scholarly journals Radar Signatures of Tropical Cyclone Tornadoes in Central North Carolina

2007 ◽  
Vol 22 (2) ◽  
pp. 278-286 ◽  
Author(s):  
Douglas Schneider ◽  
Scott Sharp
Keyword(s):  
Decision Making ◽  
North Carolina ◽  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Lead Time ◽  
Rotational Velocity ◽  
Decision Making Process ◽  
Radar Signatures ◽  
Tornado Warning ◽  
Reflectivity Data

Abstract During the tropical cyclone season of 2004, there were four tropical cyclones that spawned tornadoes in central North Carolina: Frances, Gaston, Ivan, and Jeanne. This study examines the environmental characteristics and radar signatures from these events. The tornado warning decision-making process is a difficult one during any severe weather event, but it is even more difficult in a tropical cyclone environment because of the subtlety of features and rapid tornadogenesis that can occur. Previous studies that have examined the characteristics of a tropical cyclone environment found that high low-level moisture content, high shear, and a midlevel intrusion of dry air are favorable for tornadoes. The tropical cyclones that are examined in the current study all exhibited these characteristics. Radar signatures associated with these tornadoes were more subtle and weaker when compared with nontropical cyclone tornadoes, but were still discernable. This study analyzed the radar signatures from tornadic and nontornadic storms in a tropical cyclone environment with the purpose of determining the best indicators of tornadogenesis. Three precursors were found to give good lead time for tornado touchdowns: 1) a near gate-to-gate mesocyclone rotational velocity of 20 kt (10.3 m s−1) or greater, 2) a hook or appendage signature in the reflectivity data, and 3) the presence of a velocity enhancement signature of 30 kt (15.4 m s−1) or greater between 7000 ft (2.1 km) and 14 000 ft (4.2 km) AGL. Using these signatures together in the tornado warning decision-making process can increase lead time and accuracy in the tropical cyclone environment.

scholarly journals COVID-19: A Vaccine Priority Index Mapping Tool for Rapidly Assessing Priority Populations in North Carolina

2021 ◽  
Vol 13 (3) ◽  
Author(s):  
Gregory Kearney ◽  
Katherine Jones ◽  
Yoo Min Park ◽  
Robert Howard ◽  
Ray H. Hylock ◽  
...  
Keyword(s):  
Decision Making ◽  
North Carolina ◽  
High Risk ◽  
Geographical Information ◽  
Decision Making Process ◽  
Public Health Response ◽  
Risk Population ◽  
Web Mapping ◽  
Mapping Tool ◽  
Priority Population

Background: The initial limited supply of COVID-19 vaccine in the U.S. presented significant allocation, distribution, and delivery challenges. Information that can assist health officials, hospital administrators and other decision makers with readily identifying who and where to target vaccine resources and efforts can improve public health response. Objective: The objective of this project was to develop a publicly available geographical information system (GIS) web mapping tool that would assist North Carolina health officials readily identify high-risk, high priority population groups and facilities in the immunization decision making process. Methods: Publicly available data were used to identify 14 key health and socio-demographic variables and 5 differing themes (social and economic status; minority status and language; housing situation; at risk population; and health status). Vaccine priority population index (VPI) scores were created by calculating a percentile rank for each variable over each N.C. Census tract. All Census tracts (N = 2,195) values were ranked from lowest to highest (0.0 to 1.0) with a non-zero population and mapped using ArcGIS. Results: The VPI tool was made publicly available (https://enchealth.org/) during the pandemic to readily assist with identifying high risk population priority areas in N.C. for the planning, distribution, and delivery of COVID-19 vaccine.Discussion: While health officials may have benefitted by using the VPI tool during the pandemic, a more formal evaluation process is needed to fully assess its usefulness, functionality, and limitations. Conclusion: When considering COVID-19 immunization efforts, the VPI tool can serve as an added component in the decision-making process.

scholarly journals Application of K1/3 weather coefficient to tropical cyclone avoidance

2017 ◽  
Vol 41 (1) ◽  
pp. 189-206
Author(s):  
Maciej Szymański ◽  
Bernard Wiśniewski
Keyword(s):  
Decision Making ◽  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Support Systems ◽  
Route Optimization ◽  
The North ◽  
Avoidance Manoeuvre ◽  
System Operator ◽  
The North Atlantic

Abstract The article presents the results of an application of K1/3 weather coefficient to tropical cyclone avoidance manoeuvre on the example of a tropical cyclones GASTON in the North Atlantic in. Avoidance manoeuvre was planned with the use of the Bon Voyage ORS (Onboard Routing System) of the AWT and also with the use of the programme CYKLON. The routes considered in the Bon Voyage system were generated by the route optimization algorithms of the system and routes programmed manually were generated by the system operator. Weather coefficient K1/3 was utilized as an index of safety of navigation in decision making regarding the ultimate route choice of all route variants generated and programmed in both decision making support systems. Results obtained point at the legitimacy of utilizing several decision support systems in solving the problem of tropical cyclone avoidance manoeuvre.

scholarly journals An Algorithm for Tracking Eyes of Tropical Cyclones

2009 ◽  
Vol 24 (1) ◽  
pp. 245-261 ◽  
Author(s):  
Pao-Liang Chang ◽  
Ben Jong-Dao Jou ◽  
Jian Zhang
Keyword(s):  
Standard Deviation ◽  
Tropical Cyclone ◽  
Eye Tracking ◽  
Tropical Cyclones ◽  
Satellite Images ◽  
Initial Guess ◽  
Computationally Efficient ◽  
Tracking Time ◽  
Reflectivity Data ◽  
Previous Volume

