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Historical Reconstruction of Storm Surge Activity in the Southeastern Coastal Area of China for the Past 60 Years

机译:过去60年来中国东南沿海地区风暴浪涌活动的历史重建

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摘要

It is a very difficult task to analyze the spatial and temporal variability of storm surge activity with current monitoring methods, because tide gauge observation, satellite altimeter, and numerical simulation do not ensure sufficient spatial and temporal resolution and temporal coverage at the same time. We propose to use a reanalysis data set, which covers the period from 1958 to 2016, to statistically reconstruct the daily maximum storm surge levels in the southeastern coastal area of China. Then, we used the Geographical Differential Analysis (GDA) calibration to correct the reconstruction results. The verification of the statistical model and the calibration results show that both the statistical model and the GDA calibration have a good accuracy in terms of high correlations and small errors. However, they also reveal a variable spatial quality of the multivariate statistical model in the reconstructed maximum storm surge levels, especially in the extreme events of the storm surge activity, the daily maximum surge is often underestimated. The GDA calibration result readily solves this problem, as it can accurately reflect not only the daily maximum storm surge levels but also the whole spatial and temporal dynamic storm surge evolution process. Therefore, this work provides an effective method to establish long-term sequence and high-precision daily maximum storm surge levels. This method can reveal the spatial and temporal evolution features of storm surge intensity at a climatic scale and main variability features. Moreover, it can predict possible trends in the geospatial distribution pattern of storm surge intensity in the context of future climate change.
机译:通过当前的监测方法分析风暴浪涌活动的空间和时间可变性是一项非常困难的任务,因为潮汐仪表观察,卫星高度计和数值模拟,并不能同时确保足够的空间和时间分辨率和时间覆盖。我们建议使用重新分析数据集,涵盖1958年至2016年的时间,统计地重建中国东南沿海地区的日常风暴浪涌水平。然后,我们使用地理差分分析(GDA)校准来校正重建结果。统计模型的验证和校准结果表明,统计模型和GDA校准都在高相关和小错误方面具有良好的准确性。然而,它们还揭示了在重建的最大风暴浪涌水平中的多变量统计模型的可变空间质量,特别是在暴风雨激增活动的极端事件中,日常最大浪涌通常被低估。 GDA校准结果易于解决这个问题,因为它不仅可以准确地反映每日最大风暴浪涌水平,而且可以准确地反映整个空间和时间动态风暴浪涌进化过程。因此,这项工作提供了建立长期序列和高精度每日最大风暴浪涌水平的有效方法。这种方法可以在气候刻度和主要变异特征中揭示风暴浪涌强度的空间和时间演化特征。此外,它可以预测未来气候变化的背景下风暴浪涌强度的地理空间分布模式的可能趋势。

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  • 来源
    《Oceanographic Literature Review》 |2020年第10期|2129-2130|共2页
  • 作者

    T. Ji; G. Li; R. Liu;

  • 作者单位

    Chongqing Key Laboratory of GIS Application Chongqing Normal University Chongqing China;

    Chongqing Key Laboratory of GIS Application Chongqing Normal University Chongqing China;

    Chongqing Key Laboratory of GIS Application Chongqing Normal University Chongqing China;

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  • 正文语种 eng
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