Radar-Based Automatic Identification and Quantification of Weak Echo Regions for Hail Nowcasting

Junzhi Shi,Huizhen Jia,Ping Wang,Di Wang

doi:10.3390/atmos10060325

Abstract

The identification of some radar reflectivity signatures plays a vital role in severe thunderstorm nowcasting. A weak echo region is one of the signatures that could indicate updraft, which is a fundamental condition for hail production. However, this signature is underutilized in automatic forecasting systems due to the lack of a reliable detection method and the uncertain relationships between different weak echo regions and hail-producing thunderstorms. In this paper, three algorithms related to weak echo regions are proposed. The first is a quasi-real-time weak echo region morphology identification algorithm using the radar echo bottom height image. The second is an automatic vertical cross-section-making algorithm. It provides a convenient tool for automatically determining the location of a vertical cross-section that exhibits a visible weak echo region to help forecasters assess the vertical structures of thunderstorms with less time consumption. The last is a weak echo region quantification algorithm mainly used for hail nowcasting. It could generate a parameter describing the scale of a weak echo region to distinguish hail and no-hail thunderstorms. Evaluation with real data of the Tianjin radar indicates that the critical success index of the weak echo region identification algorithm is 0.61. Statistics on these data also show that when the weak echo region parameters generated by the quantification algorithm are in a particular range, more than 85% of the convective cells produced hail.

Highlights

Severe thunderstorms are the most frequent weather threats to life and property in NorthChina [1,2]
Since we mainly focused on severe thunderstorms, in order to relieve computing pressure, the cells with a maximum reflectivity of less than 40 dBZ were excluded from the study
This paper proposed three algorithms related to weak echo regions, including a WER morphology detection algorithm, an automatic vertical cross-section-making algorithm, and a weak echo region quantification method

Summary

Introduction

Severe thunderstorms are the most frequent weather threats to life and property in NorthChina [1,2]. Severe thunderstorms are the most frequent weather threats to life and property in North. Since thunderstorms have small spatial scales and rapidly evolve, their monitoring and nowcasting commonly rely on weather surveillance radars. Weather radars can capture three-dimensional thunderstorm structure information by volume scanning with a high time and space resolution to determine their severity and development stage. In radar-based severe thunderstorm nowcasting, the identification of updrafts can help forecast some high impact events [4,5,6]. The observation of updrafts in single-polarization radars relies on specific morphology signatures of vertical reflectivity, such as the echo overhang, weak echo region, and bounded weak echo region. For dual-polarization radars, differential reflectivity and differential phase are good indicators of updrafts [7,8,9]

Methods

Results

Conclusion