主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

气象与环境学报 ›› 2024, Vol. 40 ›› Issue (3): 97-105.doi: 10.3969/j.issn.1673-503X.2024.03.012

• 论文 • 上一篇    下一篇

基于ETCCDI指数的京津冀地区极端气候事件特征及影响分析

宋扬1(),王冀2,*(),冯璞玉3,徐丽萍1,王凤4,张伟1,唐夕茹1,王玢1   

  1. 1. 北京市科学技术研究院城市系统工程研究所, 北京 100089
    2. 北京市气候中心, 北京 100089
    3. 中国农业大学土地科学与技术学院, 北京 100083
    4. 北京师范大学环境学院, 北京 100088
  • 收稿日期:2023-01-07 出版日期:2024-06-28 发布日期:2024-08-09
  • 通讯作者: 王冀 E-mail:1871002425@163.com;wangji_zl@163.com
  • 作者简介:宋扬,女,1986年生,副研究员,主要从事气候变化与能源安全研究,E-mail: 1871002425@163.com
  • 基金资助:
    国家社科基金青年项目“应对气候风险我国天然气国际供应链安全战略研究”(20CGJ026)

Characteristics and impact analysis of extreme climate events in Beijing-Tianjin-Hebei region based on ETCCDI indices

Yang SONG1(),Ji WANG2,*(),Puyu FENG3,Liping XU1,Feng WANG4,Wei ZHANG1,Xiru TANG1,Bin WANG1   

  1. 1. Institute of Urban Systems Engineering, Beijing Academy of Science and Technology, Beijing 100089, China
    2. Beijing Climate Center, Beijing 100089, China
    3. College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    4. School of Environment, Beijing Normal University, Beijing 100088, China
  • Received:2023-01-07 Online:2024-06-28 Published:2024-08-09
  • Contact: Ji WANG E-mail:1871002425@163.com;wangji_zl@163.com

摘要:

利用京津冀地区1961—2020年175个气象站逐日气温和降水资料, 通过计算9个典型极端指数, 采用线性趋势、Sen突变分析, 分析了极端气温和降水时空变化, 并基于极端指数构建极端事件影响评价指标体系, 量化了2003—2019年本地区受极端气候影响的强度。结果表明: 1961—2020年, 京津冀地区呈极端暖事件显著增多、冷事件显著减少趋势, 自20世纪90年代末以来增温速率快速增加, 冷事件减少突变时间早于暖事件增加; 与天津、河北两地相比, 北京极端高温增温及暖事件频次增多幅度最大、极端低温增温及冷事件减少最小, 说明北京暖事件更强、冷事件不弱; 京津冀地区极端降水指数呈微弱的减少趋势且年代际变化特征明显, 北京、河北极端降水量极值增大, 说明两地极强降水事件增强; 2020年日最高温(TXx)、暖昼(TX90p)、热持续指数(WSDI)、日最低温(TNn)略高于常年值, 冷夜(TN10p)、冷持续指数(CSDI)及降水指数低于常年值, 天津多个站点(CSDI)及降水指数为1961年以来最低, 指示本地区2020年的极端气温接近正常年、极端降水在天津地区为最少年; 2003年以来极端事件的影响总体上升; 北京气候灾害损失强度优于河北, 但极端天气强度较高。

关键词: 极端气温, 极端降水, 影响评价

Abstract:

Utilizing the daily temperature and precipitation data of 175 meteorological stations in Beijing-Tianjin-Hebei region from 1961 to 2020, the spatiotemporal variations of extreme temperature and precipitation events were analyzed using 9 typical extreme indices and methods of linear trend and Sen's mutation. An impact evaluation index system was constructed based on these extreme indices to quantify the local extreme climate impacts for the period of 2003-2019. The results indicate that the Beijing-Tianjin-Hebei region experienced a significant increase in extreme warm events and a significant decrease in extreme cold events from 1961 to 2020. Since the late 1990s, the warming rate has accelerated, with the decrease in cold events occurring earlier than the increase in warm events. Compared to Tianjin and Hebei, Beijing shows greater increase in extreme high temperatures and the warm event frequency, as well as smaller increase in extreme low temperatures and decrease in cold events. It implies the status of increasingly stronger warm events and less weak cold events in Beijing. The extreme precipitation indices in Beijing-Tianjin-Hebei region show a slight decreasing trend with notable decadal variability. Beijing and Hebei have experienced an increase in the precipitation maxima, suggesting an enhancement in extremely strong precipitation events in these areas. The year of 2020 shows slightly higher-than-normal values on the annual maximum temperature (TXx), warm days (TX90p), and warm spell duration index (WSDI), while lower-than-normal values for the annual minimum temperature (TNn), cold nights (TN10p), cold spell duration index (CSDI), and precipitation indices. Several stations in Tianjin have recorded the lowest CSDI and precipitation indices since 1961. It indicates that the extreme temperatures in 2020 are close to normal, while extreme precipitation in Tianjin is at a minimum state. Besides, the overall impacts of extreme events have increased since 2003. Although Beijing experiences lower climate disaster damage intensity compared to Hebei, it shows higher intensity of extreme weather events.

Key words: Temperature extremes, Precipitation extremes, Impact assessment

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