Abstract:
Two types of stochastic models have been developed to predict Arctic sea ice concentration. Linear Markov models are used to predictseaice concentration year-round at the seasonal time scale, while an auto-regressive (VAR) model is applied to predict summer daily sea ice centration and spring melting date at intra-seasonal time scale. The linear Markov model was built to capture co-variabilities in the atmosphere-ocean-sea ice system defined by sea ice concentration, sea surface and air temperature, geopotential height and winds at the 300mb level. Multivariate empirical orthogonal functions of these variables served as building blocks of the model. The predictive skill of the model was evaluated in a cross-validated fashion. The model shows good skill in predicting the signs of sea ice anomalies within the Arctic Basin during summer and fall. Particularly in the region north of the Chukchi,Beaufort, Eastern Siberian, Kara, and Barents Seas,theskill based on anomaly correlation is above 0.6 even ata nine-month lead. Because the Arctic Basin is completely frozen in winter and spring, the predictability can be seen only in the seasonal ice zone during these seasons. The model has higher skill in the Atlantic sector of the Arctic than in the Pacific sector. The model predicts well the interannual variability of September sea ice extent (SIE) but underestimates the accelerated long-term decline of SIE, resultingina systematic model bias. This model bias can be corrected by a constant bias correction or linear regression bias correction,leading toan improvedcorrelationskill of 0.93 for the two-month lead SIE prediction.
The (VAR) model is evaluated for predicting the summer time (May through September) Arctic sea ice concentration, using only the daily sea ice data and without direct information of the atmosphere and ocean. The cross-validated forecast skill of the VAR model is found to be superior to both the anomaly persistence and damped anomaly persistence at lead times of 20~60 days, especially over Northern Eurasian marginal seas and the Beaufort Sea.The daily forecast of ice concentration also leads to predictions of ice-free dates and September mean sea ice extent.While the detailed mechanism leading to the high predictability of intra-seasonal sea ice concentration needs to be further examined, the study reveals for the first time that Arctic sea ice can be predicted statistically with reasonable skills at the intra-seasonal time scales given the small signal-to-noise ratio of daily data.
本次午餐会将为报名参加的师生提供午餐，所有午餐会的报名都通过网络进行。请老师同学们访问MEL网页（http:/lecture.asp?id=1），在本次午餐会的“报名”一栏填写并提交。
本讲座将发布当天仅开放给科研人员、技术人员、博士后、访问学者等教师优先报名，第二天起开放给全体师生报名。学生应在规定时间内报名，如提前以教师的名义报名，将导致报名无效。
本周五下午4点为截止报名时间，总报名人数限制在100名以内。如未及时报上名，可于12:20直接到场听报告。如已报名但因事不能参加，也请在周五下午4点前告知。
午餐会一如既往地欢迎大家的关注，如有兴趣做讲座的老师。欢迎与我们联系。
