Identifying ZDR Columns in Radar Data with the Hotspot Technique

Author:

Krause John12,Klaus Vinzent3

Affiliation:

1. a Cooperative Institute for Severe and High-Impact Weather Research and Operations, University of Oklahoma, Norman, Oklahoma

2. b NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

3. c Institute of Meteorology and Climatology, Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria

Abstract

Abstract A novel differential reflectivity (ZDR) column detection method, the hotspot technique, has been developed. Utilizing constant altitude plan projection indicators (CAPPI) of ZDR, reflectivity, and a proxy for circular depolarization ratio at the height of the −10°C isotherm, the method identifies the location of the base of the ZDR column rather than the entire ZDR column depth. The new method is compared to two other existing ZDR column detection methods and shown to be an improvement in regions where there is a ZDR bias. Significance Statement Thunderstorm updrafts are the area of a storm where precipitation grows, electrification is initiated, and tornadoes may form. Therefore, accurate detection and quantification of updraft properties using weather radar data is of great importance for assessing a storm’s damage potential in real time. Current methods to automatically detect updraft areas, however, are error-prone due to common deficiencies in radar measurements. We present a novel algorithmic approach to identify storm updrafts that eliminates some of the known shortcomings of existing methods. In the future, our method could be used to develop new hail detection algorithms, or to improve short-term weather forecasting models.

Funder

National Oceanic and Atmospheric Administration

Publisher

American Meteorological Society

Reference21 articles.

1. Assimilation of ZDR columns for improving the spinup and forecast of convective storms in storm-scale models: Proof-of-concept experiments;Carlin, J. T.,2017

2. Impact of WSR-88D intra-volume low-level scans on severe weather warning performance;Cho, J. Y. N.,2022

3. Tornado formation and intensity prediction using polarimetric radar estimates of updraft area;French, M. M.,2021

4. A simple and effective method for separating meteorological from nonmeteorological targets using dual-polarization data;Kilambi, A.,2018

5. Development of an operational convective nowcasting algorithm using raindrop size sorting information from polarimetric radar data;Kingfield, D. M.,2018

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3