Open AccessInvestigation of South Korea Precipitation Variation using Empirical Orthogonal Function (EOF) and Cyclostationary EOF
Author(s) -
Mingdong Sun,
Gwangseob Kim,
Xiaohong Xu,
Yan Wang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/643/1/012084
Subject(s) - empirical orthogonal functions , mode (computer interface) , precipitation , climatology , series (stratigraphy) , spatial ecology , spatial distribution , cyclostationary process , environmental science , common spatial pattern , temporal scales , time series , variance (accounting) , spatial variability , statistics , mathematics , geography , meteorology , geology , computer science , paleontology , ecology , channel (broadcasting) , computer network , accounting , business , biology , operating system
The monthly precipitation data of 56 stations during 47 years (1973-2019) in South Korea are comprehensively analysed using the EOF technique and CSEOF technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The first mode account for 77.07% of the total variance and exhibits annual cycle of corresponding PC time series with traditional spatial pattern, and the second mode spatial patterns account for 8.13% of the total variance and show strong north to south gradient. In CSEOF analysis, two leading modes temporal pattern of PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation, the first mode temporal pattern of PC time series account for 73.55% of the total variance and shows an increasing linear trend which represents that temporal variability of first mode pattern has been strengthened. The spatial distribution corresponding to two leading modes show monthly spatial variation. Compared with the EOF analysis, the CSEOF analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of South Korea historical precipitation.