scholarly journals Comparison of Radar-Based Hail Detection Using Single- and Dual-Polarization

2019 ◽  
Vol 11 (12) ◽  
pp. 1436 ◽  
Author(s):  
Skripniková ◽  
Řezáčová
Keyword(s):  
Comparative Analysis ◽  
Heavy Rain ◽  
Radar Data ◽  
Severe Weather ◽  
Detection Methods ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Rain Events ◽  
Single Polarization ◽  
Strong Agreement

The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) along with 21 heavy rain events. The hail detection results compared in this study were obtained using a criterion, which is based on single-polarization radar data and a technique, which uses dual-polarization radar data. Both techniques successfully detected large hail events in a similar way and showed a strong agreement. The hail detection, as applied to heavy rain events, indicated a weak enhancement of the number of false detected hail pixels via the dual-polarization hydrometeor classification. We also examined the performance of hail size detection from radar data using both single- and dual-polarization methods. Both the methods recognized events with large hail but could not select the reported events with maximum hail size (diameter above 4 cm).

scholarly journals Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings

2014 ◽  
Vol 29 (3) ◽  
pp. 623-638 ◽  
Author(s):  
Patrick C. Kennedy ◽  
Steven A. Rutledge ◽  
Brenda Dolan ◽  
Eric Thaler
Keyword(s):  
Radar Data ◽  
Front Range ◽  
Dual Polarization ◽  
Remotely Sensed Data ◽  
Colorado State University ◽  
Freezing Level ◽  
Severe Thunderstorms ◽  
Fort Collins ◽  
Single Polarization ◽  
Real Time Identification

Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.

scholarly journals Polarimetric Radar Characteristics of Melting Hail. Part III: Validation of the Algorithm for Hail Size Discrimination

2016 ◽  
Vol 55 (4) ◽  
pp. 829-848 ◽  
Author(s):  
Kiel L. Ortega ◽  
John M. Krause ◽  
Alexander V. Ryzhkov
Keyword(s):  
Radar Data ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Polarimetric Radar ◽  
Size Discrimination ◽  
Critical Success ◽  
Single Polarization ◽  
Differential Reflectivity

AbstractThis study is the third part of a paper series investigating the polarimetric radar properties of melting hail and application of those properties for operational polarimetric hail detection and determination of its size. The results of theoretical simulations in Part I were used to develop a hail size discrimination algorithm (HSDA) described in Part II. The HSDA uses radar reflectivity Z, differential reflectivity ZDR, and cross-correlation coefficient ρhv along with melting-level height within a fuzzy-logic scheme to distinguish among three hail size classes: small hail (with diameter D < 2.5 cm), large hail (2.5 < D < 5.0 cm), and giant hail (D > 5.0 cm). The HSDA validation is performed using radar data collected by numerous WSR-88D sites and more than 3000 surface hail reports obtained from the Severe Hazards Analysis and Verification Experiment (SHAVE). The original HSDA version was modified in the process of validation, and the modified algorithm demonstrates probability of detection of 0.594, false-alarm ratio of 0.136, and resulting critical success index (CSI) equal to 0.543. The HSDA outperformed the current operational single-polarization hail detection algorithm, which only provides a single hail size estimate per storm and is characterized by CSI equal to 0.324. It is shown that HSDA is particularly sensitive to the quality of ZDR measurements, which might be affected by possible radar miscalibration and anomalously high differential attenuation.

Observed Bulk Hook Echo Drop Size Distribution Evolution in Supercell Tornadogenesis and Tornadogenesis Failure

2021 ◽  
Author(s):  
Kristofer S. Tuftedal ◽  
Michael M. French ◽  
Darrel M. Kingfield ◽  
Jeffrey C. Snyder
Keyword(s):  
Drop Size ◽  
Thermodynamic Characteristics ◽  
Radar Data ◽  
Number Concentration ◽  
Size Distributions ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Near Surface ◽  
Microphysical Processes ◽  
Drop Size Distributions

