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Comparison of predictive skills offered by Prognocean, Prognocean Plus and MyOcean real-time sea level forecasting systems

机译:Prognocean,Prognocean Plus和MyOcean实时海平面预报系统提供的预测技能的比较

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摘要

We use three real-time forecasting systems (MyOcean, Prognocean, Prognocean Plus) which provide 7 day predictions of gridded sea level anomaly (SLA) data, and carry out two independent comparisons: Prognocean with MyOcean and Prognocean Plus with MyOcean. MyOcean uses the physically based model, while the other two systems utilise a few data-based models. Because of different spatial resolutions of gridded SLA forecasts, two experiments are conducted (grid sizes of 1 degrees x 1 degrees and 1/4 degrees x 1/4 degrees). The spatial resolutions of SLA forecasts provided by the MyOcean system are artificially decreased from 1/12 degrees x 1/12 degrees to the common resolution of 1 degrees x 1 degrees and 1/4 degrees x 1/4 degrees, for each experiment. The data span the time intervals: 28/04/2013-25/09/2014 and 08/08/2014-31/01/2015, for low and high spatial resolutions, respectively. The predictions from each system are separately compared with SLA data using: root mean square error, mean absolute error, Nash-Sutcliffe efficiency coefficient, coefficient of determination and index of agreement. A rigorous statistical comparison allows us to infer that the data-based approaches may reveal better performance in forecasting sea level variability than the physically based one. It is found that Prognocean and Prognocean Plus perform better than MyOcean in terms of prediction errors, however MyOcean resolves irregular SLA changes better since its prognoses highly correlate with data. (C) 2015 Elsevier Ltd. All rights reserved.
机译:我们使用三个实时预报系统(MyOcean,Prognocean,Prognocean Plus),它们可以提供7天的网格海平面异常(SLA)数据预报,并进行两个独立的比较:Prognocean与MyOcean和Prognocean Plus与MyOcean。 MyOcean使用基于物理的模型,而其他两个系统则使用一些基于数据的模型。由于网格化SLA预测的空间分辨率不同,因此进行了两个实验(网格大小为1度x 1度和1/4度x 1/4度)。对于每个实验,由MyOcean系统提供的SLA预测的空间分辨率都会从1/12度x 1/12度人工降低到1度x 1度和1/4度x 1/4度的通用分辨率。数据的时间间隔分别为:28/04 / 2013-25 / 09/2014和08/08 / 2014-31 / 01/2015,分别用于低和高分辨率空间分辨率。每个系统的预测分别使用以下方法与SLA数据进行比较:均方根误差,平均绝对误差,纳什-萨特克利夫效率系数,确定系数和一致性指数。严格的统计比较使我们可以推断,基于数据的方法可能比基于物理的方法显示出更好的海平面变化预测性能。发现Prognocean和Prognocean Plus在预测误差方面比MyOcean更好,但是MyOcean可以更好地解决不规则SLA变化,因为其与数据高度相关。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Ocean Engineering》 |2016年第1期|44-56|共13页
  • 作者单位

    Univ Wroclaw, Dept Geoinformat & Cartog, Inst Geog & Reg Dev, Fac Earth Sci & Environm Management, Pl Uniwersytecki 1, PL-50137 Wroclaw, Poland|Wroclaw Univ Technol, Wroclaw Ctr Networking & Supercomp, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland;

    Univ Wroclaw, Dept Geoinformat & Cartog, Inst Geog & Reg Dev, Fac Earth Sci & Environm Management, Pl Uniwersytecki 1, PL-50137 Wroclaw, Poland|Wroclaw Univ Technol, Wroclaw Ctr Networking & Supercomp, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland;

    Univ Wroclaw, Dept Geoinformat & Cartog, Inst Geog & Reg Dev, Fac Earth Sci & Environm Management, Pl Uniwersytecki 1, PL-50137 Wroclaw, Poland|Wroclaw Univ Technol, Wroclaw Ctr Networking & Supercomp, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sea level anomaly; Prediction; Prognocean; Prognocean Plus; MyOcean; Statistics;

    机译:海平面异常;预测;预后;Prognocean Plus;MyOcean;统计;

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