Application of synoptic patterns to the definition of seasons in the Republic of Korea

Author:

Kwon Jaeil12,Choi Youngeun1

Affiliation:

1. Department of Geography Konkuk University Seoul Republic of Korea

2. Research Institute 4D SOLUTION Co., Ltd. Seoul Republic of Korea

Abstract

AbstractIn this study, we applied the classification of synoptic patterns to define seasons. Principal component analysis (PCA) and k‐means clustering were employed to classify the synoptic patterns. In this analysis, seven synoptic patterns were classified, corresponding to two patterns exhibiting winter, spring, and autumn‐like patterns each and one representing summer‐like patterns. The climate characteristics of each synoptic pattern for summer, spring, and autumn were clearly different from each other. The two winter patterns were considered as one season. Seasons were defined based on the occurrence frequency of each synoptic pattern, using the 11‐day window size. Accordingly, the year was divided into first spring, second spring, summer, first autumn, second autumn, and winter. The onset dates of the corresponding seasons were March 8, April 15, June 6, September 8, October 23, and November 29, respectively. In the changing trend of the seasons calculated by year, the start date of first spring was earlier by approximately 2.0 days per decade, and second autumn was delayed by 1.7 days per decade. In addition, the length of first autumn increased by 2.9 days per decade, whereas the length of winter decreased by 3.3 days per decade. In this study, a new method that had not previously been applied in Korea was used to define seasons by considering various climate variables. Compared to previous studies, the seasonal definition method used in this study is objective and reflects comprehensive climate characteristics by considering diverse variables. Furthermore, the proposed methodology for defining the seasons for each year is applicable to the study of changes in seasonal onsets.

Publisher

Wiley

Subject

Atmospheric Science

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