Version 1
: Received: 23 September 2020 / Approved: 25 September 2020 / Online: 25 September 2020 (11:45:13 CEST)
How to cite:
Kim, J.; Yoon, S.; Oh, S. Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region. Preprints2020, 2020090605. https://doi.org/10.20944/preprints202009.0605.v1
Kim, J.; Yoon, S.; Oh, S. Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region. Preprints 2020, 2020090605. https://doi.org/10.20944/preprints202009.0605.v1
Kim, J.; Yoon, S.; Oh, S. Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region. Preprints2020, 2020090605. https://doi.org/10.20944/preprints202009.0605.v1
APA Style
Kim, J., Yoon, S., & Oh, S. (2020). Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region. Preprints. https://doi.org/10.20944/preprints202009.0605.v1
Chicago/Turabian Style
Kim, J., Sun-Kwon Yoon and Sang-Myeong Oh. 2020 "Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region" Preprints. https://doi.org/10.20944/preprints202009.0605.v1
Abstract
In this study, we used statistical models to analyze nonlinear behavior links with atmospheric teleconnections between hydrometeorological variables and Indian Ocean Dipole (IOD) mode over the East Asia (EA) region. The analysis of atmospheric teleconnections was conducted using principal component analysis and singular spectrum analysis techniques. Moreover, the nonlinear lag-time correlations between climate indices and hydrological variables were calculated using mutual information (MI) techniques. The teleconnection-based nonlinear correlation coefficients (CCs) were higher than the linear CCs in each lag time. Additionally, we documented that the IOD has a direct influence on hydro-meteorological variables, such as precipitation within the Korean Peninsula (KP). Moreover, during the warm season (June to September) the variation of hydro-meteorological variables in the KP demonstrated significantly decreasing patterns during positive IOD years and they have neutral conditions during negative IOD years in comparison with long-term normal conditions. Finally, the revealed relationship between climate indices and hydro-meteorological variables and their possible changes will allow better understanding of stakeholder decision-making regarding to manage of freshwater management over the EA region. It can also provide useful data for long-range water resources prediction, to minimize hydrological uncertainties in a changing climate.
Keywords
hydrometeorological variability; Indian Ocean Dipole; principal component analysis; mutual information
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
