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Impact of Snow Depth Initialization on Seasonal Prediction of Surface Air Temperature over East Asia for Winter Season

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Title
Impact of Snow Depth Initialization on Seasonal Prediction of Surface Air Temperature over East Asia for Winter Season
Other Titles
겨울철 동아시아 지역 기온의 계절 예측에 눈깊이 초기화가 미치는 영향
Authors
Kim, Seong-Joong
Woo, Sung-Ho
Kim, Baek-Min
Jeong, Jee-Hoon
Subject
Science & Technology - Other Topics
Keywords
Snow depth initialization; Seasonal prediction; Global climate model; Snow-albedo feedback; East Asian winter climate
Issue Date
2012
Citation
Kim, Seong-Joong, et al. 2012. "Impact of Snow Depth Initialization on Seasonal Prediction of Surface Air Temperature over East Asia for Winter Season". Korean Meteorological Society, 22(1): 117-128.
Abstract
Does snow depth initialization have a quantitative impact on sub-seasonal to seasonal prediction skill? To answer this question, a snow depth initialization technique for seasonal forecast system has been implemented and the impact of the initialization on the seasonal forecast of surface air temperature during the wintertime is examined. Since the snow depth observation can not be directly used in the model simulation due to the large systematic bias and much smaller model variability, an anomaly rescaling method to the snow depth initialization is applied. Snow depth in the model is initialized by adding a rescaled snow depth observation anomaly to the model snow depth climatology. A suite of seasonal forecast is performed for each year in recent 12 years (1999-2010) with and without the snow depth initialization to evaluate the performance of the developed technique. The results show that the seasonal forecast of surface air temperature over East Asian region sensitively depends on the initial snow depth anomaly over the region. However, the sensitivity shows large differences for different timing of the initialization and forecast lead time. Especially, the snow depth anomaly initialized in the late winter (Mar. 1) is the most effective in modulating the surface air temperature anomaly after one month. The real predictability gained by the snow depth initialization is also examined from the comparison with observation. The gain of the real predictability is generally small except for the forecasting experiment in the early winter (Nov.1), which shows some skillful forecasts. Implications of these results and future directions for further development are discussed.
URI
http://repository.kopri.re.kr/handle/201206/5973
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