Publications
Detailed Information
한반도 겨울철 기온의 월별 통계 예측 모형 구축 및 검증 : Development and evaluation of statistical prediction model of monthly-mean winter surface air temperature in Korea
Cited 2 time in
Web of Science
Cited 0 time in Scopus
- Authors
- Issue Date
- 2018-06
- Publisher
- 한국기상학회
- Citation
- 대기, Vol.28 No.2, pp.153-162
- Abstract
- The statistical prediction model for wintertime surface air temperature, that is based on snow cover extent and Arctic sea ice concentration, is updated by considering El-Nino Southern Oscillation (ENSO) and Quasi-Biennial Oscillation (QBO). These additional factors, representing leading modes of interannual variability in the troposphere and stratosphere, enhance the seasonal prediction over the Northern Hemispheric surface air temperature, even though their impacts are dependent on the predicted month and region. In particular, the prediction of Korean surface air temperature in midwinter is substantially improved. In December, ENSO improved about 10% of prediction skill compared without it. In January, ENSO and QBO jointly helped to enhance prediction skill up to 36%. These results suggest that wintertime surface air temperature in Korea can be better predicted by considering not only high-latitude surface conditions (i.e., Eurasian snow cover extent and Arctic sea ice concentration) but also equatorial sea surface temperature and stratospheric circulation.
- ISSN
- 1598-3560
- Files in This Item:
- There are no files associated with this item.
Related Researcher
- College of Natural Sciences
- Department of Earth and Environmental Sciences
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.