Applied Data Analytics to Buoy Records for Weather Window Evaluation

Tirtharaj Bhaumik, Shiladitya Basu
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引用次数: 0

Abstract

This paper analyzes weather data recorded by typical oceanographic buoys using data analytics and regression techniques. Time series data over a period of more than four decades (1976 – 2020) are reviewed and profiled. A set of key variables including seasonality, wind speed, wind direction, wave period, wave direction, etc., are screened from the buoy measurements to build a predictive model based on multiple linear regression for significant wave height prediction. A sensitivity analysis is then conducted for the available weather window corresponding to specified threshold operational limits of the significant wave height. Key insights are presented along with suggestions for future work to assist marine operators in planning and derisking offshore operations. Utilizing the algorithms and workflows presented in this paper, a user can increase confidence in weather window prediction, and develop safer, efficient offshore operation plans.
应用数据分析浮标记录的天气窗口评估
本文利用数据分析和回归技术对典型海洋浮标记录的气象数据进行了分析。回顾和分析了40多年(1976 - 2020)的时间序列数据。从浮标测量数据中筛选季节性、风速、风向、波浪周期、波浪方向等关键变量,建立基于多元线性回归的显著波高预测模型。然后,就有效波高的指定阈值操作限制对应的可用天气窗进行敏感性分析。提出了关键的见解以及对未来工作的建议,以帮助海上运营商规划和降低海上作业的风险。利用本文提出的算法和工作流程,用户可以提高对天气窗口预测的信心,并制定更安全、更有效的海上作业计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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