Abstract A tropical cyclone (TC) eye tracking (TCET) algorithm is presented in this study to objectively identify and track the eye and center of a tropical cyclone using radar reflectivity data. Twelve typhoon cases were studied for evaluating the TCET algorithm. Results show that the TCET can track TC centers for several hours. The longest tracking time is about 35 h. Eye locations estimated from different radars showed consistency with a mean distance bias of about 3.5 km and a standard deviation of about 1.5 km. The TCET analysis shows decreasing eye radius as TCs approach land, especially within 50 km of the coastline. The TCET algorithm is computationally efficient and can be automated by using the TC center in the previous volume or the estimated center from satellite images as an initial guess. The TCET may not accurately find the TC center when a TC is weak or does not have an enclosed eyewall or when it does have highly noncircular eyes. However, the algorithm is still suitable for operational implementation and provides high spatial and temporal resolution information for TC centers and eye radii, especially for intense TCs.

The Characteristics of Tropical Cyclone Formation in an Environment with Large Low-Level Low-Frequency (More than 10 days) Vorticity in the Western North Pacific

2020 ◽  
Vol 148 (10) ◽  
pp. 4101-4116
Author(s):  
Yi-Huan Hsieh ◽  
Cheng-Shang Lee ◽  
Hsu-Feng Teng
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Pacific ◽  
High Frequency ◽  
Lead Time ◽  
Western North Pacific ◽  
Initial Conditions ◽  
Surface Wind ◽  
Low Frequency ◽  
Cloud Clusters

AbstractA total of 14 tropical cyclones (TCs) that formed from 2008 to 2009 over the western North Pacific are simulated to examine the effects that environmental low-frequency and high-frequency vorticity (more than 10 days and less than 10 days, respectively) have on the formations of TCs [where the maximum surface wind ~25 kt (≈13 m s−1)]. Results show that all the simulations can reproduce the formation of a TC in an environment with a large 850-hPa low-frequency vorticity, even if the high-frequency parts are removed from the initial conditions. High-frequency vorticity mainly affects the timing and location of TC formation in such an environment. The 850-hPa vorticity is also analyzed in 3854 tropical cloud clusters that developed in 1981–2009 and may or may not have formed TCs; this reveals that the strength of the low-frequency vorticity is a crucial factor in TC formation. A tropical cloud cluster is expected to develop into a TC in an environment favorable for TC formation in the presence of a large 850-hPa low-frequency vorticity. The lead time for forecasting the formation of a TC can probably be extended under such conditions.

scholarly journals Radar Observations of Tornado-Warned Convection Associated with Tropical Cyclones over Florida

2017 ◽  
Vol 32 (1) ◽  
pp. 165-186 ◽  
Author(s):  
Steven M. Martinaitis
Keyword(s):  
False Alarm ◽  
Tropical Cyclones ◽  
Rotational Velocity ◽  
Elevation Angle ◽  
Probability Of Detection ◽  
Polarization Data ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Tornado Warning ◽  
Velocity Enhancement

Abstract Statistical evaluations of tornado warnings issued during recent tropical cyclone events yielded an above-average false alarm ratio. This study analyzed tornado-warned convection associated with Tropical Storms Debby (2012) and Andrea (2013) using superresolution and dual-polarization data from Weather Surveillance Radar-1988 Doppler radars located throughout the Florida peninsula to identify precursor characteristics and signatures that would distinguish tornadic events prior to tornadogenesis. A series of radar-based interrogation guidance at varying ranges from radar is presented to help facilitate the reduction of the tornado-warning false alarm ratio without compromising the probability of detection. For convection within 74.1 km from the nearest radar, low-level velocity characteristics include a rotational velocity ≥ 10.3 m s−1 (20 kt), shear across the rotation ≥ 0.010 s−1, and a contracting rotation diameter. The convection should also exhibit supercell reflectivity signatures and at least a mesocyclone velocity enhancement signature or horizontal separation of greater ZDR and KDP values. Guidance at a range from 74.1 to 129.6 km is similar except for not requiring the presence of a supercell reflectivity signature and the change of the rotational velocity guidance to ≥7.7 m s−1 (15 kt) at the 0.5°-elevation angle. Convection at a range beyond 129.6 km only requires a rotational velocity ≥ 7.7 m s−1 (15 kt) at the 0.5°-elevation angle. Evaluation of the radar interrogation guidance for tornadic events and tornado-warned convection for six tropical cyclones reduced the number of false alarm events by 28.9% and reduced the false alarm ratio from 0.740 to 0.669.

AAC Decision-Making and Mobile Technology: Points to Ponder

2014 ◽  
Vol 23 (2) ◽  
pp. 104-111 ◽  
Author(s):  
Mary Ann Abbott ◽  
Debby McBride
Keyword(s):  
Decision Making ◽  
Mobile Technology ◽  
Communication System ◽  
Augmentative And Alternative Communication ◽  
Evaluation Process ◽  
Decision Making Process ◽  
Alternative Communication ◽  
Ipod Touch ◽  
Feature Match

The purpose of this article is to outline a decision-making process and highlight which portions of the augmentative and alternative communication (AAC) evaluation process deserve special attention when deciding which features are required for a communication system in order to provide optimal benefit for the user. The clinician then will be able to use a feature-match approach as part of the decision-making process to determine whether mobile technology or a dedicated device is the best choice for communication. The term mobile technology will be used to describe off-the-shelf, commercially available, tablet-style devices like an iPhone®, iPod Touch®, iPad®, and Android® or Windows® tablet.

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