A modified sea ice area empirical prediction model based on multi-source satellite remote sensing data for Liaodong Bay of the Bohai Sea, China

• Published in: Journal of Physics: Conference Series
• Main Authors: Chen, Xiaoyu, Wei, Dongni, Wang, Xifeng
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: IOP Publishing 2023
• Subjects: Sea ice
• Online Access: http://dx.doi.org/10.1088/1742-6596/2486/1/012020; https://iopscience.iop.org/article/10.1088/1742-6596/2486/1/012020; https://iopscience.iop.org/article/10.1088/1742-6596/2486/1/012020/pdf

Abstract Liaodong Bay is located in the north of the Bohai Sea, China. It experiences ice conditions of different degrees every year for about 3 months. Accurate prediction of sea ice area is of great significance for various marine activities. An empirical models based on the cumulative freezing temperature and cumulative melting temperature have been proposed in the past studies. This model can well describe the freezing and melting trend during each ice age, but it lost its accuracy for the prediction of short-term drastic change of sea ice area. In the present study, a modified empirical model considering sea surface temperature and wind besides cumulative freezing temperature and cumulative melting temperature is proposed. The coefficients of the modified model are fitted by the matched sea ice area of Liaodong Bay extracted from the multivariate satellite remote sensing images and the hydro-meteorological data from 2015, 2016, 2018 and 2019, while the data of 2020 are used for verification. Results show that the modified model can better adapt to the dramatic changes of sea ice area caused by short-term weather processes. The average absolute error is 685.71 km2 and the relative error is 23%. Finally, the influence of sea ice area on the time lag of temperature response and other factors such as water depth are discussed.