Electrical and Computing Engineering Department and School of Meteorology, the Oklahoma State Regents for Higher Education, the Tri-Agencies' (Department of Commerce, Defense and Transportation) Radar Operations Center, the Federal Aviation Administration’s Technical Center and Basic Commerce and Industries, Inc Using a Navy SPY-1A phased array antenna system, the NWRT provides the first phased array radar available on a full-time basis to the meteorological research community and for testing of the concept of a multi-mission phased array radar (MPAR) system.

Only a few data sets were collected during the 2006 storm season due to the limited amount of severe weather. Results from the 2007 storm season will be reported on along with planned system upgrades and a general overview of the research projects conducted in 2006 and 2007. We will also report on the progress of making the NWRT available as a national resource

Fredrickson, S. E., P. L. Heinselman, D. Zaras, W. J. Gonzales-Espada, 2006: Relative Humidity: What do students know about it?. Preprints, 15th Educational Symposium, Atlanta, GA, USA, 86th AMS Annual Meeting, CD-ROM, 3.9. [Available from Sherman Fredrickson, National Severe Storms Laboratory, 120 David L Boren Blvd, Norman, OK, USA, 73072.]

The concepts of evaporation and precipitation as related to relative humidity have evolved from a mechanistic paradigm (air and water particles showing macroscopic characteristics), to a saturation paradigm (water vapor dissolving in air up to a maximum value; air showing saturation capacity), to the correct kinetic model (evaporation and condensation as a dynamic equilibrium, Dalton's law of partial pressure, Bernoulli's Kinetic theory of gases). Unfortunately, most of the nomenclature on relative humidity, evaporation, condensation, and precipitation was coined during the saturation paradigm period and persists, even though more correct terminology exists (equilibrium vapor pressure instead of saturation point, for instance).

The incorrect concept of saturation with respect to relative humidity is very pervasive. Unlike other science misconceptions that are acquired by people through their daily experiences, their own environment explorations, their social interactions, and media, this misconception is also formally taught. Regardless of its origin, scientific misconceptions are tenacious and very resistant to change, mostly because unlearning is extremely difficult if the information "makes sense" from an uninformed or simplistic viewpoint. Because no research has tried to determine the extent of misconceptions about relative humidity, this study aims to contribute to the science education literature in this important area.

The purpose of this paper is to investigate college students' knowledge of the concept of relative humidity by (1) documenting current student ideas about relative humidity, (2) detecting what misconceptions students have about relative humidity and related areas such as evaporation, condensation, and precipitation, and (3) providing evidence that the questionnaire used for data collection is valid and reliable. The research design included the use of a locally-designed, multiple-choice survey to collect information on students' concepts of relative humidity, evaporation, condensation, and precipitation before the topic is covered in class. The participants were enrolled at OU's METR 1014 class during the Fall 2005 semester.

Available online at ://http://cimms.ou.edu/~ladue/Papers/fredrickson-ams06.pdf#search=%22fredrickson%20humidity%20students%20%22what%20do%22%22.

Fritz, A., V. Lakshmanan, T. M. Smith, E. Forren, B. Clarke, 2006: A validation of radar reflectivity control methods. Preprints, 22nd Conference on Interactive Information Processing Systems, Atlanta, GA, USA, AMS, CD-ROM, 9.10.

Available online at ://http://ams.confex.com/ams/Annual2006/techprogram/paper_102136.htm.

Giangrande, S. E., A. V. Ryzhkov, 2005: Calibration of Dual-Polarization Radar in the Presence of Partial Beam Blockage. Journal of Atmospheric and Oceanic Technology, 22, 1156-1166.

Giangrande, S. E., A. V. Ryzhkov, J. Krause, 2005: Automatic Detection of the Melting Layer with a Polarimetric Prototype of the WSR-88D Radar. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, 11R.2.

Giangrande, S. E., A. V. Ryzhkov, 2007: Estimation of rainfall based on the results of polarimetric echo classification. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P6B.7.

Green, J. S., V. Lakshmanan, T. M. Smith, 2005: Quantitative analysis of different methods for merging radar reflectivity data.. Preprints, 4th Student conference, San Diego, CA, USA, AMS, CD-ROM, P1.13.

Guillot, E. M., V. Lakshmanan, T. M. Smith, G. J. Stumpf, D. W. Burgess, K. L. Elmore, 2008: Tornado and Severe Thunderstorm Warning Forecast Skill and its Relationship to Storm Type. Extended Abstracts, 23rd Conference on Interactive Information Processing Systems, New Orleans, LA, USA, AMS, 4A.3.

The amount of forecast skill involved when issuing tornado and severe thunderstorm warnings is closely related to the type of storm that causes the severe weather. Storms from eight tornado outbreaks are classified and correlated with tornado warnings and severe thunderstorm warnings. These warnings were verified, missed, or shown to be false alarms by relating them with storm reports that match temporally and spatially with those in the Storm Prediction Center's database. Certain forecast parameters, including the critical success index (CSI), probability of detection (POD), false alarm ratio (FAR), and warning lead time are calculated for each storm type and for each type of warning. Because it was not practical to manually classify these storms (~50,000 entities), a decision tree was trained on a subset of manually classified storms using Quinlan's C4.5 algorithm. The decision tree was then used to automatically classify storms as being of one of four types: supercellular, linear, pulse or unorganized. It was found that both tornado warnings and severe thunderstorm warnings issued for isolated supercells and convective line storms have higher CSI, higher POD, and lower FAR scores than those issued for pulse and non-organized storms. Lead times were consistently longer for supercell and line storms, while usually very short for pulse and non-organized storms. We conclude that measures of forecast skill are particularly sensitive to the type of storm. Thus, any measurement of forecast skill, such as the year-over-year skill measure of an individual forecast office, has to take into account the types of storms in that office's warning area in the time period considered.

Available online at ://http://ams.confex.com/ams/88Annual/techprogram/paper_132244.htm.

Hane, C. E., D. L. Andra, Jr., J. A. Haynes, T. E. Thompson, F. H. Carr, 2005: On the Importance of Environmental Factors in Influencing the Evolution of Morning Great Plains MCS Activity during the Warm Season. Extended Abstracts, Eleventh Conference on Mesoscale Processes, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P3M.6.

Harasti, P. R., D. Smalley, M. Weber, C. Kessinger, Q. Xu, P. Zhang, S. Liu, T. Tsui, J. Cook, Q. Zhao, 2005: On the development of a multi-algorithm radar data quality control system at the naval research laboratory. 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, XXXX.

Heinselman, P. L., A. Rowe, 2005: Estimating hail size using polarimetric radar. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, Amer. Meteor. Soc., CD-ROM, P9R.16.

Heinselman, P. L., D. M. Schultz, 2006: Intraseasonal variability of summertime storms over central Arizona during 1997 and 1999. Weather and Forecasting, 21, 559-578.

Although previous climatologies over central Arizona show a summer diurnal precipitation cycle, on any given day precipitation may differ dramatically from this climatology. The purpose of this study is to investigate the intraseasonal variability of diurnal storm development over Arizona and explore the relationship to the synoptic-scale flow and Phoenix soundings during the 1997 and 1999 North American Monsoons (NAMs). Radar reflectivity mosaics constructed from Phoenix and Flagstaff Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data reveal six repeated storm development patterns or regimes. The diurnal evolution of each regime is illustrated by computing frequency maps of reflectivity 25 dBZ and greater during 3-h periods. These regimes are named to reflect their regional and temporal characteristics: dry regime (DR), Eastern Mountain regime (EMR), Central–Eastern Mountain regime (CEMR), Central–Eastern Mountain and Sonoran-isolated regime (CEMSIR), Central–Eastern Mountain and Sonoran regime (CEMSR), and nondiurnal regime (NDR).
Composites constructed from the National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis Project data show that regime occurrence is related to the north–south location of the 500-hPa geopotential height ridge axis of the Bermuda High and the east–west location of the 500-hPa monsoon boundary, a boundary between dry air to the west and moist air to the east. Consequently, precipitable water (PW) from 1200 UTC Phoenix soundings is the best parameter for discriminating the six regimes.

Heinselman, P. L., A. V. Ryzhkov, 2006: Validation of Polarimetric Hail Detection. Weather and Forecasting, 21, 839-850.

This study describes, illustrates, and validates hail detection by a simplified version of the National Severe Storms Laboratory's (NSSL) fuzzy logic polarimetric hydrometeor classification algorithm (HCA). The HCA uses four radar variables: reflectivity, differential reflectivity, cross-correlation coefficient, and "reflectivity texture" to classify echoes as rain mixed with hail, ground clutter-anomalous propagation, biological scatterers (insects, birds, and bats), big drops, light rain, moderate rain, and heavy rain. Diagnostic capabilities of HCA, such as detection of hail, are illustrated for a variety of storm environments using polarimetric radar data collected mostly during the Joint Polarimetric Experiment (JPOLE; 28 April-13 June 2003).

Hail classification with the HCA is validated using 47 rain and hail reports collected by storm-intercept teams during JPOLE. For comparison purposes, probability of hail output from the Next-Generation Weather Radar (NEXRAD) Hail Detection Algorithm (HDA) is validated using the same ground truth. The anticipated polarimetric upgrade of the Weather Surveillance Radar-1988 Doppler (WSR-88D) network drives this direct comparison of performance. For the four examined cases, contingency table statistics show that the HCA outperforms the HDA. The superior performance of the HCA results primary from the algorithm's lack of false alarms compared to the HDA. Statistical significance testing via bootstrapping indicates that differences in POD and CSI between the algorithms are statistically significant at the 95% confidence level, whereas differences in FAR and HSS are statistically significant at the 90% confidence level.

Heinselman, P. L., D. L. Priegnitz, K. L. Manross, R. Adams, 2006: Comparison of storm evolution characteristics: The NWRT and WSR-88D. Preprints, 23rd Conference on Severe Local Storms, St. Louis, MO, USA, AMS, CD-ROM, 14.1.

The National Weather Research Testbed (NWRT), located in Norman, Oklahoma at the National Severe Storms Laboratory, began collecting data with the Phased Array Radar (PAR) in spring of 2003. Until recently, these data were used mostly to address engineering issues. During the late spring of 2006 the stability of the NWRT PAR was sufficient to allow the collection of data on several storm events. A key advantage of the NWRT is the capability to adaptively scan storms at higher temporal resolution than is possible by the WSR-88D (1 min or less vs 5 min, respectively). Benefits of faster scanning of convective storms include better understanding of storm dynamics and initiation, better detection of small-scale phenomena, and increased lead time for warnings, to name a few. This paper marks the beginning of a series of studies that seek to improve understanding of the evolution of small-scale phenomena, like tornadoes and microbursts, as well as the development of convective storm structure. A first step toward this goal is comparative analysis of the evolution of convective storm structure for single cells, multicells, supercells, and line segments using rapid-scanning reflectivity and velocity data collected by the NWRT and conventional reflectivity data collected by the nearby WSR-88D (KTLX) during May and June 2006. The analysis will focus on features associated with storm initiation, growth, and decay, including mergers and hail cores. Results of this analysis will be reported in the extended abstract.

Heinselman, P. L., D. Priegnitz, T. Smith, D. Andra, R. Palmer, M. Biggerstaff, 2007: Spring 2007 National Weather Radar Testbed Demonstration. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P5.7.

Although WSR-88D data are indispensable for assessing storm severity, a recent comparative analysis of the evolution of several severe convective storms using data collected by KLTX (Oklahoma City, OK) WSR-88D and the National Weather Radar Testbed (NWRT) phased array radar (PAR) demonstrated the ability of PAR to provide the high-temporal resolution data needed for early detection of significant storm development, hail signatures, gust fronts, and wind shear. These high-temporal resolution data have the potential to benefit short-term forecasting and warning decision-making, though users may be challenged by the rapid influx of data.

This spring, National Weather Service forecasters participating in the NWRT demonstration at the NOAA Hazardous Weather Testbed in Norman, Oklahoma will be introduced to PAR data for the first time. The NWRT demonstration will be conducted from 15 April through 30 June 2007 and will primarily be concerned with data collection within a 150 km radius of the PAR prior to and during severe weather warning operations. Two overarching goals of the NWRT demonstration are to test the adaptive, multi-purpose scanning capability of PAR and to collect feedback from NWS forecasters on operational benefits and challenges of integrating PAR data into warning decision-making. The preliminary results of this study will be reported in the extended abstract.

Available online at ://http://ams.confex.com/ams/pdfpapers/123058.pdf.

Heinselman, P. L., D. Priegnitz, K. Manross, R. Adams, 2007: Comparison of Storm Evolution Characteristics: The NWRT and WSR-88D. Preprints, 23rd Conference on Interactive Information and Processing Systems, San Antonio, TX, USA, American Meteorological Society, CD-ROM, 7.5. [Available from Pam Heinselman, 120 David L Boren Blvd, Norman, OK, USA, 73069.]