AbstractThe time preceding supercell tornadogenesis and tornadogenesis “failure” has been studied extensively to identify differing attributes related to tornado production or lack thereof. Studies from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) found that air in the rear-flank downdraft (RFD) regions of non- and weakly tornadic supercells had different near-surface thermodynamic characteristics than that in strongly tornadic supercells. Subsequently, it was proposed that microphysical processes are likely to have an impact on the resulting thermodynamics of the near-surface RFD region. One way to view proxies to microphysical features, namely drop size distributions (DSDs), is through use of polarimetric radar data. Studies from the second VORTEX used data from dual-polarization radars to provide evidence of different DSDs in the hook echoes of tornadic and non-tornadic supercells. However, radar-based studies during these projects were limited to a small number of cases preventing result generalizations. This study compiles 68 tornadic and 62 non-tornadic supercells using Weather Surveillance Radar–1988 Doppler (WSR-88D) data to analyze changes in polarimetric radar variables leading up to, and at, tornadogenesis and tornadogenesis failure. Case types generally did not show notable hook echo differences in variables between sets, but did show spatial hook echo quadrant DSD differences. Consistent with past studies, differential radar reflectivity factor (ZDR) generally decreased leading up to tornadogenesis and tornadogenesis failure; in both sets, estimated total number concentration increased during the same times. Relationships between DSDs and the near-storm environment, and implications of results for nowcasting tornadogenesis, also are discussed.

A case study on severe hailstorm on 27 July 2019 in the province of Styria, Austria

2020 ◽  
Author(s):  
Satyanarayana Tani ◽  
Helmut Paulitsch
Keyword(s):  
Spatial Distribution ◽  
Life Cycle ◽  
Cell Tracking ◽  
Radar Data ◽  
Severe Weather ◽  
Crop Damage ◽  
Detection Methods ◽  
Maximum Diameter ◽  
Insurance System ◽  
Severe Thunderstorms

&lt;p&gt;A severe hailstorm activity on 27&lt;sup&gt;th&lt;/sup&gt; July 2019 created significant damage to crops in the province of Styria, Austria. The hail reports from ESWD (European Severe Weather Database) shows with maximum diameter up to 8 cm was noticed in the vicinity of the storm occurred. Total 1040 crop damage reports were claimed from the Austrian Hail Insurance System due to this severe hailstorm event. A close inspection and understanding features of severe hailstorms is helpful for hail risk assessment. The present study investigates the associated synoptic weather conditions and life cycle of the thunderstorm, and its dynamics. Further analysis carried about hail detection methods and crop hail damage assessment based remote sending and crowdsourcing data. The spatial distribution and temporal development of severe thunderstorms details extracted from radar data. The 3D radar data and storm cell tracking software used to capture the thunderstorm life cycle from the beginning to the dissipating stage. Radar-derived parameters collected for each storm cells, i.e. Duration of the storm cell, volume and area the storm cell, the cloud top height and the maximum reflectivity. Hail detection algorithms (Waldvogel and Auer) used to identify hail event period. The spatial distribution total hail kinetic energy maps prepared to capture the swath and intensity of the hail storms to classify possible crop-hail damaged areas. Hail observational data from ESWD (European Severe Weather Database) and HeDi (Hail event Data interface) and crop damage reports from the Austrian Hail Insurance System are utilised as a ground truth information.&amp;#160; An event-based severe hailstorm analysis help to find proper risk transfer solutions for loss adjustment.&lt;/p&gt;

scholarly journals A Robust Error-Based Rain Estimation Method for Polarimetric Radar. Part II: Case Study

2012 ◽  
Vol 51 (9) ◽  
pp. 1702-1713 ◽  
Author(s):  
Acacia S. Pepler ◽  
Peter T. May
Keyword(s):  
Estimation Method ◽  
Heavy Rain ◽  
Rain Gauge ◽  
Polarimetric Radar ◽  
Composite Methods ◽  
A New Technique ◽  
Rain Events ◽  
Radar Part ◽  
Rain Rates

AbstractRainfall estimation using polarimetric radar involves the combination of a number of estimators with differing error characteristics to optimize rainfall estimates at all rain rates. In Part I of this paper, a new technique for such combinations was proposed that weights algorithms by the inverse of their theoretical errors. In this paper, the derived algorithms are validated using the “CP2” polarimetric radar in Queensland, Australia, and a collocated rain gauge network for two heavy-rain events during November 2008 and a larger statistical analysis that is based on data from between 2007 and 2009. Use of a weighted combination of polarimetric algorithms offers some improvement over composite methods that are based on decision-tree logic, particularly at moderate to high rain rates and during severe-thunderstorm events.

