안정도지수를 이용한 우박 예측법 연구

Abstract

ABSTRACT

A Study of Hail Forecast by using Atmospheric Stability Indices

Park, Kyeong-hun Advisor : Prof. Ryu, Chan-su, Ph.D Department of Atmospheric Science Graduate School of Chosun University

Hail is a form of severe meso-scale meteorological phenomenon, which not only causes extensive damage to property but also results in loss of life, which is required to analyze a vast amount of meteorological data to forecast hail and to provide a relative support, but the time to accomplish the task is always limited. Therefore, this study to investigate the way to employ stability indices is accomplished, to quickly and accurately forecast hail. Hail was observed 105 times in the past 10 years(2005~2014) in Korea, scrutinized temporal, spatial and statistical characteristics of each hail occurrence. It particularly focuses on Atmospheric stability indices, such as SSI, LI, KI, TTI, CAPE, SRH, SWEAT and BRN, to assess conditions before and after the occurrence of hail events. In addition, it modifies the standard value of each stability index and creates a new combination of those stability indices, to produce a more accurate hail-forecast checklist. Moreover, it examines the application of the Numerical Weather Prediction data in hail forecast by retrospectively investigating 5 hail occurrences in 2015. As a results, it may demonstrate the accuracy of the hail-forecast checklist using the Numerical Weather Prediction data, which is updated every 6-hours, as opposed to the observatory data that is released every 12-hours. In fact, SSI, TTI and SRH are recognized as the most accurate tools in hail forecast, while SWEAT and BRN seem to be the least. As noted, those stability indices were reexamined using the modified standard value. SSI was derived from both 925~500hPa and 925~700hPa and the standard value is set at less than +3, while LI was set at less than +3. At the same time, KI score of more than 20, TTI score of more than 50, and CAPE and SRH scores of more than 0 were set as the standard value. In fact, this modification increases the accuracy of hail forecast by 15~43%. Additionally, the combination of SSI and TTI scores (SSI-TTI) with the modified standard values is found to produce the most accurate result. Lastly, SRH score of more than 150 is also found to cause hail, especially during January to March and October to December. Based on above findings, the hail-forecast checklist is finally produced. Then, it is verified that the Numerical Weather Prediction data may also provide accurate hail forecast 6-12 hours prior to the actual occurrence, when the retrospective study of 5 hail occurrences in 2015 was conducted.