摘要
干旱和热浪耦合是典型的多灾种事件,全球气候变暖增加了干旱和热浪耦合的风险。选取京津冀地区作为研究对象,以复杂网络理论为基础,构建干旱热浪时空耦合网络模型,拓展派系模型时空聚类方法,分析年代尺度上干旱和热浪时空聚类特征。结果表明:近55年京津冀地区干旱热浪耦合存在空间差异性,形成4个规律相异的时空耦合形态,即密集分布型(张家口—怀来—遵化,石家庄—邢台)、前期集中型(北部燕山地区)、后期集中型(太行山地区)、稀疏分布型(东部沿海区)。同时,干旱热浪空间耦合中心具有明显的迁移规律,以20世纪80年代为界,前期耦合中心分布偏北,位于北部燕山地区,后期则向南迁移,分布于南部太行山区。以时空数据为基础,提出面向非过程的多灾种时空网络构建方法,不仅是多灾种研究方法的探索,也是地理时空数据一体化研究的尝试,以期为多灾种时空耦合方法体系完善提供新的思路。
Concurrent occurrence of heat waves and droughts is a typical multi-hazard event.Global warming is leading to an increased risk of concurrent and compound extremes. In this study, we evaluated the changes in the pattern of concurrent drought and heat wave events in the Beijing-Tianjin-Hebei metropolitan region, China from 1960 to 2014. In addition, we used spatial-temporal data as a breakthrough point to examine the spatiotemporal clustering in concurrent heat wave and drought events by using bipartite networks. According to our results,based on the variations in heat waves and droughts trends, three distinct phases were identified：the first phase（1960s-1970s）, a relatively wet phase when heat waves continually decreased;the second phase（1980s-1990s）, when the climate conditions changed from a drought like period to a pluvial period, and the heat waves increased; the third phase（1999-2014）, when little precipitation was observed and the heat waves showed a decreasing trend. The correlation between heat waves and droughts was found to increase substantially between 1960 and 2014.Moreover, the concurrence of heat waves and droughts showed a significant pattern of spatiotemporal variation; before 1984, the concurrence of heat waves and droughts increased in the surrounding regions and the north of Yanshan Mountains; after 1984, high concurrence between heat waves and droughts was mainly observed in the south of Taihang Mountains. The research methodology used in this study can not only serve as the basis for research on multihazards, but also contribute to geographic spatiotemporal data modeling. Most importantly, the method based on the spatiotemporal network for multi-hazards makes up for the deficiencies of traditional methods in terms of utilization of spatiotemporal data.
出处
《地理研究》
CSSCI
CSCD
北大核心
2017年第8期1415-1427,共13页
Geographical Research
基金
国家重点研发计划项目(2016YFA0602403)
地表过程模型与模拟创新研究群体科学基金(41621061)
国家自然科学基金项目(41401599)
关键词
多灾种
干旱
热浪
复杂网络
时空耦合
multi-hazard
drought
heat waves
complex network
spatiotemporal clustering
