An Automated Python Algorithm to Quantify ZDR Arc and KDP-ZDR Separation Signatures in Supercells

2020 ◽  
Author(s):  
Matthew B. Wilson ◽  
Matthew S. Van Den Broeke
Keyword(s):  
Time Series ◽  
Recent Work ◽  
Radar Data ◽  
Dual Polarization ◽  
Low Level ◽  
Supercell Storms ◽  
Size Sorting ◽  
Supercell Thunderstorms ◽  
Differential Reflectivity

AbstractSupercell thunderstorms often have pronounced signatures of hydrometeor size sorting within their forward flank regions, including an arc-shaped region of high differential reflectivity (ZDR) along the inflow edge of the forward flank known as the ZDR arc and a clear horizontal separation between this area of high ZDP values and and an area of enhanced KDP values deeper into the storm core. Recent work has indicated that ZDR arc and KDP-ZDR separation signatures in supercell storms may be related to environmental storm-relative helicity and low-level shear. Thus, characteristics of these signatures may be helpful to indicate whether a given storm is likely to produce a tornado. Although ZDR arc and KDP-ZDR separation signatures are typically easy to qualitatively identify in dual-polarization radar fields, quantifying their characteristics can be time-consuming and makes research into these signatures and their potential operational applications challenging. To address this problem, this paper introduces an automated Python algorithm to objectively identify and track these signatures in Weather Surveillance Radar-1988 Doppler (WSR-88D) radar data and quantify their characteristics. This paper will discuss the development of the algorithm, demonstrate its performance through comparisons with manually-generated time series of ZDR arc and KDP-ZDR separation signature characteristics, and briefly explore potential uses of this algorithm in research and operations.

scholarly journals Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 581
Author(s):  
Matthew Van Den Broeke
Keyword(s):  
Polarimetric Radar ◽  
Low Level ◽  
Supercell Storms ◽  
Supercell Thunderstorms ◽  
Near Term ◽  
Tornadic Storms ◽  
Differential Reflectivity

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

Dual-Polarization Radar Data Analysis of the Impact of Ground-Based Glaciogenic Seeding on Winter Orographic Clouds. Part I: Mostly Stratiform Clouds

2015 ◽  
Vol 54 (9) ◽  
pp. 1944-1969 ◽  
Author(s):  
Xiaoqin Jing ◽  
Bart Geerts ◽  
Katja Friedrich ◽  
Binod Pokharel
Keyword(s):  
Radar Data ◽  
Control Area ◽  
Target Area ◽  
Dual Polarization ◽  
Stratiform Clouds ◽  
Orographic Clouds ◽  
Close Range ◽  
Glaciogenic Seeding ◽  
Differential Reflectivity ◽  
The Impact

AbstractThe impact of ground-based glaciogenic seeding on wintertime orographic, mostly stratiform clouds is analyzed by means of data from an X-band dual-polarization radar, the Doppler-on-Wheels (DOW) radar, positioned on a mountain pass. This study focuses on six intensive observation periods (IOPs) during the 2012 AgI Seeding Cloud Impact Investigation (ASCII) project in Wyoming. In all six storms, the bulk upstream Froude number below mountaintop exceeded 1 (suggesting unblocked flow), the clouds were relatively shallow (with bases below freezing), some liquid water was present, and orographic flow conditions were mostly steady. To examine the silver iodide (AgI) seeding effect, three study areas are defined (a control area, a target area upwind of the crest, and a lee target area), and comparisons are made between measurements from a treated period and those from an untreated period. Changes in reflectivity and differential reflectivity observed by the DOW at low levels during seeding are consistent with enhanced snow growth, by vapor diffusion and/or aggregation, for a case study and for the composite analysis of all six IOPs, especially at close range upwind of the mountain crest. These low-level changes may have been affected by natural changes aloft, however, as evident from differences in the evolution of the echo-top height in the control and target areas. Even though precipitation in the target region is strongly correlated with that in the control region, the authors cannot definitively attribute the change to seeding because there is a lack of knowledge about natural variability, nor can the outcome be generalized, because the sample size is small.

scholarly journals Observations of Ash, Ice, and Lightning within Pyrocumulus Clouds Using Polarimetric NEXRAD Radars and the National Lightning Detection Network

2017 ◽  
Vol 145 (12) ◽  
pp. 4899-4910 ◽  
Author(s):  
Kendell T. LaRoche ◽  
Timothy J. Lang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Case Studies ◽  
Correlation Coefficient ◽  
Convective Cloud ◽  
Past Research ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Lightning Detection ◽  
Differential Reflectivity

