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基于国家站和省级站资料的辽宁省近16 a 降水特征分析

Analysis of the precipitation characteristics based on the national and provincial meteorological stations datas in Liaoning Province in recent 16 years

  • 摘要: 为了解不同精度降水观测资料的差别,发挥精细降水观测对强降水的预警作用,基于辽宁省61个国家气象观测站(以下简称国家站)和1 785个省级气象观测站(以下简称省级站) 2007—2022年逐日、逐小时降水资料,对比研究了两类站点的月及汛期降水量、最大日降水量、暴雨日数及年雨涝指数的分布特征,结果表明:(1) 2007—2022年辽宁省国家站和省级站的月和汛期降水量变化具有较好的一致性,呈显著相关;两类站点汛期降水量均呈增加趋势,省级站的增速快于国家站;两类站点的平均汛期降水量接近,降水极值差异显著,省级站汛期降水量最大值高于国家站。(2)两类站点的最大日降水量极值和平均值的年际变化较为一致,均呈增加趋势;两类站点最大日降水量的空间分布较一致,只是辽宁中部和东部地区省级站比国家站有更多小范围的高值和低值中心。辽宁省8月更容易发生强降水,且日降水极值多出现在省级站,局地性强,极值明显高于国家站。(3)国家站和省级站暴雨日数和年雨涝指数均自西北向东南递增。两类站点的年雨涝指数高值区主要位于丹东和大连东南部地区,易发生由暴雨引发的直接和次生灾害。(4) 国家站由于数量少,空间分辨率较低,容易导致降水事件的极端性被低估,省级站能精细地刻画出辽宁省降水局部区域的细节特征,监测到更多国家站收集不到的强降水事件。

     

    Abstract: To understand the differences in precipitation observation data of different precisions and give full play of fine precipitation observation for the early warning of heavy precipitation, the daily and hourly precipitation data from 61 national meteorological stations (referred to as national stations) and 1,785 provincial meteorological stations (referred to as provincial stations) in Liaoning Province from 2007 to 2022 were utilized in this study. The distribution characteristics of monthly and flood season precipitation, maximum daily precipitation, the number of rainstorm days, and the annual rain-waterlogging index of the two stations were compared. The main results are as follows. (1) The monthly and flood season precipitation of national stations and provincial stations in Liaoning Province showed good consistency and significant correlation from 2007 to 2022. The precipitation in the flood season showed an increasing trend, with the increasing rate at provincial stations being faster than that of national stations. The average rainfall in the flood season of the two types of stations was similar, but a significant difference in extreme precipitation existed. The maximum precipitation in the flood season at provincial stations was higher than that at national stations. (2) The interannual variations in the extreme and average values of the maximum daily precipitation at the two types of stations were relatively consistent, showing an increasing trend. The spatial distributions of maximum daily precipitation at the two types of stations also agreed with each other, though provincial stations in central and eastern Liaoning Province exhibited more localized high-value and low-value centers than national stations. Heavy precipitation was more likely to occur in August in Liaoning Province. Most of the maximum daily precipitation extremes occurred at provincial stations, which showed strong locality and were significantly higher than national stations. (3) Both the number of rainstorm days and the annual rain-waterlogging index of national and provincial stations increased from northwest to southeast. The high-value area of the annual rain-waterlogging index of the two types of stations was mainly located in Dandong and the southeast of Dalian, which are prone to direct and secondary disasters caused by rainstorms. (4) Due to the small number and low spatial resolution of national stations, the extremes of precipitation events are likely to be underestimated. The provincial stations can accurately depict the detailed characteristics of precipitation in the local regions of Liaoning Province and monitor more extreme precipitation events that can not be recorded by national stations.

     

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