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

Abstract

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 difficult. In this paper, we propose a statistical model using the 1980–2013 data collected at the Qinhuangdao observation station. The 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 variables. With 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 2014–2015. The predicted duration value is only two days less than the actual situation. The results prove that the new prediction model is feasible and effective to predict the period of ice coverage. The 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 PDF. The statistical model provides a useful tool to forecast ice conditions for planning and management of maritime activities.

Journal

Journal ID (publisher-id): JOUC

Title: Journal of Ocean University of China

Publisher: Science Press and Springer (China )

ISSN (Electronic): 1672-5182

Publication date (Electronic): 12 November 2019

Publication date (Print): 01 December 2019

Volume: 18

Issue: 6

Pages: 1265-1272

Affiliations

¹College of Engineering, Ocean University of China, Qingdao 266100, China

²Qinhuangdao Marine Environmental Monitoring Central Station of SOA, Qinhuangdao 066002, China

Author notes

*Corresponding author: DONG Sheng

Article

Publisher ID: s11802-019-4060-x

DOI: 10.1007/s11802-019-4060-x

Copyright statement: Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019.

License:

The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

Product

Self URI (journal-page): https://www.springer.com/journal/11802