Seasonal Precipitation Variability and Non-Stationarity Based on the Evolution Pattern of the Indian Ocean Dipole over the East Asia Region

Sun-Kwon Yoon,Jong-Suk Kim,Sang-Myeong Oh,Hua Chen

doi:10.3390/rs13091806

Abstract

Non-linear behavioral links with atmospheric teleconnections were identified between the Indian Ocean Dipole (IOD) mode and seasonal precipitation over East Asia (EA) using statistical models. The analysis showed that the lower the lag time, the higher the correlation; more than a two-fold correlation for non-linear regression with a kernel density estimator than for the linear regression method. When the IOD peaked, a pattern of significant reductions in seasonal precipitation during the negative IOD period occurred throughout the Korean Peninsula (KP). The occurrence of the positive IOD was in line with the El Niño phenomenon and generated greater seasonal precipitation than only the positive IOD, which takes place from March to May. This change occurred more in the cold tongue El Niño than the warm pool El Niño, inducing much higher spring precipitation throughout the KP. When negative IODs and La Niña coincided, there was slightly greater precipitation from March to May compared to the sole occurrence of negative IODs. In positive (negative) IOD years, there was anti-cyclonic (cyclonic) circulation in the South China Sea (SCS), helping to transport moisture to EA. The composite precipitation anomalies in the positive (negative) IOD years show above (below) normal precipitation in southern China. In contrast, other parts of the EA experienced drier (humid) signals than normal years. In positive IOD years, the anti-cyclonic circulation strength of the Bay of Bengal and the SCS continued until autumn and spring of the following year. This shows possible remote connections between climate events related to the tropical Indian Ocean and variations in precipitation over EA.

Highlights

Introduction published maps and institutional affilThe frequency and intensity of extreme climate events have gradually increased; this has been attributed to rising global temperatures [1,2,3]
For the precipitation of the Korean Peninsula (KP), the probable mode values corresponding to the vertices of the joint probability density function were 0.632, 0.603, and 0.601 at lag times of 1, 3, and 6, respectively; the probable mode values tended to decrease with respect to lag time
There was a positive correlation between seasonal precipitation and Indian Ocean Dipole (IOD) pattern changes in each lag time over the KP

Summary

Introduction

Introduction published maps and institutional affilThe frequency and intensity of extreme climate events have gradually increased; this has been attributed to rising global temperatures [1,2,3]. Seasonal variations in regional water resource availability are closely linked to the characteristic changes in global climate [2,4,5,6,7]. These trends have significant implications for the efficient prediction and management of available water resources. It is increasingly important to understand the relationship between extreme climatic events and the seasonal variability of water resources using hydro-meteorological variables. Long-term hydro-meteorological changes are highly correlated with large-scale atmospheric teleconnections that predict the behavior of non-linear climate systems using ocean-related climate indices, such as the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mode [8,9,10,11,12]. Many studies on ENSO and the IOD report the shared understanding that these systems are major sources of large-scale atmospheric environmeniations

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