Statistical Prediction for Annual Start Date and Duration of Sea-Ice Coverage at Qinhuangdao Observation Station

作     者：JIAO Chunshuo ZHANG Wanlei DONG Sheng 

作者机构：College of EngineeringOcean University of ChinaQingdao 266100China Qinhuangdao Marine Environmental Monitoring Central Station of SOAQinhuangdao 066002China 

出 版 物：《Journal of Ocean University of China》 (中国海洋大学学报（英文版）)

年 卷 期：2019年第18卷第6期

页      面：1265-1272页

核心收录：

学科分类：0710[理学-生物学] 11[军事学] 0908[农学-水产] 0707[理学-海洋科学] 0815[工学-水利工程] 0824[工学-船舶与海洋工程] 1109[军事学-军事装备学] 

基　　金：support of the National Natural Science Foundation of China (No. 51779236) the NSFC-Shandong Joint Fund Project (No. U1706226) the Ocean University of China under the support of 111 Project (No. B14028) 

主　　题：start date of sea ice duration of sea ice statistical prediction Weibull distribution Gaussian copula 

摘      要：Qinhuangdao City is located in the mid-latitude monsoon-affected region,and the timing of sea-ice coverage changes from year to year,making sea-ice forecasting *** this paper,we propose a statistical model using the 1980-2013 data collected at the Qinhuangdao observation *** start date and the duration of ice coverage are fitted with four marginal distributions,from which the best-fitted,i.e.,the Weibull distribution,is selected to form a joint probability density function(PDF),built by the Gaussian copula method,for the two *** a given start date forecast by the Gray-Markov model(GMM),the joint PDF becomes a conditional probability model,which predicts that the duration of ice coverage is most likely 33 days at the Qinhuangdao observation station in *** predicted duration value is only two days less than the actual *** results prove that the new prediction model is feasible and effective to predict the period of ice *** general sea-ice conditions that the sea ice would most likely form on December 8 and last for 80 days at the Qinhuangdao observation station could also be obtained from the joint *** statistical model provides a useful tool to forecast ice conditions for planning and management of maritime activities.