A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts

2021年6月11日·
艾波
艾波
Corresponding
,
Mengchao Yu
,
Jingtian Guo
,
Wei Zhang
,
Tao Jiang
,
Aichao Liu
,
Wenbo Li
· 0 分钟阅读时长
摘要
Numerical models and correct predictions are important for marine forecasting, but the forecasting results are often unable to satisfy the requirements of operational wave forecasting. Because bias between the predictions of numerical models and the actual sea state has been observed, predictions can only be released after correction by forecasters. This paper proposes a spatiotemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products. The proposed method combines the advantages of numerical models and Forecast Discussion; specifically, it integrates subjective and objective information to achieve interactive spatiotemporal corrections for numerical prediction. The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judgment of forecasters to achieve numerical prediction accuracy. The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis, thereby achieving highly efficient correction for multitime forecasting fields. In this paper, the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis. Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states. The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.
类型
出版物
Journal of Ocean University of China (Oceanic and Coastal Sea Research)
publications
艾波
Authors
正教授
山东科技大学测绘与空间信息学院教授、博士生导师,地理信息科学系主任。山东省泰山产业领军人才、2022年中国青年测绘科技创新人才、2019年山东省青年“互联网+”新锐人物。2005年获武汉大学地图学与地理信息系统硕士学位,2011年获山东科技大学大地测量学与测量工程博士学位,现任中国地理信息产业协会教育与科普工作委员会委员。主要从事“互联网+海洋”研究,主持国家自然科学基金(面上、青年)、国家重点研发计划、863计划等国家级课题10余项,发表论文70余篇(其中SCI论文30余篇为第一/通讯作者)。研发海洋大数据管理、防灾减灾、三维可视化等软件平台,应用于国家海洋环境预报中心、自然资源部北海局等单位。成果中国近海动力参数长期预测及应用系统研发获地理信息科技进步二等奖(第一完成人),另获测绘科技进步一等奖、海洋科学技术奖二等奖等省部级奖励9项。指导学生连续三年获全国GIS应用技能大赛特等奖,个人获全国高校GIS青年教师讲课竞赛一等奖。2020年主持建设地理信息科学国家级一流本科专业,2024年获评山东科技大学教书育人楷模。
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