The status and prospect of seasonal climate prediction of climate over Korea and East Asia: A review

Over the last few decades, there have been startling advances in our understanding of climate system and in modelling techniques. However, the skill of seasonal climate prediction is still not enough to meet the various needs from industrial and public sectors. Therefore, there are tremendous on-goi...

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Bibliographic Details
Published in:Asia-Pacific Journal of Atmospheric Sciences
Main Authors: Jeong, Jee Hoon, Lee, Hyun Soo, Yoo, Jin Ho, Kwon, Min Ho, Yeh, Sang Wook, Kug, Jong Seong, Lee, Jun Yi, Kim, Baek Min, Son, Seok Woo, Min, Seung Ki, Lee, Han Su, Lee, Woo Seop, Yoon, Jin Ho, Kim, Hyun Kyung
Format: Article in Journal/Newspaper
Language:unknown
Published: 한국기상학회 2018
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Online Access:https://hdl.handle.net/10371/206766
https://doi.org/10.1007/s13143-017-0008-5
Description
Summary:Over the last few decades, there have been startling advances in our understanding of climate system and in modelling techniques. However, the skill of seasonal climate prediction is still not enough to meet the various needs from industrial and public sectors. Therefore, there are tremendous on-going efforts to improve the skill of climate prediction in the seasonal to interannual time scales. Since seasonal to interannual climate variabilities in Korea and East Asia are influenced by many internal and external factors including East Asian monsoon, tropical ocean variability, and other atmospheric low-frequency variabilities, comprehensive understanding of these factors are essential for skillful seasonal climate prediction for Korea and East Asia. Also, there are newly suggested external factors providing additional prediction skill like soil moisture, snow, Arctic sea ice, and stratospheric variability, and techniques to realize skills from underlying potential predictability. In this review paper, we describe current status of seasonal climate prediction and future prospect for improving climate prediction over Korea and East Asia. N 1