A pyrocumulus is a convective cloud that can develop over a wildfire. Under certain conditions, pyrocumulus clouds become vertically developed enough to produce lightning. NEXRAD dual-polarization weather radar and upgraded National Lightning Detection Network (NLDN) data were used to analyze 10 case studies of ash plumes and pyrocumulus clouds from 2013 that either did or did not produce detected lightning. Past research has shown that pyrocumulus cases are most likely to produce lightning when there is a decrease in differential reflectivity (toward 0 dB) and an increase in the correlation coefficient (to >0.8), as measured by polarimetric radar, due to the transition from pure smoke/ash to frozen hydrometeors. All pyrocumulus cases that produced lightning in this study displayed the polarimetric characteristics of rimed ice within their respective clouds. Time series analysis of radar-inferred ash and rimed ice volumes within ash plumes and pyrocumulus clouds showed that NLDN-detected lightning occurred only after the cloud contained significant amounts of precipitation-sized rimed ice. The results suggest that the recently dual-pol-enabled NEXRADs and the more sensitive NLDN network can be used to explore ash plume and pyrocumulus microphysical structure and lightning production.

scholarly journals Differential Reflectivity Calibration and Antenna Temperature

2017 ◽  
Vol 34 (9) ◽  
pp. 1885-1906 ◽  
Author(s):  
J. C. Hubbert
Keyword(s):  
Thermal Expansion ◽  
Doppler Radar ◽  
Radar Data ◽  
The Sun ◽  
Dual Polarization ◽  
Calibration Technique ◽  
Atmospheric Research ◽  
Using Data ◽  
Power Measurements ◽  
Differential Reflectivity

AbstractTemporal differential reflectivity bias variations are investigated using the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Using data from the Multi-Angle Snowflake Camera-Ready (MASCRAD) Experiment, S-Pol measurements over extended periods reveal a significant correlation between the ambient temperature at the radar site and the bias. Using radar scans of the sun and the ratio of cross-polar powers, the components of the radar that cause the variation of the bias are identified. It is postulated that the thermal expansion of the antenna is likely the primary cause of the observed bias variation. The cross-polar power (CP) calibration technique, which is based on the solar and cross-polar power measurements, is applied to data from the Plains Elevated Convection at Night (PECAN) field project. The bias from the CP technique is compared to vertical-pointing bias measurements, and the uncertainty of the bias estimates is given. An algorithm is derived to correct the radar data for the time- and temperature-varying bias. Bragg scatter measurements are used to corroborate the CP technique bias measurements.

scholarly journals Quantifying the Separation of Enhanced ZDR and KDP Regions in Nonsupercell Tornadic Storms

2018 ◽  
Vol 33 (5) ◽  
pp. 1143-1157 ◽  
Author(s):  
Scott D. Loeffler ◽  
Matthew R. Kumjian
Keyword(s):  
United States ◽  
Southeastern United States ◽  
Separation Distance ◽  
Dual Polarization ◽  
Cool Season ◽  
The Public ◽  
Size Sorting ◽  
The Right ◽  
Tornadic Storms ◽  
Differential Reflectivity

Abstract Tornadoes associated with nonsupercell storms present unique challenges for forecasters. These tornadic storms, although often not as violent or deadly as supercells, occur disproportionately during the overnight hours and the cool season—times when the public is more vulnerable. Additionally, there is significantly lower warning skill for these nonsupercell tornadoes compared to supercell tornadoes. This study utilizes dual-polarization Weather Surveillance Radar-1988 Doppler (WSR-88D) data to analyze nonsupercell tornadic storms over a three-and-a-half-year period focused on the mid-Atlantic and southeastern United States. A signature found in a large number of cases is the separation of low-level specific differential phase KDP and differential reflectivity ZDR enhancement regions, thought to arise owing to size sorting. This study employs a new method to define the “separation vector,” which comprises the distance separating the enhancement regions and the direction from the KDP enhancement region to the ZDR enhancement region, measured relative to storm motion. While there is some variation between cases, preliminary results show that the distribution of separation distance between the enhancement regions is centered around 3–4 km and tends to maximize around the time of tornadogenesis. A preferred quadrant for separation direction is found between parallel and 90° to the right of storm motion and is most orthogonal near the time of tornadogenesis. Further, it is shown that, for a given separation distance, separation direction increasing from 0° toward 90° is associated with increased storm-relative helicity.

scholarly journals Relationships between Extreme Rain Rates and Convective Intensities from the Perspectives of TRMM and WSR-88D Radars

2018 ◽  
Vol 57 (6) ◽  
pp. 1353-1369 ◽  
Author(s):  
Alexandria Gingrey ◽  
Adam Varble ◽  
Edward Zipser
Keyword(s):  
Radar Data ◽  
Horizontal Resolution ◽  
Near Surface ◽  
Differential Phase ◽  
Low Level ◽  
Freezing Level ◽  
Trmm Pr ◽  
Extreme Rain ◽  
Rain Rates ◽  
Differential Reflectivity