The National Weather Radar Testbed (NWRT), located in Norman, Oklahoma at the National Severe Storms Laboratory, began collecting data with the Phased Array Radar (PAR) in spring of 2003. Until recently, these data were used mostly to address engineering issues. Beginning in late spring of 2006 the stability of the NWRT PAR was sufficient to allow the collection of data. Several storm eventshave been captured since colletion began, and more atmospheric phenomena are being added to the PAR data set. A key advantage of the NWRT is the capability to adaptively scan storms at higher temporal resolution than is possible by the WSR-88D (1 min or less vs 5 min, respectively). Benefits of faster scanning of convective storms include better understanding of storm dynamics and initiation, better detection of small-scale phenomena, and increased lead time for warnings, to name a few. This paper marks the beginning of a series of studies that seek to improve understanding of the evolution of small-scale phenomena, like tornadoes and microbursts, as well as the development of convective storm structure. A first step toward this goal is comparative analysis of the evolution of convective storm structure for single cells, multicells, and line segments using rapid-scanning reflectivity and velocity data collected by the NWRT and conventional reflectivity data collected by the nearby WSR-88D (KTLX) during May and June 2006. The analysis will focus on features associated with storm initiation, growth, and decay, including mergers and hail cores. Results of this analysis will be reported in the extended abstract.

Heinselman, P. L., D. Priegnitz, T. Smith, D. Andra, R. Palmer, M. Biggerstaff, 2007: Spring 2007 National Weather Radar Testbed Demonstration. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, American Meteorological Society, CD-ROM, P5.7.

Available online at ://http://ams.confex.com/ams/33Radar/techprogram/paper_123058.htm.

Heinselman, P. L., D. Priegnitz, K. Manross, R. Adams, 2007: Comparison of Storm Evolution Characteristics: The NWRT and WSR-88D. Preprints, 23rd Conference on 23rd Conference onInteractive Information and Processing Systems, San Antonio, TX, USA, Amer. Meteor. Soc., CD-ROM, 7.8.

Higgins, W., D. Ahijevych, J. Amador, A. Barros, E. Berbery, E. Caetano, R. Carbone, P. Ciesielski, R. Cifelli, M. Cortez-Vazquez, A. Douglas, M. Douglas, G. Emmanuel, C. Fairall, D. Gochis, D. Gutzler, T. Jackson, R. Johnson, C. King, T. Lang, M. Lee, D. Lettenmaier, R. Lobato, V. Magaña, J. Meitin, K. Mo, S. Nesbitt, F. Ocampo-Torres, E. Pytlak, P. Rodgers, S. Rutledge, J. Schemm, S. Schubert, A. White, C. Williams, A. Wood, R. Zamora, C. Zhang, 2006: The NAME 2004 Field Campaign and Modeling Strategy. Bulletin of the American Meteorological Society, 87, 79-94.

Hondl, K. D., V. Lakshmanan, T. M. Smith, G. J. Stumpf, 2007: Warning Decision Support System - Integrated Information (WDSS-II) Progress and Plans. Preprints, 23rd Conference on Interactive Information Processing Systems, San Antonio, TX, USA, AMS, CD-ROM, 6.3.

The Warning Decision Support System -- Integrated Information (WDSS-II) has been enhanced to support several new research and real-time efforts. The real-time ingest now includes Canadian radar data, the National Weather Radar Testbed (NWRT) Phased Array Radar (PAR), and the CASA X-band radar network being testing in Oklahoma.

New outputs include Grib2 files and a variety of georeferenced products covering the continental United States and capable of being displayed in GIS systems such as Google Earth.

New or improved algorithms include an improved WSR-88D reflectivity quality-control algorithm, improved azimuthal shear detection, a local-maximum feature tracker, and a faster real-time 3D multi-radar product creation. New experiments include an experimental warning program, real-time delivery of products to the Storm Prediction Center (SPC) and several National Weather Service (NWS) forecast offices and a real-time hail verification experiment.

The 3D base radar display is being configured as the Four-Dimensional Stormcell Investigator (FSI) and is currently being transferred to the National Weather Service AWIPS. Also, there are plans to transfer the multi-radar, multi-sensor applications, as well as some aspects of the infrastructure to the next generation AWIPS.

Available online at ://http://ams.confex.com/ams/pdfpapers/118556.pdf.

Ice, R. L., D. A. Warde, A. D. Free, R. D. Rhoton, D. S. Saxion, C. A. Ray, N. K. Patel, O. E. Boydstun, D. S. Berkowitz, J. N. Chrisman, J. C. Hubbert, C. J. Kessinger, M. Dixon, S. M. Torres, 2007: Optimizing clutter filtering in the WSR-88D. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, CD-ROM, P2.11.

Ivic, I., A. Zahrai, S. Torres, 2005: Decorrelation in range of oversampled weather radar signals using FIR filter. Preprints, 32nd International Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, P4R.12.

Ivic, I. R., D. S. Zrnic, 2007: USE OF COHERENCY TO IMPROVE SIGNAL DETECTION IN DUAL-POLARIZATION WEATHER RADARS. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, National Weather Service (NWS), CD-ROM, P11B.14.

Currently the WSR-88D network of weather surveillance radars (i.e., NEXRAD) uses only power estimates for signal censoring. The planned network upgrade to dual polarization will result in 3dB SNR reduction because transmitter output will be split between H and V channels. As a result, this will diminish radar sensitivity if the current power based censoring scheme is retained. In this paper, an alternative signal detection scheme is proposed which yields the improved detection over current approach. It mitigates the effects of SNR decrease by utilizing the weather signal coherency in sample-time and across channels.

Available online at ://http://ams.confex.com/ams/33Radar/techprogram/paper_123063.htm.

James, M. R., R. D. Palmer, T.-Y. Yu, S. M. Torres, R. J. Doviak, D. S. Zrnic, 2005: Implementation of refractivity retrieval from ground clutter using the S-band KOUN radar. Preprints, 32nd International Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, 4R.7.

Kang, M., S. E. Giangrande, A. V. Ryzhkov, D. Lee, 2005: Polarimetric Rainfall Measurements in Localized Strong Convection. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P9R.12.

Kanofsky, L. M., P. B. Chilson, T. J. Schuur, G. Zhang, E. Brandes, 2005: A comparative study of drop size distribution retrieval using two video disdrometers and a UHF wind profiling radar. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P14R.3.

Kanofsky, L. M., P. B. Chilson, T. J. Schuur, G. Zhang, Q. Cao, E. Brandes, 2007: Quantitative precipitation estimation and error analysis with a UHF wind profiling radar and a two-dimensional video disdrometer. Preprints, 33rd Conference on radar Meteorology, Cairns, Australia, American Meteorological Society, P13B.6.

Katz, S., D. Lafrance, H. Urkowitz, D. Staiman, M. Campbell, D. Forsyth, 2006: Solid State Fractional Phased Array Addition To NWRT. Extended Abstracts, 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, 11.7.

The National Weather Radar Testbed (NWRT) serves as a tool for radar meteorological research and for investigation of techniques for utilizing phased array radars for weather sensing. Using a SPY-1A phased array antenna, loaned to NOAA by the U. S. Navy, the testbed is capable of performing scans over user-defined sectors considerably faster than conventional weather radars using rotating reflector antennas. Lockheed Martin and NSSL are planning an addition to the NWRT in the form of a solid state transmit/receive (T/R) module fractional array. This array will provide a proof of concept capability for advanced phased array applications to meteorological sensing and multifunction applications. In particular, implementation will support validation of concepts such as dual polarization control and calibration over all scan angles, digital beamforming, beam multiplexing, site specific nulling of point clutter, split array processing for wind direction estimation and real time dwell scheduling to support adaptive scan algorithms. In this paper we provide an overview of the proposed fractional array capabilities, integration with NWRT and some of the radar design tradeoffs that may be required as the project proceeds

Kitzmiller, D. H., F. Ding, S. Van Cooten, K. Howard, C. Langston, J. Zhang, H. Moser, R. J. Kuligowski, D. Kim, Y. Zhang, D. Riley, 2008: A comparison of evolving multisensor precipitation estimation methods based on impacts on flow prediction using a distributed hydrologic model. Extended Abstracts, 22nd Conference on Hydrology, Poster Session 3 Validation of Hydrometeorological Observations, New Orleans, LA, USA, AMS, CD-ROM, P3.4.

Evolving methodologies for multisensor precipitation estimation are being investigated to determine their influence on the flow predictions of a distributed hydrologic model. These methods include the National Mosaic and Quantitative Precipitation algorithm package (NMQ) under development at the National Severe Storms Laboratory, the Multisensor Precipitation Estimator package (MPE) currently operational at National Weather Service field offices, and the Self-Calibrating Multivariate Precipitation Retrieval algorithm (SCaMPR) under development within the National Environmental Satellite, Data, and Information Service Center for Satellite Applications and Research. Our goal is to determine which combination of algorithm features offer the greatest benefit toward operational hydrologic forecasting. These features include automated radar quality control, range correction, and methods of multiple-radar data compositing, all of which vary among NMQ, MPE, and SCaMPR.

All methods described above have been applied to deriving high-resolution (4-km hourly) gridded precipitation estimates over and near the Tar River Basin of North Carolina through the course of several precipitation events during the period December 2004-January 2005. The NMQ and MPE algorithms are driven by identical WSR-88D reflectivity and rain gauge input. The GOES infrared-based SCaMPR algorithm is calibrated by comparison with contemporaneous radar rainrate fields from the NMQ. All results are currently being compared to an independent set of hourly and daily rain gauge reports; the various precipitation grids will later be input to the NWS Hydrology Laboratory - Research Distributed Hydrologic Model, to determine impacts on the quality of its discharge simulations at several gauged points on the Tar River and its tributaries. Further results will be reported in our extended abstract.

Available online at ://http://ams.confex.com/ams/88Annual/techprogram/paper_134451.htm.

Kitzmiller, D. H., F. Ding, S. Van Cooten, K. Howard, C. Langston, J. Zhang, H. Moser, R. J. Kuligowski, D. Kim, Y. Zhang, D. Riley, 2008: A comparison of evolving multisensor precipitation estimation methods based on impacts on flow prediction using a distributed hydrologic model. Extended Abstracts, 22nd Conference on Hydrology, Poster Session 3 Validation of Hydrometeorological Observations, New Orleans, LA, USA, AMS, CD-ROM, P3.4.

Evolving methodologies for multisensor precipitation estimation are being investigated to determine their influence on the flow predictions of a distributed hydrologic model. These methods include the National Mosaic and Quantitative Precipitation algorithm package (NMQ) under development at the National Severe Storms Laboratory, the Multisensor Precipitation Estimator package (MPE) currently operational at National Weather Service field offices, and the Self-Calibrating Multivariate Precipitation Retrieval algorithm (SCaMPR) under development within the National Environmental Satellite, Data, and Information Service Center for Satellite Applications and Research. Our goal is to determine which combination of algorithm features offer the greatest benefit toward operational hydrologic forecasting. These features include automated radar quality control, range correction, and methods of multiple-radar data compositing, all of which vary among NMQ, MPE, and SCaMPR.

All methods described above have been applied to deriving high-resolution (4-km hourly) gridded precipitation estimates over and near the Tar River Basin of North Carolina through the course of several precipitation events during the period December 2004-January 2005. The NMQ and MPE algorithms are driven by identical WSR-88D reflectivity and rain gauge input. The GOES infrared-based SCaMPR algorithm is calibrated by comparison with contemporaneous radar rainrate fields from the NMQ. All results are currently being compared to an independent set of hourly and daily rain gauge reports; the various precipitation grids will later be input to the NWS Hydrology Laboratory - Research Distributed Hydrologic Model, to determine impacts on the quality of its discharge simulations at several gauged points on the Tar River and its tributaries. Further results will be reported in our extended abstract.

Available online at ://http://ams.confex.com/ams/88Annual/techprogram/paper_134451.htm.

Kumjian, M. R., A. V. Ryzhkov, 2007: Polarimetric characteristics of tornadic and nontornadic supercell storms. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P10.1.

Kumjian, M. R., A. V. Ryzhkov, J. L. Alford, M. Knight, J. W. Conway, 2008: Close-range observations of a tornadic supercell with C-band polarimetric Doppler radar. Extended Abstracts, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, 88th Annual Meeting, New Orleans, LA, USA, American Meteorological Society, P2.14.

Kumjian, M. R., A. V. Ryzhkov, 2008: Microphysical size sorting revealed by dual-polarization Doppler radar. Extended Abstracts, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, 88th Annual Meeting, New Orleans, LA, USA, American Meteorological Society, P2.13.

Kumjian, M. R., A. V. Ryzhkov, 2008: Polarimetric signatures in supercell thunderstorms. Journal of Applied Meteorology and Climatology, 47, 1940-1961.

Kumjian, M. R., A. V. Ryzhkov, 2008: Interpretation of polarimetric signatures in supercell storms using explicit microphysical modeling. Extended Abstracts, 5th European Radar Conference on Radar in Meteorology and Hydrology, Helsinki, Finland, Finnish Meteorological Institute, CD-ROM, P7.2.

