Abstract：Based on the data of seawater transparency and seawater turbidity,this paper gives a quantitative prediction model of "blue ocean" meteorological index,and analyzes its influencing factors,especially meteorological elements.The analysis shows that the prediction model of seawater transparency established by linear_model modular in scikit-learn machine learning library is effective.The "blue ocean" phenomenon is closely related to seawater transparency and "blue ocean" meteorological index can be quantified by the seawater transparency prediction model.Tidal range,sea state level and temperature have a significant impact on the "blue ocean" meteorological index.The index has a positive correlation with the temperature and a negative correlation with the wind.
蔡仕博, 王杰, 夏静雯, 赵晓彤, 闻丹. 基于机器学习的“蓝海”气象指数建立及其影响因素分析[J]. 气象水文海洋仪器, 2022, 39(1): 44-47.
Cai Shibo, Wang Jie, Xia Jingwen, Zhao Xiaotong, Wen Dan. Establishment of "blue ocean" meteorological index based on machine learning and its influencing factors analysis. Meteorological Hydrological and Marine Instrument, 2022, 39(1): 44-47.
Gordon H R,Brown O B,Jacobs M M .Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean[J].Applied Optics,1975,14(2):417-27.
2022, Vol. 39 
