Brain, Digital, & Learning

 Open access, Peer Reviewed

Indexed in KCI

pISSN 2384-2474
eISSN 2586-7490

RESEARCH ARTICLE

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

Korea National University of Education

Correspondence to envir007@knue.ac.kr

Brain, Digital, & Learning. Volume 12, Number 4, 637–647, December 2022. https://doi.org/10.31216/BDL.20220039
Received on November 11, 2022, Revised on November 27, 2022, Accepted on December 28, 2022, Published on December 31, 2022.
Copyright © 2022. Institute of Brain based Education, Korea National University of Education This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.
Keywords

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

Section