Available online at ://http://erad2008.fmi.fi/proceedings/extended/erad2008-0065-extended.pdf.

Kumjian, M. R., A. V. Ryzhkov, 2008: Microphysical analysis of supercell rear-flank downdrafts using dual-polarization radar observations. Extended Abstracts, 5th European Conference on Radar in Meteorology and Hydrology, Helsinki, Finland, Finnish Meteorological Institute, CD-ROM, P7.10.

Available online at ://http://erad2008.fmi.fi/proceedings/extended/erad2008-0066-extended.pdf.

Lakshmanan, V., G. Stumpf, A. Witt, 2005: A neural network for detecting and diagnosing tornadic circulations using the mesocyclone detection and near storm environment algorithms. Preprints, 21st International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, USA, American Meteorological Society, CD-ROM, J5.2.

Lakshmanan, V., G. Stumpf, 2005: A real-time learning technique to predict cloud-to-ground lightning. Preprints, 4th Conference on Artificial Intelligence Applications to Environmental Science, San Diego, CA, USA, American Meteorological Society, CD-ROM, J5.6.

Lakshmanan, V., T. M. Smith, K. Cooper, J. J. Levit, G. J. Stumpf, D. R. Bright, 2006: High-resolution radar data and products over the continental United States. Preprints, 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, 9.7.

Lakshmanan, V., I. Adrianto, T. M. Smith, G. J. Stumpf, 2005: A spatiotemporal approach to tornado prediction. Preprints, International Joint Conference on Neural Networks 2005, Montreal, Canada, INNS, 1072.

Lakshmanan, V., T. Smith, K. Hondl, G. Stumpf, A. Witt, 2006: A Real-Time, Three Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity and Derived Products. Weather and Forecasting, 21, 802-823.

With the advent of real-time streaming data from various radar networks, including most WSR-88Ds and several TDWRs, it is now possible to combine data in real-time to form three-dimensional (3D) multiple-radar grids. We describe a technique for taking the base radar data (reflectivity and radial velocity), and derived products, from multiple radars and combining them in real-time into a rapidly updating 3D merged grid. An estimate of that radar product combined from all the different radars can be extracted from the 3D grid at any time. This is accomplished through a formulation that accounts for the varying radar beam geometry with range, vertical gaps between radar scans, lack of time synchronization between radars, storm movement, varying beam resolutions between different types of radars, beam blockage due to terrain, differing radar calibration and inaccurate time stamps on radar data.

Techniques for merging scalar products like reflectivity as well as innovative, real-time techniques for combining velocity and velocity-derived products are demonstrated. Precomputation techniques that can be utilized to perform the merging in real-time and derived products that can be computed from these three-dimensional merger grids are described.

Available online at ://http://cimms.ou.edu/~lakshman/Papers/.

Lakshmanan, V., A. Fritz, T. Smith, K. Hondl, G. J. Stumpf, 2007: An automated technique to quality control radar reflectivity data. Journal of Applied Meteorology, 46, 288-305.

Echoes in radar reflectivity data do not always correspond to precipitating particles. Echoes on radar may be due to biological targets such as insects, birds or wind-borne particles, due to anomalous propagation (AP) or ground clutter (GC) or due to test and interference patterns that inadvertently seep into the final products. Although weather forecasters can usually identify, and account for, the presence of such contamination, automated weather radar algorithms are drastically affected.

Several horizontal and vertical features have been proposed to discriminate between precipitation echoes and echoes that do not correspond to precipitation. None of these features by themselves can discriminate between precipitating and non-precipitating areas. In this paper, we use a neural network to combine the individual features, some of which have already been proposed in the literature and some of which we introduce in this paper, into a single discriminator that can distinguish between "good" and "bad" echoes (i.e., precipitation and non-precipitation respectively). The method of computing the horizontal features leads to statistical anomalies in their distributions near the edges of echoes. We describe how to avoid presenting such range gates to the neural network. The gate-by-gate discrimination provided by the neural network is followed by more holistic postprocessing based on spatial contiguity constraints and object identification to yield quality-controlled radar reflectivity scans that have most of the bad echo removed, while leaving most of the good echo untouched. A possible multi-sensor extension, utilizing satellite data and surface observations, to the radar-only technique is also demonstrated. We demonstrate the resulting technique is highly skilled, and that its skill exceeds that of the currently operational algorithm.

Available online at ://http://cimms.ou.edu/~lakshman/Papers/qcnnjam.pdf.

Lakshmanan, V., K. L. Ortega, T. M. Smith, 2007: Creating spatio-temporal tornado probability forecasts using fuzzy logic and motion variability. Preprints, Fifth Conference on Artificial Intelligence Applications to Environmental Science, San Antonio, TX, USA, AMS, CD-ROM, 2.3.

In this paper, we describe our approach to addressing the problem of creating good probabilistic forecasts when the entity to be forecast can move and morph. We formulate the tornado prediction problem to be one of estimating the probability of an event at a particular spatial location within a given time window. The technique involves clustering Doppler radar-derived fields such as low-level shear and reflectivity to form candidate regions. Assuming stationarity, the spatial probability distribution of this region T minutes ahead is estimated and combined with the probability that the candidate region becomes tornadic T minutes later. Using these two probabilities and the variability of the motion estimates, a spatio-temporal probability field is derived.

The neural network training required to correctly estimate the probabilities has not yet been developed. Therefore, this paper illustrates the underlying idea using fuzzy logic, storm half-life and motion variability.

Available online at ://http://ams.confex.com/ams/pdfpapers/119456.pdf.

Lakshmanan, V., T. M. Smith, G. J. Stumpf, K. D. Hondl, 2007: The Warning Decision Support System—Integrated Information. Weather and Forecasting, 22, 596-612.

The Warning Decision Support System—Integrated Information (WDSS-II) is the second generation of a system of tools for the analysis, diagnosis, and visualization of remotely sensed weather data. WDSS-II provides a number of automated algorithms that operate on data from multiple radars to provide information with a greater temporal resolution and better spatial coverage than their currently operational counterparts. The individual automated algorithms that have been developed using the WDSS-II infrastructure together yield a forecasting and analysis system providing real-time products useful in severe weather nowcasting. The purposes of the individual algorithms and their relationships to each other are described, as is the method of dissemination of the created products.

Lakshmanan, V., 2007: An overview of radar data compression. Proc. SPIE Optics + Photonics: Satellite Data Compression, Communications and Archiving III, San Diego, CA, USA, SPIE, CD-ROM, 6683-07.

We describe how radar data is transmitted, compressed and archived. We note that although custom compression techniques have been devised for radar data that outperform generic techniques, radar operations groups ultimately use off-the-shelf solutions. We also point out that the underlying ideas behind compressibility are useful beyond just reducing the amount of data for transmission and archival. The compressibility of radar data has been found useful for devising quality control algorithms, especially for the detection and removal of test patterns.

Available online at ://http://cimms.ou.edu/%7Elakshman/Papers/radarcompression.pdf.

Lakshmanan, V., K. Hondl, 2007: A polar-coordinate real-time three-dimensional rapidly updating merger technique for phased array radar scanning strategies. Proc. 33rd Conference on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., CD-ROM, 7.4.

The National Weather Radar Testbed (NWRT) phased array radar will not be operated in fixed volume coverage patterns. Instead, the phased array radar will attempt to simultaneously maximize the utility of several possible uses, such as 3D storm analysis, area surveillance and aircraft tracking. In order to do so, the phased array radar will employ adaptive scanning and intersperse meteorological scans with aircraft tracking. To a downstream visualization program or automated severe-weather detection algorithm operating on phased array radar data, the incoming stream will be randomly organized in space and time. It is up to the application to create a coherent view of the atmosphere from the phased array radar beams.

In this paper, we describe a method of creating such a coherent view. In polar coordinates, this involves creating a rapidly updated "virtual volume scan". The virtual volume scan is created by treating each of the phased array radar range gates as "intelligent agents" that place themselves in the resulting polar grid, know how to collaborate with other agents to create optimal estimates of the radar values at each range gate of the virtual volume and know when they have either been superseded or are too old. The resulting virtual volume, created in real-time, is used by the downstream applications. This enables the downstream applications to work with a regularly spaced grid that is created at periodic intervals.

Available online at ://http://cimms.ou.edu/%7Elakshman/Papers/polarmerger.pdf.

Lakshmanan, V., J. Zhang, C. Langston, 2008: Quality control of Canadian radar reflectivity data. Proc. European Conference on Radar in Meteorology and Hydrology, Helsinki, Finland, Finnish Meteorological Institute, P2.11.

Langston, C., J. Zhang, K. Howard, 2007: Four-Dimensional Dynamic Radar Mosaic. Journal of Atmospheric and Oceanic Technology, 24, 776-790.

Le, K. D., R. D. Palmer, S. M. Torres, T.-Y. Yu, D. Zrnic, 2005: On the Use of Polarimetric Radars for Studies of Clouds: Numerical Simulations and S-Band Radar Observations. Preprints, 32nd International Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, 9R.7.

Le, K. D., R. D. Palmer, T. Y. Yu, G. Zhang, S. M. Torres, B. L. Cheong, 2007: Improving Angular Resolution Using Adaptive Processing for Multifunction Phased Array Radar. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, CD-ROM, P2.14A.

Le, K. D., R. D. Palmer, T. Y. Yu, G. Zhang, S. M. Torres, B. L. Cheong, 2007: Adaptive Array Processing for Multi-Mission Phased Array Radar. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P7.2.

As the use of phased array radars becomes more established for weather surveillance, adaptive array processing techniques will become more important to the weather radar community. Such techniques can be applied to phased array radars to improve angular resolution and also to suppress clutter compared to conventional beamforming methods. Thus, enhanced details of weather phenomena can be realized in terms of finer and better estimates of the reflectivity and radial velocity. This paper compares the performance of conventional beamforming to the performance of adaptive array processing based methods for a fully adaptive array and a partially adaptive array with six sidelobe-canceling elements, which is the configuration of the Phased Array Radar (PAR) of the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. Different scenarios of fading clutter and clutter positions relative to the steering directions are considered. The simulated phased array concept uses a transmit beam that is wide in both angular directions to illuminate a large field of view and is thus termed an imaging radar . The receiver consists of individual antenna elements placed in a planar configuration. Time series signals for each antenna element are generated using a realistic radar simulator based on point-target scatterers, which flow and scatter according to a simulated environment produced from the Advanced Regional Prediction System (ARPS). Preliminary results show that, as expected, the performance of more sophisticated adaptive algorithms is better compared to conventional beamforming, both in terms of angular resolution and clutter suppression.

Available online at ://http://ams.confex.com/ams/pdfpapers/123304.pdf.

Le, K., R. Palmer, B. Cheong, T. Yu, G. Zhang, S. M. Torres, 2008: Novel Adaptive Beamforming Techniques for Atmospheric Imaging Radars. Preprints, 24rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, New Orleans, LA, USA, AMS, CD-ROM, 9A.5.

Liu, S., C. Qiu, Q. Xu, P. Zhang, J. Gao, A. Shao, 2005: An improved method for Doppler wind and thermodynamic retrievals. Advances in Atmospheric Sciences, 22, 90-102.

Liu, S., Q. Xu, P. Zhang, 2005: Quality control of Doppler velocities contaminated by migrating birds. Part II: Bayes identification and probability tests. Journal of Atmospheric and Oceanic Technology, 22, 1114-1121.

Liu, L., P. Zhang, Q. Xu, F. Kong, S. Liu, 2005: Retrieval model of dual linear polarization radar observations from simulation model output.. Adv. Atmos. Sci. 22, 711-719., 22, 711-719.

Lund, N., D. MacGorman, D. Rust, T. Schuur, P. Krehbiel, W. Rison, T. Hamlin, J. Straka, M. Biggerstaff, 2007: Relationship between lightning location and polarimetric radar signatures in an MCS. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, IUGG/Commission on Atmospheric Electricity, PS5-2.

