基于HSIC核函数聚类的湖北省降雪气候区划
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湖北省气象局科技发展基金重点项目(2022Z05)、中国气象局创新发展专项(CXFZ2023J51)、中国长江电力股份有限公司项目(Z242302024)共同资助


Snow Climatic Regionalization in Hubei Province Based on HSIC Kernel Function Clustering
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    摘要:

    无资料地区雪灾防御参数常采用周边有资料的气象站参数替代,基于气候背景相似的降雪气候区划可以为代表站的选取提供科学依据。本文利用湖北省76个国家气象站1961—2020年的气象观测资料,选取了降雪初终日、雪日数、积雪日数、降雪量、最大积雪深度等12个多维时间序列指标,采用Hilbert-Schmidt Independence Criterion(HSIC)核函数的有偏估计公式计算12个指标的整体相似性,对湖北省降雪气候进行了聚类分析。结果表明:湖北省降雪气候可以划分为东南部、中部、西北部和西南部4个气候分区,分区的地带性分布特征与湖北省强降雪天气由北方冷空气南下产生的气候背景一致;初雪日从西北部向中部、西南部、东南部降雪区推迟,终雪日则正好相反,西北部的降雪日数和积雪日数最多;东南部代表站为黄石站,中部代表站有麻城、武汉、钟祥,西南部代表站有咸丰、巴东,西北部代表站郧西、老河口。HSIC核函数能很好处理较大年际波动的指标序列集之间的相似性,其聚类方法对湖北省降雪的气候区划较为合理,区划结果为湖北省精细化雪灾防御提供了技术依据。

    Abstract:

    Snow disaster is one of the meteorological disasters with a wide range of impact in winter. The technical parameters for engineering snow disaster prevention include the calculation of snow density, snow pressure, and other snow accumulation parameters. Due to the scarcity of snow observation stations in southern provinces and the lack of data, the calculation of important parameters for snow disaster prevention often uses data from other meteorological stations with snow accumulation observations as a substitute. How to choose representative stations with scientific significance is an urgent problem to be solved. The snowfall climate zoning based on similar climate backgrounds can provide a scientific basis for the selection of representative stations for snow cover parameters in areas without data. In the study of snowfall climate zoning in Hubei Province, due to the significant interannual fluctuations of climate indicators such as the first and last days of snowfall, snowfall amount, we use 12 climate indicators such as the dates of the first and last days of snowfall, the number of snow days, the number of snow cover days, the amount of snowfall and the maximum snow depth, to reflect the fluctuation characteristics of climate indicators in the snowfall area of Hubei Province. At the same time, we draw inspiration from common research methods on snowfall climate in the northern region and adopt the clustering analysis method based on Hilbert Schmidt Independence Criterion (HSIC) kernel function to calculate the overall similarity of multidimensional time series indicators to carry out the classification and zoning of snowfall climate in Hubei Province. The results show that the snowfall climate in Hubei Province can be divided into four climatic zones: southeast, central, northwest, and southwest. The zonal distribution characteristics of the zones are consistent with the climatic background of heavy snowfall in Hubei Province caused by the cold air from the north. The first snow day is delayed from the northwest to the central, southwest, and southeast, and the last snow day is just the opposite. The number of snow days and the number of days with snow cover in the northwest are the greatest. The southeast representative station is Huangshi station; the central representative station is Macheng, Wuhan, and Zhongxiang; the southwest representative station is Xianfeng and Badong; and the northwest representative station is Yunxi and Laohekou. The HSIC kernel function can handle the similarity between sets of indicator sequences with significant interannual fluctuations well, and its clustering method is more reasonable for the climate zoning of Hubei snowfall. The zoning results provide a technical basis for the refined snow disaster prevention in Hubei Province.

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魏华兵,史瑞琴,温泉沛,廖冬生,张俊,朱云柏.基于HSIC核函数聚类的湖北省降雪气候区划[J].气象科技,2024,52(3):392~402

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  • 收稿日期:2023-06-26
  • 定稿日期:2024-01-12
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  • 在线发布日期: 2024-06-25
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