Data Analysis of Seasonal Air Temperature Variations in East Asia Using the Meteorological Datasets

• 영문명: Data Analysis of Seasonal Air Temperature Variations in East Asia Using the Meteorological Datasets
• 발행기관: 한국교원대학교 뇌기반교육연구소
• 저자명: Jae-Hee Cho Hak-Sung Kim
• 간행물 정보: 『Brain, Digital, & Learning』제12권 제4호, 637~647쪽, 전체 11쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2022.12.31

영문 초록

This study suggested to the National Center for Atmospheric Research (NCAR) command language (NCL) software setup in a Community Enterprise Operating System (CentOS) Linux-based computing environment, analyzing seasonal air temperature variations using the meteorological big data in the file format of the Network Common Data Form (NetCDF). The mathematic method of empirical orthogonal function (EOF), included as in the libraries within NCL, was used to analyze the statistical features of the East Asian atmospheric variability for the air temperatures at 850 hPa during the three climatological periods of 1971-2000, 1981-2010, and 1991-2020. The seasonal spatial patterns derived from EOF analysis showed that the seasonal air temperature variations in Korea, a downwind region in East Asia, were consistent with those in Mongolia and northern China, primarily throughout all seasons. The influence of the East Asian continent on Korea has gradually intensified during the early spring season. Furthermore, the expanding air mass over the Northwest Pacific to the East Asian region in summer has gradually intensified the influence on the air temperatures in Korea for the recent climatological period of 1991-2020. The dominant EOF mode is a monopole covering most of East Asia. The seasonal principal component analysis (PCA) on the first EOF mode in East Asia shows that it significantly correlates with the variations of the observed air temperatures in Korea ahead of the recent climatological period.

목차

Introduction

Materials and Methods

Results and Discussions

Conclusions

References

Authors Information

키워드

Meteorological big data EOF analysis air temperature seasonal variations NCL NetCDF Linux