The relationship of lightning initiation and structure to the storm microphysics and structure depicted by polarimetric radar has been analyzed for a small mesoscale convective system (MCS) that occurred on 19 June 2004 during the Thunderstorm Electrification and Lightning Experiment (TELEX). Horizontal reflectivity (Z), differential reflectivity (Zdr), specific differential phase (Kdp) and correlation coefficient (ρHV) data were gathered by a 10-cm, polarimetric radar located in Norman, Oklahoma. Three-dimensional lightning structure was mapped by the Oklahoma Lightning Mapping Array (OK-LMA), and ground strike points were mapped by the United States National Lightning Detection Network. OK-LMA data were processed to group mapped points into flashes and to determine the initiation location of each flash that contained more than 10 mapped points. The initiation location was calculated by sequentially eliminating outliers among the first 10 points that occurred in a flash, with no fewer than 5 points being used in the final initiation location. The initiation location and mapped points for each flash were superimposed on polarimetric radar data in order to investigate lightning relationships with storm structure. The lightning initiation points tended to cluster together in one of two altitude ranges and were almost all in the convective line. Initial results show a relationship between the lightning initiation locations and radar signatures in both Z and Kdp. In the lower altitude range, between 3 and 5 km MSL, initiation locations tended to cluster around updraft cores, in regions characterized by a transition in Z from 50 to 55 dBZ and a transition in Kdp from 0.4 to 0.5 deg/km. In the upper range, between 8 and 10 km MSL, initiation points tended to cluster directly above the updrafts, in regions characterized by a transition in Z from 42.5 to 47.5 dBZ and in Kdp from 0.075 to 0.150 deg/km. The two-layer nature of the initiation points is consistent with grossly tripolar structure of the charge distribution involved in lightning in the convective line. Also, the horizontal pattern of the initiation locations has a quasi-periodic horizontal structure which is 180 degrees out of phase with the maximum updraft locations for the lower region and is in phase with the maximum updraft locations for the upper region. There were also a few flash initiations within the stratiform region, possibly associated with decaying cells. The values of Z and Kdp associated with these initiation points were smaller than in the convective line, but as in the convective line, the initiations also occurred along gradients, above a local maximum, in these parameters.

Lund, N., D. R. MacGorman, W. D. Rust, T. J. Schuur, P. Krehbiel, W. Rison, T. Hamlin, J. Straka, M. Biggerstaff, 2008: Relationship between lightning location and polarimetric radar signatures in an MCS. Preprints, 3rd Conference on Meteorological Applications of Lightning Data, New Orleans, LA, USA, American Meteorological Society, P1.5.

MacGorman, D., D. Rust, T. Schuur, M. Biggerstaff, J. Straka, C. Ziegler, E. Mansell, P. Krehbiel, W. Rison, T. Hamlin, L. Carey, E. Bruning, K. Kuhlman, N. Ramig, C. Payne, 2005: Lightning Relative to Storm Structure and Microphysics in TELEX. Polarimetric radar and electrical structure of a multicell storm. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, 10R.7.

MacGorman, D., K. Kuhlman, D. Rust, M. Biggerstaff, T. Schuur, J. Straka, P. Krehbiel, B. Rison, L. Carey, 2007: Lightning and electrical structure of a heavy-precipitation supercell storm during TELEX. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, IUGG/Commission on Atmospheric Electricity, OS5-1.

The Thunderstorm Electrification and Lightning Experiment (TELEX) observed a heavy-precipitation (HP) supercell storm in central Oklahoma on 29 May 2004. In a HP supercell storm, the initial location of the mesocyclone, which is the parent rotation of tornadoes, is embedded well within the precipitation of the storm, instead of being on the edge of the storm (as in classic and low-precipitation supercell storms). Two 5-cm wavelength mobile Doppler radars were positioned near the storm and collected volume scans every 3 minutes for 3 h beginning as the storm became supercellular. The storm had supercell characteristics for this entire period. The Oklahoma Lightning Mapping Array provided three-dimensional data throughout the storm’s supercellular stage and provided two-dimensional data from the time of storm initiation in western Oklahoma. A 10-cm wavelength polarimetric radar also provided data for much of this period.
Lightning flash rates became extraordinarily large as the storm evolved into a supercell and its motion turned rightward. Flash rates increased again (to an estimated peak value of almost 500 flashes per minute) shortly before the storm produced a tornado rated F2 on the Fujita scale. During this period, an upward pulse in lightning density extended as high as 18 km MSL in a plume extending above the equilibrium level, and the region of lightning activity pulsed eastward far into the anvil, up to 150 km from the western edge of the storm. A series of minimums in the plan projection of lightning density (i.e., lightning holes) formed just above the bounded weak echo region. A dual-Doppler synthesis of wind during one volume scan shows the lightning hole was co-located with large vertical wind speeds in the rotating updraft. The hole apparently occurred because precipitation particles had little time to grow and gain charge in the strong updraft before they were lifted to upper regions of the storm and advected outward by flow from the diverging updraft. Cloud-to-ground lightning activity in and near heavy precipitation was dominated initially by negative ground flashes, but during part of the supercell phase, evolved to become dominated by positive ground flashes. Lightning mapping data suggest that, when positive ground flashes dominated, the vertical polarity of the storm’s electrical structure was inverted from the usual polarity.

MacGorman, D. R., W. D. Rust, T. J. Schuur, M. I. Biggerstaff, J. M. Straka, C. L. Ziegler, E. R. Mansell, E. C. Bruning, K. M. Kuhlman, N. R. Lund, N. S. Biermann, C. Payne, L. D. Carey, P. R. Krehbiel, W. Rison, K. B. Eack, W. H. Beasley, 2008: TELEX: The Thunderstorm Electrification and Lightning Experiment. Bulletin of the American Meteorological Society, 89, 997-1013.

The field program of the Thunderstorm Electrification and Lightning Experiment (TELEX) took place in central Oklahoma, May–June 2003 and 2004. It aimed to improve understanding of the interrelationships among microphysics, kinematics, electrification, and lightning in a broad spectrum of storms, particularly squall lines and storms whose electrical structure is inverted from the usual vertical polarity. The field program was built around two permanent facilities: the KOUN polarimetric radar and the Oklahoma Lightning Mapping Array. In addition, balloon-borne electric-field meters and radiosondes were launched together from a mobile laboratory to measure electric fields, winds, and standard thermodynamic parameters inside storms. In 2004, two mobile C-band Doppler radars provided high-resolution coordinated volume scans, and another mobile facility provided the environmental soundings required for modeling studies. Data were obtained from twenty-two storm episodes, including several small isolated thunderstorms, mesoscale convective systems, and supercell storms. Examples are presented from three storms. A heavy-precipitation supercell storm on 29 May 2004 produced greater than 3 flashes per second for 1.5 h. Holes in the lightning density formed and dissipated sequentially in the very strong updraft and bounded weak echo region of the mesocyclone. In a small squall line on 19 June 2004, most lightning flashes in the stratiform region were initiated in or near strong updrafts in the convective line and involved positive charge in the upper part of the radar bright band. In a small thunderstorm on 29 June 2004, lightning activity began as polarimetric signatures of graupel first appeared near lightning initiation regions.

Available online at ://http://ams.allenpress.com/archive/1520-0477/89/7/pdf/i1520-0477-89-7-997.pdf.

MacGorman, D., T. Schuur, M. Kumjian, 2008: Total lightning activity during the re-intensification of Tropical Storm Erin over Oklahoma on 18–19 August 2007. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, American Meteorological Society, 7A.5.

The remnants of Tropical Storm Erin made landfall on the Texas coast on 16 August 2007 and reached Oklahoma on 18 August, where it produced tornadoes, severe straight-line winds, and flooding. In west-central Oklahoma (roughly 800 km from the coast), the system re-intensified and formed an eye and rainband structure characteristic of tropical cyclones. The Oklahoma Mesonet indicated that the system eventually produced greater sustained winds (26 m s-1, 58 mph) and a lower central pressure (1001.3 hPa) than it had produced over open water.

The eye, which fluctuated from 5 to 25 km in diameter, was first apparent on lightning and radar displays at 4:50 am local time and began dissipating over Oklahoma City at 9:50 am. Throughout the period during which the eye formed and dissipated, the eye and the majority of the area of rainbands were well within the region in which the Oklahoma Lightning Mapping Array maps lightning in three dimensions and in which the KOUN S-Band radar provides polarimetric data. Both radar displays and displays of lightning density delineated the formation of the eye and rainband well. Convection extended highest and lightning rates were greatest in the rainband on the southeast flank. The height of convection in the rainband decreased as one approached the eye, and the decrease in height extended around the eye as the eye formed. Some long, horizontal flashes extended eastward from storms along the east side of the eye into the region of widespread light precipitation east of the rainband. The appearance of these long horizontal flashes was similar to the lightning structure observed in the stratiform precipitation regions of mesoscale convective systems. As the cyclone structure weakened, convection on the west side of the eye dissipated, and the remnants of the rainband on the east side propagated eastward as a line of storms.

Though the lightning in this system was probably influenced by being over land, this case still may provide clues to what happens electrically in tropical cyclones over open water, where continuous observations of total lightning activity during tropical cyclone intensification and dissipation are not yet available.

Available online at ://http://www.ametsoc.org.

Marchand, R. N., N. Beagley, S. Thompson, T. P. Ackerman, D. M. Schultz, 2006: A bootstrap technique for testing the relationship between local-scale radar observations of cloud occurrence and large-scale atmospheric fields. Journal of the Atmospheric Sciences, 63, 2813-2830.

Melnikov, V. M., D. S. Zrnic, 2005: Measurements of polarimetric parameters at low signal-to-noise ratios. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P9R.2.

Melnikov, A. V., V. M. Melnikov, A. V. Ryzhkov, 2005: On the differential phase in the melting layer. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P9R.9.

Melnikov, V. M., 2006: One-lag estimators for cross-polarization measurements. Journal of Atmospheric and Oceanic Technology, 23, 915-926.

Estimators of the linear depolarization ratio (LDR) and cross-polarization correlation coefficients (ρxh ) free from noise biases are devised. The estimators are based on the 1-lag correlation functions. The 1-lag estimators can be implemented with radar with simultaneous reception of copolar and cross-polar returns. Absence of noise biases makes the1-lag estimators useful in eliminating variations of the system gain and in observations of heavy precipitation with enhanced thermal radiation. The 1-lag estimators allow for measurements at lower signal-to-noise ratios than the conventional algorithms.

The statistical biases and standard deviations of 1-lag estimates are obtained via the perturbation analysis. It is found that both the 1-lag and conventional estimates of ρxh experience strong statistical biases at ρxh less than 0.3 (i.e. at low canting angles of oblate hydrometeors) and a procedure to correct for this bias is proposed.

Melnikov, V. M., D. S. Zrnic, 2007: Autocorrelation and cross-correlation estimators of polarimetric variables. Journal of Atmospheric and Oceanic Technology, 24, 1337-1350.

Herein are proposed novel estimators of differential reflectivity, ZDR, and correlation coefficient, ρ, between horizontally and vertically polarized echoes. The estimators use autocorrelations and cross-correlations of the returned signals to avoid bias by omnipresent but varying white noise. These estimators are considered for implementation on the future polarimetric WSR-88D network. On the current network the reflectivity factor is measured at signal-to-noise ratios (SNR) as low as 2 dB and the same threshold is expected to hold for the polarimetric variables. At such low SNR and all the way up to SNR = 15 dB, the conventional estimators of differential reflectivity and the copolar correlation coefficient are prone to errors due to uncertainties in noise levels caused by instability of radar devices, thermal radiations of precipitation and the ground, and wideband radiation of electrically active clouds. Noise variations less than 15 dB can bias the estimates beyond apparatus accuracy. For short we refer to the estimators of ZDR and ρ free from noise bias as the “1-lag estimators” because these are derived from 1-lag correlations. The estimators are quite robust and the only weak assumption for validity is that spectral widths of signals from vertically and horizontally polarized returns are equal. This assumption is verified on radar data. Radar observations demonstrate the validity of these estimator and lower sensitivity to interference signals than the conventional algorithms.

Melnikov, V. M., D. S. Zrnic, R. J. Doviak, Y. L. Kogan, P. B. Chilson, D. B. Mechem, 2007: The WSR-88D observes non precipitating clouds. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P6A3.

Preliminary observations made with the WSR-88D show sufficient sensitivity of the radar to measure parameters of non-precipitating clouds. Cloud characteristics can be obtained with the WSR-88D in scanning mode, i.e., to generate “instant” fields of spectral moments. Cloud observations with the WSR-88Ds can be used in studies related to the development and evolution of clouds and precipitation, cloud model parameterization, application to climate effects, and radiation transfer in the atmosphere

Melnikov, V., D. S. Zrnic, R. M. Rabin, P. Zhang, 2008: Radar polarimetric signatures of fire plumes in Oklahoma. Geophysical Research Letters, 35, .

Radar observations of wild fire plumes in Oklahoma carried out with the prototype of dual polarization S-band WSR-88D weather radar are presented. The observations show that the copolar correlation coefficients between horizontally and vertically polarized returns in the plumes are mostly less than 0.4 and this can be used in identification of plumes.

Melnikov, V., R. J. Doviak, 2008: Strong wind shears in stratiform precipitation observed with weather radar. Extended Abstracts, 13th Conference on Aviation, Range, and Aerospace Meteorology., New Orleans, LA, USA, AMS, 12.4.

Morris, M., P. Chilson, G. Zhang, Q. Cao, R. Palmer, M. Teshiba, L. Kanofsky, T. Schuur, A. Ryzhkov, 2008: Validation of rainddrop size distributions retrieved from polarimetric radar variables. Preprints, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, New Orleans, LA, USA, American Meteorological Society, P2.4.

