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山东省极端气候指数变化特征研究
引用本文:刘玄,唐培军,吴同帅,冯忠伦,刁艳芳,王刚.山东省极端气候指数变化特征研究[J].水利水运工程学报,2022,0(2):40-50.
作者姓名:刘玄  唐培军  吴同帅  冯忠伦  刁艳芳  王刚
作者单位:1.山东农业大学 水利土木工程学院, 山东 泰安 271000
基金项目:国家自然科学基金资助项目(41202174);山东省自然科学基金资助项目(ZR202102220203);山东省重点研发计划项目(2019GSF111043)
摘    要:为探究山东省极端气候指数的时空变化与特征,选取山东省1979—2020年95个气象站点的逐日气温和降水量实测数据,采用Mann-Kendall(M-K)检验方法和Sen斜率估计法计算时间变化特征,及Inverse Distance Weight(IDW)反距离权重法探究空间变化趋势。结果表明:(1)山东省境内低温极端气温指数(TN10p和FD0)呈下降趋势,下降速率分别为0.004 8和6.42 d/(10 a),高温极端气温指数(TX90p、TXx和SU25)呈上升趋势,上升速率分别为4.06 d/(10 a)、0.32 ℃/(10 a)和2.31 d/(10 a);其内陆区域和沿海区域极端气温指数表现出了与山东省整体较好的一致性,空间趋势不明显。(2)极端降水指数均呈上升趋势,沿海区域多大于内陆区域。降水强度指数(R95p、R99p和RX5day)呈显著增加趋势,增加速率分别为22.16、10.83和10.55 mm/(10 a),空间分布上,高值区域多分布在东部沿海区域和南部部分区域,可能会增加洪涝灾害风险。

关 键 词:极端气温    极端降水    极端气候指数    时空变化
收稿时间:2021-07-22

Study on the characteristics of extreme climate indices in Shandong Province
Affiliation:1.College of Water Conservancy and Civil Engineering, Shandong Agricultural University, Taian 271000, China2.Weifang Hydrological Center, Weifang 261031, China
Abstract:In order to explore the temporal and spatial changes of the extreme climate indices in Shandong Province, based on the daily temperature and precipitation data of 95 meteorological stations in Shandong Province from 1979 to 2020, we used the Mann-Kendall (M-K) test and Sen slope estimation methods to calculate the time-varying characteristics and the Inverse Distance Weight method (IDW) to explore the trend of spatial change. The results show that: (1) The extreme temperature indices (TN10p and FD0) characterized by low temperature in Shandong Province show a downward trend, and the decline rates are 0.004 8 and 6.42 d/(10 a) respectively, and TX90p, TXx and SU25 characterized by high temperature show an upward trend, and the ascent rates are 4.06 d/(10 a), 0.32 ℃/(10 a) and 2.31 d/(10 a) respectively. The extreme temperature indices in the inland and coastal areas show good consistency with Shandong Province, but the spatial trend is not obvious. (2) The extreme precipitation indices are upward, and most indices in the coastal area are larger than those in the inland area. The precipitation intensity indices (R95p, R99p and RX5day) show a significant increasing trend, and the ascent rates are 22.16, 10.83 and 10.55 mm/(10 a) respectively. In terms of spatial distribution, the high value areas are mostly the eastern coastal areas and some areas in the south, which may increase the risk of flood disasters.
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