The Joint Polarization Experiment: Polarimetric Radar in Forecasting and Warning Decision Making

2005 ◽  
Vol 20 (5) ◽  
pp. 775-788 ◽  
Author(s):  
Kevin A. Scharfenberg ◽  
Daniel J. Miller ◽  
Terry J. Schuur ◽  
Paul T. Schlatter ◽  
Scott E. Giangrande ◽  
...  
Keyword(s):  
Decision Making ◽  
Weather Forecast ◽  
Heavy Rain ◽  
Radar Data ◽  
Added Value ◽  
Polarimetric Radar ◽  
Operational Environment ◽  
Polarization Experiment ◽  
Estimation Algorithms ◽  
Precipitation Estimation

Abstract 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.

scholarly journals The Lightning Jump Algorithm for Nowcasting Convective Rainfall in Catalonia

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 397 ◽  
Author(s):  
Carme Farnell ◽  
Tomeu Rigo
Keyword(s):  
Heavy Rainfall ◽  
Direct Relationship ◽  
Heavy Rain ◽  
Radar Data ◽  
Severe Weather ◽  
Convective Rainfall ◽  
Skill Scores ◽  
Jump Algorithm ◽  
The Relationship ◽  
Ne Iberian Peninsula

Previous studies in Catalonia (NE Iberian Peninsula) showed a direct relationship between the Lightning Jump (LJ) and severe weather, from the study of different events, occurring in the last few years in this region. This research goes a step beyond by studying the relationship between LJ and heavy rainfall, considering different criteria. It selects those episodes exceeding the 40 mm/h threshold, dividing them between those with or without LJ occurrence (3760 and 14,238 cases, respectively). The time and distance criteria (<150 km and <50 min, respectively) allow the detection of rainfall episodes with LJ, to establish an accurate relationship between the jump and the heavy rain occurrence. Then, lightning and radar data are analyzed, considering monthly and hourly distributions. Skill scores for the period 2013–2018 showed good results, especially in summer, with values of POD ≃ 90% and FAR ≃ 10%

Comparative Analysis of Edge Detection Methods and its Implementation using UTLP Kit

2016 ◽  
Vol 3 (2) ◽  
pp. 26
Author(s):  
HEMALATHA R. ◽  
SANTHIYAKUMARI N. ◽  
MADHESWARAN M. ◽  
SURESH S. ◽  
◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Edge Detection ◽  
Detection Methods

scholarly journals Technical a Gaussian Mixture Model to Separate Birds and Insects in Single-Polarization Weather Radar Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1989
Author(s):  
Raphaël Nussbaumer ◽  
Baptiste Schmid ◽  
Silke Bauer ◽  
Felix Liechti
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Doppler Radar ◽  
Animal Movement ◽  
Weather Radar ◽  
Gaussian Mixture ◽  
Radar Data ◽  
Volume Data ◽  
Simple Method ◽  
Single Polarization

Recent and archived data from weather radar networks are extensively used for the quantification of continent-wide bird migration patterns. While the process of discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two Doppler radar products within a Gaussian mixture model to estimate the proportions of birds and insects within a single measurement volume, as well as the density and speed of birds and insects. This method can be applied to any existing archives of vertical bird profiles, such as the European Network for the Radar surveillance of Animal Movement repository, with no need to recalculate the huge amount of original polar volume data, which often are not available.

A Comparative Analysis of PCR-Based Detection Methods for Avian Malaria

2002 ◽  
Vol 88 (4) ◽  
pp. 819 ◽  
Author(s):  
F. Alexander Richard ◽  
Ravinder N. M. Sehgal ◽  
Hugh I. Jones ◽  
Thomas B. Smith
Keyword(s):  
Comparative Analysis ◽  
Avian Malaria ◽  
Detection Methods
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