| 引用本文: | 高 霞,李 睿,乔 平,等.1972—2023年京津冀地区极端气候事件的时空变化特征[J].灌溉排水学报,2026,45(7):151-162. |
| Gao Xia,Li Rui,Qiao Ping,et al.1972—2023年京津冀地区极端气候事件的时空变化特征[J].灌溉排水学报,2026,45(7):151-162. |
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| 摘要: |
| 【目的】全球变暖背景下，京津冀生态脆弱区极端气候事件频发。本研究定量揭示1972—2023年该地区极端气温和降水事件的时空分布规律，以支撑区域水资源管理、农业适应及风险管理。【方法】基于京津冀地区159个气象站点逐日数据，利用RClimDex模型计算28个极端气候指数，采用M-K趋势检验、一元线性回归、广义极值分布模型等方法分析其时空变化特征。【结果】极端气温事件变化显著：生长季长度以4 d/10 a的速率极显著延长，空间上呈南部平原地区最长、西北高原最短的分布特征；霜冻时间、冷昼时间等冷指数以4.6 d/10 a、3.9 d/10 a的速率显著减少，而夏日时间、暖夜时间等暖指数以3.3 d/10 a、11.7 d/10 a的速率显著增加，空间上，冷事件多发于西北山区但减少明显，暖事件集中于东南平原且增幅突出，且最低气温的升温速率较最高气温高0.3 ℃/10 a。极端降水事件时空异质性强：年降水量及各类极端降水指数未呈显著的长期变化趋势，但2013年以来极端降水指标年际变率明显增大，呈尾部上扬的非线性突变特征，反映极端降水事件风险趋于升级。空间上，燕山南麓和太行山东麓多发，北京-保定-石家庄沿线山前地带，极端降水量及其强度呈增强趋势。全区非常潮湿与极端潮湿天气对降水的贡献显著，强降水贡献率超过30%，沿海地区持续湿润时间略有增加。这些信号表明，尽管总量趋势不显著，但降水的极端性和局地性正在增强。【结论】1972—2023年京津冀地区极端气候呈暖干化趋势，暖事件增多、冷事件减少，降水极端性增强，集中于燕山南麓和太行山东麓。研究揭示了年降水量趋势不显著背景下极端降水的空间集聚性与潜在风险（如山前地带的高贡献率），为应对气候变化风险提供了科学依据。 |
| 关键词: 京津冀地区；极端气候指数；时空变化特征；极端气温指数；极端降水指数 |
| DOI：10.13522/j.cnki.ggps.2025389 |
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| Spatiotemporal variations of extreme climate events in the Beijing-Tianjin-Hebei Region |
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Gao Xia, Li Rui, Qiao Ping, Zheng Yuanxin
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1. Tangshan Meteorological Bureau, Tangshan 063000, China;
2. Tangshan Key Laboratory of Meteorological Disaster Early Warning, Tangshan 063000, China;
3. Shuozhou Meteorological Bureau, Shuozhou 036000, China; 4. Handan Meteorological Bureau, Handan 056000, China
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| Abstract: |
| 【Objective】Climate change has increased the frequency of extreme climate events. This paper analysed the spatiotemporal variation of extreme climate events in the Beijing-Tianjin-Hebei region in central China.【Method】The analysis was based on daily meteorological data measured from 159 stations across the region during 1972–2023. Twenty-eight extreme climate indices were calculated using the RClimDex model. Multiple analytical approaches, including the McLeod trend test, univariate linear regression and generalized extreme value (GEV) distribution model, were used to identify the spatiotemporal variation in these indices.【Result】Temporally, extreme temperature experienced pronounced changes, with the length of crop growing seasons increasing at a rate of 4 days per decade. Spatially, the growing season was longer in the southern plains than in the northwestern plateau. Frost days and cold days decreased by 4.6 days and 3.9 days per decade, respectively, while the number of warm summer days and warm nights increased at rates of 3.3 days and 11.7 days per decade, respectively. Spatially, cold events were more frequent in the northwestern mountainous areas but had declined from 1972 to 2023. In contrast, warm events mainly occurred in the southeastern plains and had increased from 1972 to 2023. The increasing rate of minimum temperature was 0.3 days per decade, higher than that of maximum temperature. Extreme precipitation was spatiotemporally heterogeneous. Temporal changes in annual precipitation and extreme precipitation did not show significant long-term trends, despite pronounced interannual variability. Spatially, extreme precipitation events were more frequent on the southern slopes of the Yanshan Mountains and eastern slopes of the Taihang Mountains; the amount and intensity of extreme precipitation increased along the Beijing-Baoding- Shijiazhuang piedmont zone. The number of consecutive humid days increased slightly in coastal areas. Temporal variation in regional annual precipitation showed no noticeable trend, but precipitation has become more extreme and localized. 【Conclusion】 Over the past 50 years, the Beijing-Tianjin-Hebei region has become more warming and drying. Meanwhile, extreme precipitation events have intensified, especially on the southern Yanshan slopes and eastern Taihang slopes. This study identifies the spatial clustering and potential hazards of regional extreme precipitation. These findings can help develop mitigation strategies to alleviate the adverse impact of climate change in the region. |
| Key words: Beijing-Tianjin-Hebei region; extreme climate indices; spatial and temporal variation characteristics; extreme temperature index; extreme precipitation index |
