Historical Reconstruction of Storm Surge Activity in the Southeastern Coastal Area of China for the Past 60 Years
Historical Reconstruction of Storm Surge Activity in the Southeastern Coastal Area of China for the Past 60 Years
复制标题
近60年中国东南沿海风暴潮活动历史重建
DOI：
10.1029/2019ea001056
复制
发表时间：
2020-08-01
影响因子：
3.1
通讯作者：
Liu, Rui
中科院分区：
文献类型：
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作者：
Ji, Tao;Li, Guosheng;Liu, Rui
由于验潮站观测、卫星高度计和数值模拟不能同时保证足够的时空分辨率和时间覆盖率，用现有的监测方法分析风暴潮活动的时空变异性是一项非常困难的任务。利用1958 ~ 2016年的再分析资料，对我国东南沿海地区的日最大风暴潮水位进行了统计重建。然后，我们使用地理差分分析（GDA）校准，以纠正重建结果。对统计模型和定标结果的验证表明，统计模型和GDA定标具有较高的相关性和较小的误差，具有较好的精度。然而，他们也揭示了一个可变的空间质量的多元统计模型在重建的最大风暴潮水位，特别是在极端事件的风暴潮活动，每日最大激增往往被低估。GDA定标结果较好地解决了这一问题，不仅能准确反映日最大风暴潮水位，而且能反映风暴潮时空动态演变的全过程。为建立长期序列、高精度的日最大风暴潮水位提供了一种有效的方法。该方法可以揭示风暴潮强度在气候尺度上的时空演变特征和主要变率特征。此外，它可以预测未来气候变化背景下风暴潮强度地理空间分布模式的可能趋势。
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.