地理科学 ›› 2021, Vol. 41 ›› Issue (4): 717-727.doi: 10.13249/j.cnki.sgs.2021.04.018

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1964—2019年辽宁省平均风速时空演变特征及其影响因素

范帅邦1(), 肖春柳2, 曹永强2(), 高璐3   

  1. 1.东北财经大学公共管理学院,辽宁 大连 116025
    2.辽宁师范大学地理科学学院,辽宁 大连 116029
    3.大连理工大学水利工程学院,辽宁 大连 116024
  • 收稿日期:2020-11-03 修回日期:2021-03-10 出版日期:2021-04-25 发布日期:2021-06-04
  • 通讯作者: 曹永强 E-mail:fanshuaibang@dufe.edu.cn;caoyongqiang@lnnu.edu.cn
  • 作者简介:范帅邦(1987−),男,辽宁大连人,博士,讲师,主要从事自然地理、经济地理、环境政策研究。E-mail:fanshuaibang@dufe.edu.cn
  • 基金资助:
    国家自然科学基金(51779114);辽宁省自然科学基金(2020-BS-222)

Multiscale Analysis of Wind Speed and Its Influencing Factors in Liaoning Province From 1964 to 2019

Fan Shuaibang1(), Xiao Chunliu2, Cao Yongqiang2(), Gao Lu3   

  1. 1. School of Public Administration, Dongbei University of Finance and Economics, Dalian 116025, Liaoning, China
    2. School of Geographical Sciences, Liaoning Normal University, Dalian 116029, Liaoning, China
    3. School of Hydraulic Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China
  • Received:2020-11-03 Revised:2021-03-10 Online:2021-04-25 Published:2021-06-04
  • Contact: Cao Yongqiang E-mail:fanshuaibang@dufe.edu.cn;caoyongqiang@lnnu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(51779114);Natural Science Foundation of Liaoning Province(2020-BS-222)

摘要:

风的变化程度和强弱会引起其他气象要素变化,探究风场时空分布及其历史变化规律,可为气候预报预测和风能科学利用提供重要参考。基于1964―2019年辽宁省23个气象站点风速及其他气象因子的逐日监测数据,利用小波分析及经验正交分解法对近56 a辽宁省风场、风速时空变化特征进行分析,并结合主成分分析法揭示其影响因素。结果表明:① 1964―2019年间辽宁省平均风速呈显著降低的态势,下降速率为0.13 m/(s·10a),月尺度上呈现出“双峰型”变化特点,季尺度上表现为春季>冬季>秋季>夏季,均未发生明显的突变现象。② 年际和年代际平均风速的空间分布均呈现以中部地区为中心、东西两侧逐渐降低的演变格局,但年代际风速高值区逐渐由带状转变为点状分布。③ 平均气温和日照时数的变化是辽宁省平均风速减弱的主要原因,日照时数的减少和平均气温的增加促使了平均风速的下降。

关键词: 平均风速, 时空演变特征, 经验正交函数分解(EOF), 主成分分析, 辽宁省

Abstract:

The degree and strength of the wind will cause changes in many meteorological elements. Exploring the temporal and spatial distribution of the wind field and its historical changes can provide important references for climate forecast and scientific utilization of wind energy. Based on the daily monitoring data of wind speed and other meteorological factors data of 23 meteorological stations in Liaoning Province from 1964 to 2019, this paper analyzed the spatial and temporal variation of the wind field and wind speed in Liaoning Province by multi-scale analysis using Empirical Orthogonal Function (EOF), Morlet wavelet analysis and Mann-Kendall non-parametric test. The results show that: 1) During 1964-2019, the average wind speed in Liaoning Province presented a significant decrease with a rate of 0.13 m/(s·10a). Further, this paper indicated that the bimodal distribution is a characteristic of intra-year trend analysis. The four seasons in a year were listed in the sequence as follows based on descending order of the decreasing rate value: spring, winter, autumn and summer. However, no abrupt changes were evident at all scales. 2) The spatial distribution of the average wind speed showed an evolutionary pattern centered on the central region and gradually decreased from east to west on both interannual and interdecadal scales, but the high-value area of the latter gradually changed from strip to point-like distribution. 3) The increase in average temperature and decrease in sunshine hours contributed more to the weakening of the average wind speed in Liaoning Province in the past 56 years. The results of the study provide a theoretical basis for the prevention and mitigation of wind disasters and the scientific utilization of wind energy in the region.

Key words: average wind speed, spatial and temporal evolution characteristics, Empirical Orthogonal Function (EOF), principal component analysis, Liaoning Province

中图分类号: 

  • F129.9