AbstractTRMM PR 2A25, version 7 (V7), retrievals of reflectivity Z and rainfall rate R are compared with WSR-88D dual-polarimetric S-band radar data for 28 radars over the southeastern United States after matching their horizontal resolution and sampling. TRMM Ku-band measurements are converted to S-band approximations to more directly compare reflectivity estimates. Rain rates are approximated from WSR-88D data using the CSU–hydrometeor identification rainfall optimization (HIDRO) algorithm. Tropics-wide TRMM retrievals confirm previous findings of a low overlap fraction between extreme convective intensity, as approximated by the maximum 40-dBZ height, and extreme near-surface rain rates. WSR-88D data also confirm this low overlap but show that it is likely higher than TRMM PR retrievals indicate. For maximum 40-dBZ echo heights that extend above the freezing level, mean WSR-88D reflectivities at low levels are approximately 2 dB higher than TRMM PR reflectivities. Higher WSR-88D-retrieved rain rates for a given low-level reflectivity combine with these higher low-level reflectivities for a given maximum 40-dBZ height to produce rain rates that are approximately double those retrieved by the TRMM PR for maximum 40-dBZ heights that extend above the freezing level. TRMM PR path-integrated attenuation, and WSR-88D specific differential phase, differential reflectivity, and hail fraction indicate that the TRMM PR 2A25 V7 algorithm is possibly misidentifying low–midlevel hail and/or graupel as greater attenuating liquid, or vice versa. This misidentification, coupled with underestimation of path-integrated attenuation caused by nonuniform beamfilling and higher rain rates produced by specific differential phase (KDP)–R than Z–R relationships, results in low-biased 2A25 V7 rain rates in intense convection.

scholarly journals Impact of the Dual-Polarization Doppler Radar Data on Two Convective Storms with a Warm-Rain Radar Forward Operator

2012 ◽  
Vol 140 (7) ◽  
pp. 2147-2167 ◽  
Author(s):  
Xuanli Li ◽  
John R. Mecikalski
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Radar Data ◽  
Dual Polarization ◽  
Convective Storms ◽  
Warm Rain ◽  
Mesoscale Convective ◽  
Differential Reflectivity ◽  
The Impact

Abstract The dual-polarization (dual pol) Doppler radar can transmit/receive both horizontally and vertically polarized power returns. The dual-pol radar measurements have been shown to provide a more accurate precipitation estimate compared to traditional radars. In this study, the horizontal reflectivity ZH, differential reflectivity ZDR, specific differential phase KDP, and radial velocity VR collected by the C-band Advanced Radar for Meteorological and Operational Research (ARMOR) are assimilated for two convective storms. A warm-rain scheme is constructed to assimilate ZH, ZDR, and KDP data using the three-dimensional variational data assimilation (3DVAR) system with the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The main goals of this study are first to demonstrate and compare the impact of various dual-pol variables in initialization of real case convective storms and second to test how the dual-pol fields may be better used with a 3DVAR system. The results show that the ZH, ZDR, KDP, and VR data substantially improve the initial condition for two mesoscale convective storms. Significant positive impacts on short-term forecast are obtained for both storms. Additionally, KDP and ZDR data assimilation is shown to be superior to ZH and ZDR and ZH-only data assimilation when the warm-rain microphysics is adopted. With the ongoing upgrade of the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network to include dual-pol capabilities (started in early 2011), the findings from this study can be a helpful reference for utilizing the dual-pol radar data in numerical simulations of severe weather and related quantitative precipitation forecasts.

Storm-Relative Helicity Revealed from Polarimetric Radar Measurements

2009 ◽  
Vol 66 (3) ◽  
pp. 667-685 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Alexander V. Ryzhkov
Keyword(s):  
Strong Positive Correlation ◽  
Convective Storms ◽  
Low Level ◽  
Initial Drop ◽  
Size Sorting ◽  
Radar Measurements ◽  
Microphysical Processes ◽  
Differential Sedimentation ◽  
The Right ◽  
Differential Reflectivity