Morris, M., P. Chilson, A. Ryzhkov, T. Schuur, M. Teshiba, R. Palmer, 2008: Application of polarimateric radar to improve wind profiler-based microphysical retrieval. Preprints, Fifth European Conference on Radar in Meteorology and Hydrology, Helsinki, Finland, Finnish Meteorological Institute, 7.4.

Orescanin, M. B., T. Y. Yu, C. D. Curtis, D. S. Zrnic, D. E. Forsyth, 2005: Signal processing of Beam-multiplexed data for Phased-Array weather radar. Extended Abstracts, 32nd Conference on Radar Meteorology, Alburqueue, NM, USA, American Meteorological Society, CD-ROM, 4R.6.

The S-band Phased Array Radar(PAR) has been recently installed at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. It is equipped with the SPY-1A phased array antenna loaned by the NAVY and can rapidly and adaptively scan multiple regions of interest. Beam-multiplexing makes further use of the PAR's beam agility to provide high-quality and rapid-update weather observations. In a beam-multiplexing mode regions of interest are re-sampled after weather signals become uncorrelated. As a result, the statistical error of spectral moment estimation can be reduced optimally through the average of a number of independent measurements. Moreover, PAR can be tasked to probe other regions during the period of re-sampling to maximize the use of radar resources. Thus PAR can provide fast update of weather information in regions of interest. In this work, the idea of beam-multiplexing is presented and verified using numerical simulation. An experiment was designed to demonstrate the feasibility and advantage of beam-multiplexing. The PAR and the research WSR-88D (KOUN) were coordinated to simultaneously scan the same region using beam-multiplexing and conventional sampling, respectively. Preliminary results have shown that data quality and update rate can be improved using PAR beam-multiplexing.

Pal, N. R., A. K. Mandal, S. Pal, J. Das, V. Lakshmanan, 2006: Fuzzy Rule-Based Approach for Detection of Bounded Weak-Echo Regions in Radar Images. Journal of Applied Meteorology, 45, 1304-1312.

A method for the detection of a bounded weak-echo region (BWER) within a storm structure that can help in the prediction of severe weather phenomena is presented. A fuzzy rule-based approach that takes care of the various uncertainties associated with a radar image containing a BWER has been adopted. The proposed technique automatically finds some interpretable (fuzzy) rules for classification of radar data related to BWER. The radar images are preprocessed to find subregions (or segments) that are suspected candidates for BWERs. Each such segment is classified into one of three possible cases: strong BWER, marginal BWER, or no BWER. In this regard, spatial properties of the data are being explored. The method has been tested on a large volume of data that are different from the training set, and the performance is found to be very satisfactory. It is also demonstrated that an interpretation of the linguistic rules extracted by the system described herein can provide important characteristics about the underlying process.

Palmer, R. D., T. Y. Yu, G. Zhang, P. B. Chilson, M. I. Biggerstaff, M. B. Yeary, S. M. Torres, J. E. Crain, Y. Zhang, 2007: Weather radar education at the University of Oklahoma: An integrated inter-disciplinary approach. Proc. 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P13B.10.

In recent years, the University of Oklahoma (OU) has invested heavily in the development of a strategic research initiative in radar meteorology. Several new faculty members, with interests in weather radar, have joined both the School of Meteorology (SoM) and the School of Electrical and Computer Engineering (ECE). This inter-disciplinary group of energetic meteorologists and engineers has established the Atmospheric Radar Research Center (ARRC). The ARRC supports a broad portfolio of research interests, including radar polarimetry, phased array radar, profiling radar, advanced signal processing, retrieval algorithms, clutter mitigation, severe storm observations and detection, quantitative precipitation estimation, and general studies of atmospheric physics. In addition to research, one of the fundamental goals of the ARRC is providing OU students with a comprehensive, challenging education in the area of radar meteorology, emphasizing both the engineering and meteorological aspects of the field. We achieve our educational goals, in part, by the creation and continual maintenance of a synergistic curriculum exploiting the complementary disciplines of meteorology and electrical/computing engineering. As an integral component of OU's radar program, an innovative and coherent sequence of radar-related courses has been developed which serves both our undergraduate and graduate educational goals. This novel curriculum is not independent of, but forms an important component of the more traditional curricula of the two disciplines. Given the importance of weather radar for many observational studies of atmospheric phenomena, it is essential to include a significant hands-on experience for the students. Our curriculum provides a complete theoretical framework with which to understand weather radar theory while also providing access to local weather radar systems. In close collaboration with our NOAA partners at the National Severe Storms Laboratory (NSSL), we have developed laboratory modules for many of the radar courses using the C-band SMART radars, the S-band phased array radar, and the S-band KOUN polarimetric Doppler radar. Experimental design, operation, data analysis, and interpretation are emphasized. A description of the curriculum development effort will be provided. In addition, example laboratory modules will be presented emphasizing the practical aspects of this program.

Available online at ://http://ams.confex.com/ams/pdfpapers/123307.pdf.

Palmer, R., G. Zhang, M. Biggerstaff, P. Chilson, J. Crain, S. Torres, M. Yeary, T. Y. Yu, Y. Zhang, 2007: University Profile: Atmospheric Radar Research Center at the University of Oklahoma. IEEE Trans. Geosci. Remote Sensing. Newsletter, 1, 10-16.

Available online at ://http://www.grss-ieee.org/files/grsNL0307.pdf.

Park, H. S., A. V. Ryzhkov, D. S. Zrnic, K. E. Kim, 2007: Optimization of the matrix of weights in the polarimetric algorithms for classification of radar echoes. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P11B.12.

Payne, C., T. J. Schuur, D. R. MacGorman, W. D. Rust, M. Biggerstaff, K. Kuhlman, E. Bruning, N. Lund, 2008: Electrical and polarimetric radar observations of an HP supercell on 29 May 2004 during TELEX. Preprints, 3rd Conference on Meteorological Applications of Lightning Data, New Orleans, LA, USA, American Meteorological Society, 4.6.

Pinto, J., C. Kessinger, B. Hendrickson, D. Megenhardt, P. Harasti, Q. Xu, P. Zhang, Q. Zhao, M. Frost, J. Cook, S. Potts, 2007: Storm characterization and short term forecasting potential using a phase array radar. Extended Abstracts, 33rd Conference on Radar Meteorology. 6–10 August 2007, Cairns, Australia. Amer. Meteor. Soc.,, Cairns, Australia, Amer. Meteor. Soc., P5.18.

Available online at ://http://ams.confex.com/ams/pdfpapers/123703.pdf.

Priegnitz, D. L., D. E. Forsyth, 2006: The Radar Control Interface for the National Weather Radar Testbed. Extended Abstracts, 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, American Meteorological Society, 11.2. [Available from David Priegnitz, NSSL, 1313 Halley Circle, Norman, OK, USA, 73069.]

The National Weather Radar Testbed (NWRT) in Norman Oklahoma is a national weather research facility consisting of a converted Navy SPY-1 phased-array radar system. It is expected to be utilized by researchers both inside and outside the Norman area. One goal of the facility s to allow researchers to operate the radar and collect data without having to travel to Norman. A new Radar Control Interface (RCI) is being developed to simplify radar control and data collection operations. This paper describes the design and operation of the new RCI.

Available online at ://http://ams.confex.com/ams/Annual2006/techprogram/paper_104391.htm.

Priegnitz, D. L., 2007: UPDATE TO THE NATIONAL WEATHER RADAR TESTBED RADAR CONTROL INTERFACE. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS), San Antonio, TX, USA, American Meteorological Society, CD-ROM, 8A.2. [Available from David Priegnitz, 120 David L. Boren Blvd., Norman, OK, USA, 73072.]

Significant improvements have been made to the National Weather Radar Testbed (NWRT) Radar Control Interface (RCI) over the past year to support research operations. The "look and feel" of the RCI has been modified to improve human-computer interaction. New process control functions have been implemented to better notify the operator of problems, allowing them to take corrective actions in a more timely manner. New processes have been added to simplify the building of scan control files, called "Stimulus Files", and integrating them into the system.

This paper describes in more detail the improvements to the RCI.

Available online at ://http://ams.confex.com/ams/87ANNUAL/techprogram/paper_117163.htm.

Priegnitz, D. L., P. L. Heinselman, C. D. Curtis, 2007: Dynamica scanning for the National Weather Radar Testbed. Extended Abstracts, 33rd International Radar Meteorology Conference, Cairns, Australia, American Meteorological Society, CD-ROM, 7.3. [Available from David Priegnitz, 120 David L Boren Blvd, Norman, OK, USA, 73072.]

During 2006 data collected on several convective storms with the National Weather Radar Testbed (NWRT) Phased Array Radar (PAR) demonstrated the benefits of scanning strategies based on higher temporal and spacial resolutions. The analysis of these data showed that increasing the temporal resolution of a volume scan could potentially benefit short-term forecasting by identifying rapidly changing features that would otherwise be missed with the longer scan times of conventional mechanically scanned radars (i.e., WSR-88D). Furthermore, the data collection demonstrated that storm location plays an important role in determining the best scanning strategy to use. For each of these events, a single pre-defined scanning strategy was chosen to meet the data collection goals at a given time. In many instances, it would have been desirable to "fine-tune" the scanning strategy by changing the number of elevation cuts, reducing azimuthal sector width, etc.

In this paper, changes to the NWRT software that allow "dynamic scanning" of convective events are discussed. Dynamic scanning allows the operator to update scan properties in real-time. It also provides the operator with the capability to schedule more than one scanning strategy (i.e., one or more focused rapid scan strategies followed by a surveillance scanning strategy). Preliminary results on the effectiveness of dynamic scanning used to support projects during the 2007 spring season will be discussed in the extended abstract.

Priegnitz, D., D. E. Forsyth, 2007: Update to the National Weather Radar Testbed Radar Control Interface. Preprints, The 23rd Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, American Meteorological Society, CD-ROM, 8A.2.

Ramig, N., D. MacGorman, W. D. Rust, T. J. Schuur, E. Bruning, P. Krehbiel, W. Rison, T. Hamlin, J. Straka, C. Payne, I. Apostolakopoulos, M. Biggerstaff, N. Biermann, L. Carey, 2005: The stratiform region of an MCS on 19 June in TELEX 2004 observed with polarimetric and Doppler radars, electric field soundings, and a lightning mapping array. Preprints, AGU Fall Meeting, San Francisco, CA, USA, American Geophysical Union, AE21A-0977.

Ramig, N., D. MacGorman, D. Rust, T. Schuur, P. Krehbiel, W. Rison, T. Hamlin, J. Straka, M. Biggerstaff, 2007: Relationship between lightning location and polarimetric radar signatures in an MCS. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, IUGG/Commission on Atmospheric Electricity, PS5-2.

The relationship of lightning initiation and structure to the storm microphysics and structure depicted by polarimetric radar has been analyzed for a small mesoscale convective system (MCS) that occurred on 19 June 2004 during the Thunderstorm Electrification and Lightning Experiment (TELEX). Horizontal reflectivity (Z), differential reflectivity (Zdr), specific differential phase (Kdp) and correlation coefficient (ρHV) data were gathered by a 10-cm, polarimetric radar located in Norman, Oklahoma. Three-dimensional lightning structure was mapped by the Oklahoma Lightning Mapping Array (OK-LMA), and ground strike points were mapped by the United States National Lightning Detection Network. OK-LMA data were processed to group mapped points into flashes and to determine the initiation location of each flash that contained more than 10 mapped points. The initiation location was calculated by sequentially eliminating outliers among the first 10 points that occurred in a flash, with no fewer than 5 points being used in the final initiation location. The initiation location and mapped points for each flash were superimposed on polarimetric radar data in order to investigate lightning relationships with storm structure. The lightning initiation points tended to cluster together in one of two altitude ranges and were almost all in the convective line. Initial results show a relationship between the lightning initiation locations and radar signatures in both Z and Kdp. In the lower altitude range, between 3 and 5 km MSL, initiation locations tended to cluster around updraft cores, in regions characterized by a transition in Z from 50 to 55 dBZ and a transition in Kdp from 0.4 to 0.5 deg/km. In the upper range, between 8 and 10 km MSL, initiation points tended to cluster directly above the updrafts, in regions characterized by a transition in Z from 42.5 to 47.5 dBZ and in Kdp from 0.075 to 0.150 deg/km. The two-layer nature of the initiation points is consistent with grossly tripolar structure of the charge distribution involved in lightning in the convective line. Also, the horizontal pattern of the initiation locations has a quasi-periodic horizontal structure which is 180 degrees out of phase with the maximum updraft locations for the lower region and is in phase with the maximum updraft locations for the upper region. There were also a few flash initiations within the stratiform region, possibly associated with decaying cells. The values of Z and Kdp associated with these initiation points were smaller than in the convective line, but as in the convective line, the initiations also occurred along gradients, above a local maximum, in these parameters.

