基于HSIC核函數(shù)聚類的湖北省降雪氣候區(qū)劃
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湖北省氣象局科技發(fā)展基金重點(diǎn)項(xiàng)目(2022Z05)、中國氣象局創(chuàng)新發(fā)展專項(xiàng)(CXFZ2023J51)、中國長(zhǎng)江電力股份有限公司項(xiàng)目(Z242302024)共同資助


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

    無資料地區(qū)雪災(zāi)防御參數(shù)常采用周邊有資料的氣象站參數(shù)替代,基于氣候背景相似的降雪氣候區(qū)劃可以為代表站的選取提供科學(xué)依據(jù)。本文利用湖北省76個(gè)國家氣象站1961—2020年的氣象觀測(cè)資料,選取了降雪初終日、雪日數(shù)、積雪日數(shù)、降雪量、最大積雪深度等12個(gè)多維時(shí)間序列指標(biāo),采用Hilbert-Schmidt Independence Criterion(HSIC)核函數(shù)的有偏估計(jì)公式計(jì)算12個(gè)指標(biāo)的整體相似性,對(duì)湖北省降雪氣候進(jìn)行了聚類分析。結(jié)果表明:湖北省降雪氣候可以劃分為東南部、中部、西北部和西南部4個(gè)氣候分區(qū),分區(qū)的地帶性分布特征與湖北省強(qiáng)降雪天氣由北方冷空氣南下產(chǎn)生的氣候背景一致;初雪日從西北部向中部、西南部、東南部降雪區(qū)推遲,終雪日則正好相反,西北部的降雪日數(shù)和積雪日數(shù)最多;東南部代表站為黃石站,中部代表站有麻城、武漢、鐘祥,西南部代表站有咸豐、巴東,西北部代表站鄖西、老河口。HSIC核函數(shù)能很好處理較大年際波動(dòng)的指標(biāo)序列集之間的相似性,其聚類方法對(duì)湖北省降雪的氣候區(qū)劃較為合理,區(qū)劃結(jié)果為湖北省精細(xì)化雪災(zāi)防御提供了技術(shù)依據(jù)。

    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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魏華兵,史瑞琴,溫泉沛,廖冬生,張俊,朱云柏.基于HSIC核函數(shù)聚類的湖北省降雪氣候區(qū)劃[J].氣象科技,2024,52(3):392~402

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  • 收稿日期:2023-06-26
  • 最后修改日期:2024-01-12
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  • 在線發(fā)布日期: 2024-06-25
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