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曾琦, 任国玉. 2020: 湖北省主要山系高影响天气指标空间特征分析与建模. 暴雨灾害, 39(2): 192-200. DOI: 10.3969/j.issn.1004-9045.2020.02.010
引用本文: 曾琦, 任国玉. 2020: 湖北省主要山系高影响天气指标空间特征分析与建模. 暴雨灾害, 39(2): 192-200. DOI: 10.3969/j.issn.1004-9045.2020.02.010
ZENG Qi, REN Guoyu. 2020: Analysis and modeling of spatial characteristics of high impact weather index of major mountain systems in Hubei Province. Torrential Rain and Disasters, 39(2): 192-200. DOI: 10.3969/j.issn.1004-9045.2020.02.010
Citation: ZENG Qi, REN Guoyu. 2020: Analysis and modeling of spatial characteristics of high impact weather index of major mountain systems in Hubei Province. Torrential Rain and Disasters, 39(2): 192-200. DOI: 10.3969/j.issn.1004-9045.2020.02.010

湖北省主要山系高影响天气指标空间特征分析与建模

Analysis and modeling of spatial characteristics of high impact weather index of major mountain systems in Hubei Province

  • 摘要: 为了揭示湖北省主要山系高影响天气指标空间分布特征,利用湖北省内1 716个气象站点2016—2018年逐日气温、降水资料,定义6个高影响天气指标,利用GIS空间插值方法,绘制了湖北省高影响天气指标的空间分布图。选取7个湖北主要山系坡面,分析各个坡面上高影响天气指标的海拔梯度变化特征。根据湖北主要山系分布将湖北分为8个区,利用DEM数据,采用多元回归分析方法,建立各个区域内高影响天气指标和经度、纬度、海拔高度和坡度这4个地理因子之间的关系模型。结果表明,模型相关性显著,对估算模型进行F检验,大部分通过置信度为0.95的相关性检验。研究结果可为湖北山区风电建设、旅游开发、风险区划等提供参考依据。

     

    Abstract: In order to reveal the spatial distribution law of high impact weather indicators of major mountain systems in Hubei Province,we used daily temperature and precipitation data of 1716 meteorological stations in Hubei Province from 2016 to 2018 to define and obtain 6 high impact weather indicators. Combined with GIS spatial interpolation method,the spatial distribution map of high impact weather indicators in Hubei Province was drawn. In this paper,7 main mountain slopes in Hubei were selected to further analyze the elevation gradient change characteristics of the high influence weather index on each slope. According to the distribution of main mountain systems in Hubei Province,we divided the province into 8 regions. Based on DEM data and multiple regression analysis method,the relationship model between high influence weather indices and four geographical factors including longitude,latitude,elevation and slope in each region is established. The results showed that the model was significantly correlated. F test was carried out on the estimation model; most of tests passed the correlation test with a confidence of 0.95. The study will provide references for wind power construction,tourism development and risk zoning in mountainous areas of Hubei Province.

     

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