Rust, W. D., D. R. MacGorman, T. J. Schuur, P. Krehbiel, T. Hamlin, M. Biggerstaff, L. Carey, J. Straka, C. Payne, A. Caine, 2005: The stratiform region of an MCS on 19 June in TELEX 2004 observed with polarimetric radar, electric field soundings, and a lightning mapping array. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, J3J.5.

Ryzhkov, A. V., T. J. Schuur, D. W. Burgess, D. S. Zrnic, 2005: Polarimetric tornado detection. Journal of Applied Meteorology, 44, 557-570.

Ryzhkov, A. V., S. E. Giangrande, T. J. Schuur, 2005: Rainfall estimation with a polarimetric prototype of WSR-88D. Journal of Applied Meteorology, 44, 502-515.

Ryzhkov, A. V., T. J. Schuur, D. W. Burgess, P. L. Heinselman, S. E. Giangrande, D. S. Zrnic, 2005: The Joint Polarization Experiment: Polarimetric rainfall measurements and hydrometeor classification. Bulletin of the American Meteorological Society, 86, 809-824.

Ryzhkov, A. V., S. E. Giangrande, V. M. Melnikov, T. J. Schuur, 2005: Calibration Issues of Dual-Polarization Radar Measurements. Journal of Atmospheric and Oceanic Technology, 22, 1138-1155.

Ryzhkov, A. V., D. S. Zrnic, 2005: Radar Polarimetry at S, C, and X bands. Comparative Analysis and Operational Implications. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, 9R.3.

Ryzhkov, A. V., 2005: On the Use of Differential Phase for Polarimetric Rainfall Measurements. A New Approach to Kdp Estimation. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P9R.8.

Ryzhkov, A. V., 2007: The impact of beam broadening on the quality of radar polarimetric data. Journal of Atmospheric and Oceanic Technology, 24, .

Ryzhkov, A. V., D. S. Zrnic, 2007: Depolarization in ice crystals and its effect on radar polarimetric measurements. Journal of Atmospheric and Oceanic Technology, 24, .

Ryzhkov, A. V., D. S. Zrnic, P. Zhang, J. Krause, H. Park, D. Hudak, J. Young, J. L. Alford, M. Knight, J. W. Conway, 2007: Comparison of polarimetric algorithms for hydrometeor classifcation at S and C bands. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, 10.3.

Ryzhkov, A. V., P. Zhang, D. Hudak, J. L. Alford, M. Knight, J. W. Conway, 2007: Validation of polarimetric methods for attenuation correction at C band. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P11B.12.

Sachidananda, M., D. S. Zrnic, 2006: Ground Clutter Filtering Dual_polarized, Staggered PRT Sequnece-. Journal of Atmospheric and Oceanic Technology, 23, 1114-1130.

A procedure to filter the ground clutter from a dual polarized staggered PRT sequence and recover the complex spectral coefficients of the weather signal is presented. While magnitude spectra are sufficient for estimation of the spectral moments from staggered PRT sequences, computation of differential phase in dual polarized radars requires recovery of the complex spectra. Herein a method is given to recover the complex spectral coefficients after the ground clutter is filtered. Under the condition of "narrow" spectra, it is possible to recover the differential phase, ФDP, and the copolar correlation coefficient, ρhv accurately, in addition to the differential reflectivity, ZDR. The technique is tested on simulated time series and on actual radar data. The efficacy of the method is demonstrated on PPI plots of polarimetric variables.

Santos, P., K. Carey, W. MacKenzie, J. Zhang, R. Ferraro, J. Yoe, 2007: Summary of Global Positioning System (GPS) Integrated Precipitable Water (IPW). NWA Elec. J. Op. Met., EJ4, x-x.

Saxion, D. S., R. D. Rhoton, R. L. Ice, D. A. Warde, O. E. Boydstun, S. M. Torres, G. Meymaris, W. D. Zittel, 2007: New science for the WSR-88D: implementing a major mode on the SIGMET RVP8. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, CD-ROM, P2.9.

Scharfenberg, K. A., V. Lakshmanan, S. E. Giangrande, 2005: Development and testing of polarimetric radar applications in WDSS-II. Preprints, 21st International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, USA, American Meteorological Society, CD-ROM, 5.1.

Scharfenberg, K. A., D. J. Miller, T. J. Schuur, P. T. Schlatter, S. E. Giangrande, V. M. Melnikov, D. W. Burgess, D. L. Andra, Jr., M. P. Foster, J. M. Krause, 2005: The Joint Polarization Experiment: Polarimetric radar in forecasting and warning decision-making. Weather and Forecasting, 20, 775-788.

To test the utility and added value of polarimetric radar products in an operational environment, data from the Norman, Oklahoma (KOUN), polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) were delivered to the National Weather Service Weather Forecast Office (WFO) in Norman as part of the Joint Polarization Experiment (JPOLE). KOUN polarimetric base data and algorithms were used at the WFO during the decision-making and forecasting processes for severe convection, flash floods, and winter storms. The delivery included conventional WSR-88D radar products, base polarimetric radar variables, a polarimetric hydrometeor classification algorithm, and experimental polarimetric quantitative precipitation estimation algorithms. The JPOLE data collection, delivery, and operational demonstration are described, with examples of several forecast and warning decision-making successes. Polarimetric data aided WFO forecasters during several periods of heavy rain, numerous large-hail-producing thunderstorms, tornadic and nontornadic supercell thunderstorms, and a major winter storm. Upcoming opportunities and challenges associated with the emergence of polarimetric radar data in the operational community are also described.

Scharfenberg, K. A., K. L. Elmore, E. Forren, V. Melnikov, D. S. Zrnic, 2005: Estimating the impact of a 3-dB sensitivity loss on WSR-88D data. Preprints, 32nd Conf. on Radar Meteorology, Albuquerque, NM, USA, Amer. Meteor. Soc., CD-ROM, P12R.9.

The planned upgrade of the WSR-88D network to include dual-polarimetric capabilities is expected to result in a loss of about 3 dB in sensitivity per channel. In order to better estimate the impact of this sensitivity loss, case study and real-time simulations were performed.

Algorithm products and base data from six archive WSR-88D cases were examined. The proportion of reflectivity samples lost upon desensitization was calculated, and the visibility of important meteorological features and velocity dealiasing errors before and after the desensitization were noted. Changes in the outputs of the echo top, hail detection, and legacy mesocyclone algorithms were observed. Changes to the output of the VAD wind profile (VWP) algorithm were measured. These results are presented.

In addition, a 3 dB higher threshold then usual was applied to KTLX WSR-88D data to simulate the signal loss. This data was then made available to National Weather Service forecasters for a side-by-side evaluation during the spring 2005 convective season. Forecaster feedback was compiled to estimate the impact of the sensitivity loss on situation awareness and decision-making, and these results are discussed.

An overview of proposed mitigation techniques to recover some of the lost velocity information is presented.

Available online at ://http://ams.confex.com/ams/pdfpapers/96931.pdf.

Scharfenberg, K. A., K. L. Elmore, T. J. Schuur, C. Legett, 2007: Analysis of dual-pol WSR-88D base data collected during three significant winter storms. Preprints, 31st Intl. Conf. on Radar Meteor., Cairns, Australia, Amer. Meteor. Soc., CD-ROM, P10.10.

Base data from a dual-pol WSR-88D radar collected during three significant winter storms in Oklahoma are examined. These cases (29-30 November 2006, 12-14 January 2007, and 20 January 2007) were chosen due to concurrent collection of high-resolution surface precipitation type reports near the radar (see paper by Elmore, Scharfenberg, and Legett). Large temporal and spatial variabilities in precipitation types were observed during these events as revealed by the surface reports. This paper will focus on radar data collected during these periods of large variability. Associating the evolution of the radar data and the surface reports is critical for future enhancements to automated hydrometeor classification and to successful forecast decision-making during winter storms.

Available online at ://http://ams.confex.com/ams/pdfpapers/123618.pdf.

Schultz, D. M., K. M. Kanak, J. M. Straka, R. J. Trapp, B. A. Gordon, D. S. Zrnic, G. H. Bryan, A. J. Durant, T. J. Garrett, P. M. Klein, D. K. Lilly, 2006: The mysteries of mammatus clouds: Observations and formation mechanisms. Journal of the Atmospheric Sciences, 63, 2409-2435.

Mammatus clouds are an intriguing enigma of atmospheric fluid dynamics and cloud physics. Most commonly observed on the underside of cumulonimbus anvils, mammatus also occur on the underside of cirrus, cirrocumulus, altocumulus, altostratus, and stratocumulus, as well as in contrails from jet aircraft and pyrocumulus ash clouds from volcanic eruptions. Despite their aesthetic appearance, mammatus have been the sub ject of few quantitative research studies. Observations of mammatus have been obtained largely through serendipitous opportunities with a single observ- ing system (e.g., aircraft penetrations, visual observations, lidar, radar) or tangential observations from field programs with other ob jectives. Theories describing mammatus remain untested as ad- equate measurements for validation do not exist because of the small distance scales and short time scales of mammatus. Modeling studies of mammatus are virtually nonexistent. As a result, relatively little is known about the environment, formation mechanisms, properties, microphysics, and dynamics of mammatus.

This paper presents a review of mammatus clouds that addresses these mysteries. Previous observations of mammatus and proposed formation mechanisms are discussed. These hypothesized mechanisms are anvil subsidence, subcloud evaporation/sublimation, melting, hydrometeor fallout, cloud-base detrainment instability, radiative effects, gravity waves, Kelvin-Helmholtz instability, Rayleigh-Taylor instability, and Rayleigh-Bénard-like convection. Other issues addressed in this paper include whether mammatus are composed of ice or liquid water hydrometeors, why mammatus are smooth, what controls the temporal and spatial scales and organization of individual mammatus lobes, and what are the properties of volcanic ash clouds that produce mammatus? The similarities and differences between mammatus, virga, stalactites, and reticular clouds are also discussed. Finally, because much still remains to be learned, research opportunities are described for using mammatus as a window into the microphysical, turbulent, and dynamical processes occurring on the underside of clouds.

Schultz, D. M., F. Zhang, 2007: Baroclinic development within zonally varying flows. Quarterly Journal of the Royal Meteorological Society, 133, 1101-1112.

Schuur, T. J., A. V. Ryzhkov, D. R. Clabo, 2005: Climatological analysis of DSDs in Oklahoma as revealed by a 2D-video disdrometer and polarimetric WSR-88D radar. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, 15R.4.

Schuur, T. J., A. V. Ryzhkov, P. Zhang, 2005: Polarization characteristics of winter storms in Oklahoma. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P9R.13.

Schuur, T. J., A. V. Ryzhkov, S. Giangrande, 2006: Winter precipitation type classification with a polarimetric WSR-88D radar. Preprints, 12th Conference on Aviation, Range, and Aerospace Meteorology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, P6.1.

Schuur, T. J., S. E. Giangrande, A. V. Ryzhkov, 2008: Polarimetric WSR-88D reflectivity and differential reflectivity attenuation correction for tropical rainfall. Preprints, International Symposium of Weather Radar and Hydrology, Grenoble, France, Europole Congress Center, P1-021.

Seo, D. J., C. R. Kondragunta, K. Howard, S. V. Vasiloff, J. Zhang, 2005: The National Mosaic and Multisensor QPE (NMQ) Project-Status and plans for a community testbed for high-resolution multisensor quantitative precipitation estimation (QPE) over the United States. Preprints, 19th Conference on Hydrology, San Diego, CA, USA, American Meteorological Society, CD-ROM, 1.3.

Seo, D. J., C. R. Kondragunta, K. Howard, S. Vasiloff, J. Zhang, 2005: The national mosaic and multisensor QPE (NMQ) project-status and plans for a community testbed for high-resolution multisensor quantitative precipitation estimation (QPE) over the United States. Preprints, 19th Conf. on Hydrology, San Diego, CA, USA, Amer. Meteor. Soc., CD-ROM, 1.3.

Smith, T. M., V. Lakshmanan, 2006: Utilizing Google Earth as a GIS platform for weather applications. Preprints, 22nd Conference on Interactive Information Processing Systems, Atlanta, GA, USA, AMS, CD-ROM, 8.2.

Available online at ://http://ams.confex.com/ams/Annual2006/techprogram/paper_104847.htm.

Smith, T. M., P. L. Heinselman, D. Priegnitz, 2007: Characteristics of microburst events observed with the National Weather Radar Testbed phased array radar. Preprints, 23rd Conference on Interactive Information Processing Systems, San Antonio, TX, USA, AMS, CD-ROM, 7.8.

Microbursts are small-scale (< 4 km diameter) outflows induced by strong downdrafts in thunderstorms that frequently cause damage to property and are a hazard to aviators. Many severe microbursts originate from storm cells that form in regions of moderate-to-high Convective Available Potential Energy (CAPE), weak environmental shear, and environments that are highly unstable to downdraft formation. These storm cells typically have a life cycle of 20-40 minutes, which makes them very difficult to predict.