Abstract The dual-polarization radar variables are especially sensitive to the microphysical processes of melting and size sorting of precipitation particles. In deep convective storms, polarimetric measurements of such processes can provide information about the airflow in and around the storm that may be used to elucidate storm behavior and evolution. Size sorting mechanisms include differential sedimentation, vertical transport, strong rotation, and wind shear. In particular, winds that veer with increasing height typical of supercell environments cause size sorting that is manifested as an enhancement of differential reflectivity (ZDR) along the right or inflow edge of the forward-flank downdraft precipitation echo, which has been called the ZDR arc signature. In some cases, this shear profile can be augmented by the storm inflow. It is argued that the magnitude of this enhancement is related to the low-level storm-relative environmental helicity (SRH) in the storm inflow. To test this hypothesis, a simple numerical model is constructed that calculates trajectories for raindrops based on their individual sizes, which allows size sorting to occur. The modeling results indicate a strong positive correlation between the maximum ZDR in the arc signature and the low-level SRH, regardless of the initial drop size distribution aloft. Additional observational evidence in support of the conceptual model is presented. Potential changes in the ZDR arc signature as the supercell evolves and the low-level mesocyclone occludes are described.

scholarly journals Rapid-Scan Super-Resolution Observations of a Cyclic Supercell with a Dual-Polarization WSR-88D

2010 ◽  
Vol 138 (10) ◽  
pp. 3762-3786 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Alexander V. Ryzhkov ◽  
Valery M. Melnikov ◽  
Terry J. Schuur
Keyword(s):  
Phased Array ◽  
Super Resolution ◽  
Radar Data ◽  
Small Time ◽  
Limited Area ◽  
Dual Polarization ◽  
Scanning Strategy ◽  
Low Level ◽  
Rapid Scan ◽  
Phased Array Radar

Abstract In recent years, there has been widespread interest in collecting and analyzing rapid updates of radar data in severe convective storms. To this end, conventional single-polarization rapid-scan radars and phased array radar systems have been employed in numerous studies. However, rapid updates of dual-polarization radar data in storms are not widely available. For this study, a rapid scanning strategy is developed for the polarimetric prototype research Weather Surveillance Radar-1988 Doppler (WSR-88D) radar in Norman, Oklahoma (KOUN), which emulates the future capabilities of a polarimetric multifunction phased array radar (MPAR). With this strategy, data are collected over an 80° sector with 0.5° azimuthal spacing and 250-m radial resolution (“super resolution”), with 12 elevation angles. Thus, full volume scans over a limited area are collected every 71–73 s. The scanning strategy was employed on a cyclic nontornadic supercell storm in western Oklahoma on 1 June 2008. The evolution of the polarimetric signatures in the supercell is analyzed. The repetitive pattern of evolution of these polarimetric features is found to be directly tied to the cyclic occlusion process of the low-level mesocyclone. The cycle for each of the polarimetric signatures is presented and described in detail, complete with a microphysical interpretation. In doing so, for the first time the bulk microphysical properties of the storm on small time scales (inferred from polarimetric data) are analyzed. The documented evolution of the polarimetric signatures could be used operationally to aid in the detection and determination of various stages of the low-level mesocyclone occlusion.

scholarly journals Development of an Operational Convective Nowcasting Algorithm Using Raindrop Size Sorting Information from Polarimetric Radar Data

2018 ◽  
Vol 33 (5) ◽  
pp. 1477-1495 ◽  
Author(s):  
Darrel M. Kingfield ◽  
Joseph C. Picca
Keyword(s):  
Model Simulation ◽  
Algorithm Design ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
Spatiotemporal Resolution ◽  
Raindrop Size Distribution ◽  
Size Sorting ◽  
Raindrop Size ◽  
Differential Reflectivity

Abstract Raindrop size sorting is a ubiquitous microphysical occurrence in precipitating systems. Owing to the greater terminal fall speed of larger particles, a raindrop’s fall trajectory can be sensitive to its size, and strong air currents (e.g., a convective updraft) can enhance this sensitivity. Indeed, observational and numerical model simulation studies have confirmed these effects on raindrop size distributions near convective updrafts. One striking example is the lofting of liquid drops and partially frozen hydrometeors above the environmental 0°C level, resulting in a small columnar region of positive differential reflectivity ZDR in polarimetric radar data, known as the ZDR column. This signature can serve as a proxy for updraft location and strength, offering operational forecasters a tool for monitoring convective trends. Beneath the 0°C level, where WSR-88D spatiotemporal resolution is highest, anomalously high ZDR collocated with lower reflectivity factor at horizontal polarization ZH is often observed within and beneath convective updrafts. Here, size sorting creates a deficit in small drops, while relatively large drops and melting hydrometeors are present in low concentrations. As such, this unique raindrop size distribution and its related polarimetric signature can indicate updraft location sooner and more frequently than the detection of a ZDR column. This paper introduces a novel algorithm that capitalizes on the improved radar coverage at lower levels and automates the detection of this size sorting signature. At the algorithm core, unique ZH–ZDR relationships are created for each radar elevation scan, and positive ZDR outliers (often indicative of size sorting) are identified. Algorithm design, examples, performance, strengths and limitations, and future development are discussed.

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