Automated algorithms that analyze radar data and make short-term predictions for microburst events, as well as detecting low-altitude divergence signatures associated with their outflows, have been implemented for WSR-88D and TDWR systems. These applications rely on microburst “precursors” that may be observed at the higher altitudes of a storm shortly preceding the outflow at the surface to make short-lead-time forecasts of a microburst event. However, microburst events evolve rapidly, and because these radars typically only sample the upper portions of a storm once every 4 to 6 minutes (depending on scanning strategy), they may not sample key precursor features aloft or the near-surface outflow.

This presentation examines damage-producing severe microburst events that occurred in Central Oklahoma during July 2006 that were observed with the National Weather Radar Testbed (NWRT) Phased Array Radar (PAR). These storms formed within 50 km of the PAR site and were sampled with a temporal resolution of 15 to 30 seconds. We will compare the PAR observations of the storms with the KTLX WSR-88D, OKC TDWR, and multi-radar, multi-sensor information from the Warning Decision Support System – Integrated Information.

Available online at ://http://ams.confex.com/ams/pdfpapers/120074.pdf.

Smith, T. M., V. Lakshmanan, 2008: Real-time and recent historical weather data in Google Earth. Extended Abstracts, 23rd Conference on Interactive Information Processing Systems, New Orleans, LA, USA, AMS, 9B.6.

The National Severe Storms Laboratory (NSSL) utilizes Google Earth as one of several ways to share experimental severe weather products with other researchers and operational meteorologists for evaluation and feedback. A variety of multi-sensor severe weather products are generated by NSSL and shared to Google Earth users via the internet at http://wdssii.nssl.noaa.gov. These products include spatially gridded fields of Vertically Integrated Liquid, Maximum Expected Hail Size, tracks of circulations derived from Doppler velocity data, composite reflectivity, and 30-to-60 minute forecast reflectivity fields, among others. These products, which have a spatial resolution of approximately 1 km by 1 km, are generated every one to five minutes within the Warning Decision Support System – Integrated Information (WDSS-II). The WDSS-II system provides the images in GeoTIFF format which may be imported into most Geographic Information Systems software including virtual globes such as Google Earth.

During the first two years these data have been provided on the internet, they have been used to improve the verification of severe weather events as well as in disaster response and post-event damage assessments. This presentation focuses on the scientific and educational uses of virtual globes to interrogate real-time and archived severe weather products.

Available online at ://http://http://ams.confex.com/ams/88Annual/techprogram/paper_134923.htm.

Storm, B. A., M. D. Parker, D. P. Jorgensen, 2007: A convective line with leading stratiform precipitation from BAMEX. Monthly Weather Review, 135, 1769-1785.

On 31 May 2003, a front-fed convective line with leading stratiform precipitation (FFLS) was observed during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX). The high-resolution BAMEX measurements provided one of the first opportunities to thoroughly observe the characteristics of an FFLS system. The 31 May system had an overturning updraft during its early stages, and produced leading stratiform precipitation. As the system matured, a jump updraft developed and the system began to produce trailing stratiform precipitation. It appears that this transition was facilitated by a local decrease in the low-level line-perpendicular vertical wind shear over time, as well as an increase in the surface cold pool's strength. The BAMEX data further help to address the question of how FFLS systems can be long lived when their inflow passes through the line-leading precipitation: preline soundings suggest a destabilization mechanism resulting from the vertical profile of cooling within the leading stratiform precipitation. This destabilization also helps to explain the 31 May convective system's persistence in an environment with very low CAPE.

Stumpf, G. J., K. D. Hondl, S. B. Smith, M. T. Filiaggi, V. Lakshmanan, 2005: Status on the four-dimensional base radar data analysis tool for AWIPS. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, 8R.5.

Stumpf, G. J., M. T. Filiaggi, M. A. Magsig, K. D. Hondl, S. B. Smith, R. Toomey, C. Kerr, 2006: Status on the integration of the NSSL Four-dimensional Stormcell Investigator (FSI) into AWIPS. Preprints, 23rd Conference on Severe Local Storms, St. Louis, MO, USA, American Meteorological Society, CD-ROM, 8.3.

Teshiba, M., R. D. Palmer, P. B. Chilson, A. V. Ryzhkov, T. J. Schuur, 2005: Dynamics of Mesoscale Convective Systems Observed with a UHF Wind Profiler and a Polarimetric S-band Weather Radar. Extended Abstracts, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, JP3J.27.

Teshiba, M., P. Chilson, A. Ryzhkov, T. Schuur, L. Kanofsky, R. Palmer, 2007: Investigations of microphysical processes of rain formation using wind profilers and S-band polarimetric radar. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, 8A.7.

Teshiba, M., P. B. Chilson, A. V. Ryzhkov, T. J. Schuur, R. D. Palmer, L. Kanofsky, 2007: Snow characteristics observed using two UHF wind profilers and a polarimetric S-band weather radar. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, American Meteorological Society, 8A.7.

Thompson, W., S. Burk, J. Lewis, 2005: Fog and low clouds in a coastally trapped disturbance. J. Geophysical Research, 110, .

Torres, S., I. Ivic, 2005: Demonstration of range oversampling techniques on the WSR-88D. Preprints, 32nd International Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, 4R.5.

Torres, S., 2005: Range and velocity ambiguity mitigation on the WSR-88D: Performance of the SZ-2 phase coding algorithm. Preprints, 21st International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, USA, American Meteorological Society, 19.2.

Torres, S., M. Sachidananda, D. Zrnic, 2005: Signal Design and Processing Techniques for WSR-88D Ambiguity Resolution. Phase Coding and Staggered PRT 9, 112 pp. [Available from Sebastian Torres, 1313 Halley Cir, Norman, OK, USA, 73069.]

Available online at ://http://cimms.ou.edu/rvamb/Documents/Report_9.pdf.

Torres, S., 2006: Range and velocity ambiguity mitigation on the WSR-88D: Performance of the staggered PRT algorithm. Extended Abstracts, 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, AMS, CD-ROM, 9.9.

In the WSR-88D, the range and Doppler velocity ambiguity problems are coupled such that trying to alleviate one of them worsens the other. Accordingly, special techniques are necessary to resolve both ambiguities to the levels required for the efficient observation of severe weather. The Radar Operations Center of the National Weather Service has sponsored the National Severe Storms Laboratory (NSSL) and the National Center for Atmospheric Research (NCAR) to develop methods for mitigating the effects of velocity and range ambiguities on the WSR-88D. NSSL has recently recommended an algorithm for the second stage of deployment of range and velocity ambiguity mitigation techniques on the Open Radar Data Acquisition (ORDA) subsystem. The algorithm is based on alternating pulse repetition times (PRT) and can replace the Batch cuts at intermediate elevation angles of the antenna beam. This paper shows the performance of the staggered PRT algorithm on weather data collected with NSSL's KOUN radar in Norman, OK. Comparisons with existing “legacy” algorithms demonstrate the ability of the staggered PRT algorithm to effectively mitigate range and velocity ambiguities in future enhancements of the NEXRAD radar network.

Available online at ://http://cimms.ou.edu/rvamb/Documents/AMS_IIPS_2006.pdf.

Torres, S. M., W. J. Gonzalez-Espada, 2006: Calculating 'g' from acoustic Doppler data. The Physics Teacher, 44, 536-539.

Torres, S. M., C. D. Curtis, 2007: Initial implementation of super-resolution data on the NEXRAD network. Preprints, 23rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, AMS, CD-ROM, 5B.10.

Torres, S. M., C. D. Curtis, 2006: Design considerations for improved tornado detection using super-resolution data on the NEXRAD network. Preprints, Third European Conf. on Radar Meteorology and Hydrology (ERAD), Barcelona, Spain, Copernicus, 2.8.

Torres, S. M., D. S. Zrnic, 2006: Signal Design and Processing Techniques for WSR-88D Ambiguity Resolution. Evolution of the SZ-2 Algorithm 10, 74 pp.

Available online at ://http://cimms.ou.edu/rvamb/Documents/Report_10.pdf.

Torres, S. M., C. D. Curtis, D. S. Zrnic, M. Jain, 2007: Analysis of the new NEXRAD spectrum width estimator. Proc. 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P7.8.

Recently, the US network of weather surveillance radars (NEXRAD) was upgraded with new receiver, signal processor, and control subsystems. Before this upgrade, the spectrum width was estimated using the standard pulse-pair technique. The new signal processor implements a similar spectrum width estimator, but relies on a DFT-based estimator to compute the first few lags of the time-series autocorrelation function. Initial evaluation of the upgraded system demonstrated that, if combined with a tapered data window, the DFT-based estimator produces results that are acceptable and very close to the classical pulse-pair estimator. However, this paper demonstrates that, in general, the new and legacy autocorrelation estimators are not equivalent, resulting in inconsistent spectrum width estimates. Theoretical, simulation, and data analyses show that the new spectrum width estimator on non-windowed data is positively biased, especially for narrow spectrum widths. Given that biased estimates would negatively impact the performance of algorithms that rely on the spectrum width (e.g., the radar echo classifier, or the new turbulence detection algorithm), we propose changes to the new spectrum width estimator to make it unbiased, mathematically equivalent to the pulse-pair implementation, and naturally able to handle data window effects.

Available online at ://http://ams.confex.com/ams/pdfpapers/123048.pdf.

Torres, S. M., 2007: Range oversampling techniques for polarimetric radars with dual transmitters. Proc. AMS, Cairns, Australia, AMS, CD-ROM, 7.5.

Range oversampling followed by a decorrelation transformation is a novel method for increasing the number of independent samples from which to estimate the Doppler spectrum, its moments, as well as several polarimetric variables on pulsed weather radars. Range oversampling techniques rely on the precise knowledge of the range correlation of oversampled signals, which is a function of the transmitter pulse envelope, the receiver filter impulse response, and the reflectivity field illuminated by the radar. Theoretical and simulation studies demonstrating the advantages of these techniques have been successfully verified on weather data collected with a single-transmitter dual-polarization radar. In contrast, recent experimental results on a dual-transmitter system have been rather negative; if the amplitude and/or phase mismatch between transmission pulses is disregarded in the formulation of the decorrelation transformation, processing of range oversampled dual-polarization signals with the standard whitening transformation can produce biased polarimetric variable estimates. This paper demonstrates that, by properly accounting for the amplitude and/or phase differences in the transmission channels, it is always possible to obtain unbiased polarimetric variable estimates. However, the accuracy of these estimators degrades as the degree of mismatch between the horizontally and the vertically polarized transmitted pulses increases.

Available online at ://http://ams.confex.com/ams/pdfpapers/123045.pdf.

Torres, S. M., S. Bachmann, D. Zrnic, 2007: Signal Design and Processing Techniques for WSR-88D Ambiguity Resolution. Staggered PRT and Updates to the SZ-2 Algorithm 11, 146 pp.

Torres, S. M., C. Curtis, I. Ivic, S. Bachmann, E. Forren, J. Thompson, D. Priegnitz, R. Adams, A. Zahrai, 2008: Signal Processing Upgrades for the National Weather Radar Testbed. Preprints, 24rd International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, New Orleans, LA, USA, AMS, CD-ROM, 9A.2.

The National Weather Radar Testbed (NWRT) located in Norman, Oklahoma was established to demonstrate the potential to simultaneously perform aircraft tracking, wind profiling, and weather surveillance as a multi-mission phased-array radar (MPAR). Since its inception in September of 2003, the system has undergone an extensive engineering evaluation and numerous hardware and software upgrades. However, in spite of significant engineering work, the real-time signal processing functionality currently implemented in the PAR is limited. Even with these limitations, several research experiments have successfully demonstrated many of the unique advantages of using phase-array technology in the context of weather observation. A modern and improved multi-processor/multi-computer signal processing environment will allow the implementation of new and advanced real-time signal processing techniques. These include schemes to effectively remove clutter contamination from meteorological signals, methods to mitigate range and velocity ambiguities, and techniques that allow for faster data collection. This paper presents initial results and describes the roadmap of planned signal processing upgrades for the NWRT that will provide researchers and users with an optimum platform for demonstrating and evaluating the MPAR concept.

Vasiloff, S. V., D. J. Seo, K. H. Howard, J. Zhang, D. H. Kitzmiller, C. Coauthors, 2007: Improving QPE and Very Short Term QPF. Bulletin of the American Meteorological Society, 88, 1899-1911.

Vasiloff, S. V., D. J. Seo, K. W. Howard, J. Zhang, D. H. Kitzmiller, M. G. Mullusky, W. F. Krajewski, E. A. Brandes, R. M. Rabin, D. S. Berkowitz, H. E. Brooks, J. A. McGinley, R. J. Kuligowski, B. G. Brown, 2007: Improving QPE and Very Short Term QPF: An Initiative for a Community-Wide Integrated Approach. Bulletin of the American Meteorological Society, 88, 1899-1911.

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

Wang, B., J. Zhang, W. Xia, K. Howard, X. Xu, 2008: Analysis of radar and gauge rainfall during the warm season in Oklahoma. Preprints, The 22nd Conf. on Hydrology, New Orleans, LA, USA, Amer. Meteor. Soc., CD-ROM, P2.1.

Witt, A., R. A. Brown, V. Lakshmanan, 2005: Real-time calculation of horizontal winds using multiple Doppler radars: A new WDSS-II module. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, Amer. Meteor. Soc., CD-ROM, P8R.7.

Xu, Q., K. Nai, L. Wei, P. Zhang, L. Wang, H. Lu, Qingyun Zhao, 2005: Progress in doppler radar data assimilation. 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, JP1J7.

Xu, Q., K. Nai, L. Wei, H. Lu, P. Zhang, S. Liu, D. Parrish, 2007: Estimating radar wind observation error and NCEP WRF background wind error covariances from radar radial-velocity innovations. Extended Abstracts, 18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., 1B.3.

Available online at ://http://ams.confex.com/ams/pdfpapers/123419.pdf.

Yeary, M. B., B. McGuire, D. Forsyth, W. Benner, G. Torok, 2007: Target tracking at the National Weather Radar Testbed: a progress report on detecting and tracking aircraft.. Preprints, The 23rd Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Antonio, TX, USA, American Meteorology Society, CD-ROM, 8A.1.

Yeary, M., R. Palmer, M. Xue, T. Y. Yu, G. Zhang, A. Zahrai, J. Crain, Y. Zhang, R. Doviak, Q. Xu, P. Chilson, 2008: Introduction to multi-channel receiver development for the realization of multi-mission capabilities at the National Weather Radar Testbed. Extended Abstracts, 24rd Conference on Interactive Information Processing Systems (IIPS), New Orleans, LA, USA, AMS, 9A.3.

You, T., Y. Wang, A. Shapiro, M. B. Yeary, D. S. Zrnic, 2007: Characterization of Tornado Spectral Signatures Using Higher-Order Statistics. Journal of Atmospheric and Oceanic Technology, 24, 1997-2013.

Yu, T. Y., A. B. Chalamalasetti, R. J. Doviak, D. S. Zrnic, 2006: Resolution Enhancement Technique using Range Oversampling. Journal of Atmospheric and Oceanic Technology, 23, 228-240.

Yu, T. Y., G. Zhang, A. Chalamalasetti, R. J. Doviak, D. S. Zrnic, 2005: Improve Radar Resolution using Range Oversampling. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, 4R.4.

YU, T. Y., M. B. Orescanin, C. D. Curtis, D. S. Zrnic, D. E. Forsyth, 2007: Beam Multiplexing Using the Phased-Array Weather Radar.. Journal of Atmospheric and Oceanic Technology, 24, .

Yu, T. Y., M. B. Orescanin, C. D. Curtis, D. S. Zrnic, D. E. Forsyth, 2007: Optimization of weather update time and data quality using phased-array radar. Preprints, The 23rd Conference on Interactive Information Processing System (IIPS) for Meteorology, Oceanograph, and Hydrology, San Antonio, TX, USA, American Meteorological Society, CD-ROM, 7.6.

Yu, T. Y., Y. Wang, A. Shapiro, M. B. Yeary, D. S. Zrnic, R. J. Doviak, 2007: Characterization of Tornado Spectral Signatures using Higher-Order Spectra. Journal of Atmospheric and Oceanic Technology, 24, .

Zhang, P., A. Ryzhkov, D. Zrnic, 2006: Polarimetric prototype of the WSR-88D radar observations of insects and birds. Preprints, 12th Conference on Aviation, Range, and Aerospace Meteorology, Atlanta, GA, USA, American Meteorological Society, CD-ROM, P6.4.

Zhang, P., S. Liu, Q. Xu, Lulin Song, 2005: Storm targeted radar wind retrieval system. 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, P8R1.

Zhang, G., T-Y Yu, R. J. Doviak, 2005: Angular and range interferometry to refine weather radar resolution. Radio Science, 39, .

Zhang, J., K. Howard, J. J. Gourley, 2005: Constructing three-dimensional multiple radar reflectivity mosaics: examples of convective storms and stratiform rain echoes. Journal of Atmospheric and Oceanic Technology, 22, 30-42.

Zhang, P., S. Liu, Q. Xu, 2005: Quality control of Doppler velocities contaminated by migrating birds. Part I: Feature extraction and quality control parameters. Journal of Atmospheric and Oceanic Technology, 22, 1105-1113.

Zhang, S. W., C. J. Qiu, Q. Xu, 2005: Reply. Journal of Applied Meteorology, 44, 551-552.

Zhang, P., A. Ryzhkov, D. Zrnic, 2005: Observations of insects and birds with a polarimetric prototype of the WSR-88D radar. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, American Meteorological Society, CD-ROM, 9R.6.

Zhang, J., S. Wang, 2006: An Automated 2D Multipass Doppler Radar Volocity Dealiasing Scheme. Journal of Atmospheric and Oceanic Technology, 23, 1239-1248.

Zhang, G., R. J. Doviak, 2007: Spaced-Antenna Interferometry to Measure Crossbeam Wind, Shear, and Turbulence: Theory and Formulation.. Journal of Atmospheric and Oceanic Technology, 24, 791-805.

The theory of measuring crossbeam wind, shear, and turbulence within the radar's resolution volume V6 is described. Weather radar interferometry is formulated for such measurements using phased-array weather-radar. The formulation for a Spaced Antenna Interferometer (SAI) includes shear of the mean wind, allows turbulence to be anisotropic, and allows receiving beams to have elliptical cross sections. Auto- and cross-correlation functions are derived based on wave scattering by randomly distributed particles. Antenna separation, mean wind, shear, and turbulence all contribute to signal de-correlation. Crossbeam wind cannot be separated from shear and thus crossbeam wind measurements are biased by shear. It is shown that SAI measures an apparent crossbeam wind (i.e., the angular shear of the radial wind component). Whereas angular shear and turbulence within V6 cannot be separated using monostatic Doppler techniques, they can be separated using the SAI.

Zhang, G., R. J. Doviak, R. Palmer, T. Y. Yu, P. Chilson, 2005: Bistatic Interferometry to Measure Clear Air Wind. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, USA, AMS, CD-ROM, P2R.11.

Zhang, G., R. J. Doviak, X. Chen, 2007: Space Antenna Interferometry to Detect Discrete Objects and Sub-Volume Inhomogeneities of Reflectivity. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, 8B1.

Zhang, P., A. Ryzhkov, D. Zrnic, 2007: Kelvin-Helmholtz Waves Observed by a Polarimetric Prototype of the WSR-88D Radar. Extended Abstracts, 33rd International Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P10.4. [Available from Pengfei Zhang, National Weather Center, 120 David L. Boren Blvd. Suite 4502, Norman, OK, USA, 73072.]

At 15:40UTC on 2 May 2005, wave-like bright band is observed at 0.5o elevation angle by KOUN radar. The band highlighted by stronger reflectivity (~30dBZ), high Zdr (~2dB) and low hv (~0.9) moves eastwardly and last about 1 hour in KOUN radar scope. Doppler velocity observation shows strong wind shear in vertical direction at about 2 km height. Rawinsonde of OUN station at 12 UTC observes wind shift from NE (40o) at 1.2 km height to SW (220o) at 2.1 km height. Sounding also shows atmosphere is stable in the whole troposphere. 0oC temperatures layer locates at 2.1 km. Temperature is higher than 0oC underneath it. It means bright band is right embedded in the wind shear layer. Thus, we believe that bright band is altered by Kelvin-Helmholtz wave.

Zhang, G., Q. Cao, M. Xue, P. Chilson, M. Morris, R. Palmer, J. Brotzke, T. Schuur, E. Brandes, K. Ikeda, A. Ryzhkov, D. Zrnic, E. Jessup, 2008: A field experiment to study rain microphysics using video disdrometers and polarimetric S and X-band radars. Preprints, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, New Orleans, LA, USA, American Meteorological Society, P2.23.

Zhang, J., K. Howard, X. Xu, 2008: A warm season radar QPE algorithm using adaptive Z-R relationships. Proc. World Environmental and Water Resources Congress 2008, Honolulu, HI, USA, Amer. Soc. Civil Engineers, CD-ROM, 420.pdf.

Zhang, J., C. Langston, K. Howard, 2008: Three-dimensional radar mosaic integrating WSR-88Ds and Canadian radar network. Preprints, The 13th Conf. on Aviation, Range, and Aerospace Meteorology, New Orleans, LA, USA, Amer. Meteor. Soc., CD-ROM, P4.4.

Zhang, J., C. Langston, K. Howard, 2007: Brightband identification from vertical profile of reflectivity. Preprints, The 33rd International Conf. on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., P8A.13.

Zhang, J., C. Langston, K. Howard, 2006: Vertical profiles of reflectivity for different precipitation regimes. Proc. The 4th European Conference on Radar in Meteorology and Hydrology, Barcelona, Spain, Servei Meteorologic de Catalunya, 225-228.

Zhang, J., K. Howard, S. Wang, 2006: Single radar Cartesian grid and adaptive radar mosaic system. Preprints, The 12th Conference on Aviation, Range, and Aerospace Meteorolog, Atlanta, GA, USA, Amer. Meteor. Soc., 1.8.

Zhang, J., C. Langston, K. Howard, B. Clarke, 2006: Gap-filling in 3D radar mosaic analysis using vertical profile of reflectivity. Preprints, The 12th Conference on Aviation, Range, and Aerospace Meteorology, Atlanta, GA, USA, Amer. Meteor. Soc., CD-ROM, P1.9.

Zrnic, D., A. Zahrai, S. Torres, C. Curtis, I. Ivic, 2005: Development of advanced techniques using the NOAA's WSR-88D research radar. Preprints, 21st International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, USA, American Meteorological Society, 5.9.

Zrnic, D. S., V. M. Melnikov, J. K. Carter, 2005: Calibrating Differential Reflectivity on the WSR-88D. Radar report 1, NOAA/NSSL, 34 pp. [Available from NSSL's Library, 1313 Haley Circle, Norman, OK, USA, 73069.]

A procedure on how to calibrate differential reflectivity on the WSR-88D is described. It has been tested on the NOAA's modified WSR-88D research and development polarimetric radar and is directly applicable to radars which simultaneously transmit and receive waves having horizontal and vertical polarizations.

Available online at ://http://www.cimms.ou.edu/~schuur/jpole/WSR-88D_reports.html.

Zrnic, D. S., V. M. Melnikov, J. K. Carter, 2006: Calibrating differential reflectivity on the WSR-88D. Journal of Atmospheric and Oceanic Technology, 23, 944-951.

A calibration procedure of differential reflectivity on the Weather Surveillance Radar-1988 Doppler (WSR-88D) is described. It has been tested on NOAA's modified WSR-88D research and development polarimetric radar and is directly applicable to radars that simultaneously transmit and receive waves having horizontal and vertical polarization.

Zrnic, D. S., V. M. Melnikov, A. V. Ryzhkov, 2006: Correlation coefficients between horizontally and vertically polarized returns from ground clutter. Journal of Atmospheric and Oceanic Technology, 23, 381-394.

Characteristics of the magnitude and phase of correlation coefficients between horizontally and vertically polarized returns from ground clutter echoes are quantified by analyzing histograms obtained with an 11-cm wavelength weather surveillance radar in Norman, Oklahoma. The radar receives simultaneously horizontal and vertical (SHV) electric fields and can transmit either horizontal fields or both vertical and horizontal fields. The differences between correlations obtained in this SHV mode and correlations measured in alternate H, V mode are reviewed; a histogram of differential phase obtained in Florida using alternate H, V mode is also presented. Data indicate that the backscatter differential phase of clutter has a broad histogram that completely overlaps the narrow histogram of precipitation echoes. This is important as it implies that a potent discriminator for separating clutter from meteorological echoes is the texture of the differential phase. Values of the copolar cross-correlation coefficient from clutter overlap completely those from precipitation, and effective discrimination is possible only if averages in range are taken. It is demonstrated that the total differential phase (system and backscatter) depends on the polarimetric measurement technique and the type of scatterers. In special circumstances, such as calibrating or monitoring the radar, clutter signal can be beneficial. Specifically, system differential phase can be estimated from histograms of ground clutter, receiver differential phase can be estimated from precipitation returns, and from these two, the differential phase of transmitted waves is easily computed.

Zrnic, D. S., V. M. Melnikov, 2007: Ground clutter recognition using polarimetric spectral parameters. Preprints, 33rd Conference on Radar Meteorology, Cairns, Australia, AMS, CD-ROM, P11B13.

Zrnic, D. S., J. F. Kimpel, D. F. Forsyth, A. Shapiro, G. Crain, R. Ferek, J. Heimmer, W. Benner, T. J. McNellis, 2007: Agile beam phased array radar for weather observations. Bulletin of the American Meteorological Society, 88, 1753-1766.