中山大学地理科学与规划学院,广东 广州 510006
张未(2001年生),男;研究方向:全球变暖与气候变化;E-mail:zhangw329@mail2.sysu.edu.cn
王大刚(1975年生),男;研究方向:极端气候变化,陆面过程模拟;E-mail:wangdag@mail.sysu.edu.cn
收稿:2025-05-18,
修回:2025-10-25,
录用:2025-11-19,
网络出版:2026-01-09,
移动端阅览
张未, 王程宇, 王大刚. 基于站点观测的中国大陆地区1979—2019年骤冷骤热时空变化特征[J/OL]. 中山大学学报(自然科学版)(中英文), 2026,1-9.
ZHANG Wei, WANG Chengyu, WANG Dagang. Temporal and spatial variation of abrupt cooling and warming in Chinese mainland based on site observations during 1979-2019[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2026, 1-9.
张未, 王程宇, 王大刚. 基于站点观测的中国大陆地区1979—2019年骤冷骤热时空变化特征[J/OL]. 中山大学学报(自然科学版)(中英文), 2026,1-9. DOI: 10.11714/acta.snus.ZR20250085.
ZHANG Wei, WANG Chengyu, WANG Dagang. Temporal and spatial variation of abrupt cooling and warming in Chinese mainland based on site observations during 1979-2019[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2026, 1-9. DOI: 10.11714/acta.snus.ZR20250085.
在气候变暖背景下,短期气温剧变会对人类社会与生态系统构成显著威胁。然而,现有研究多关注温度的绝对变化,对表征变化方向的“骤冷”与“骤热”尚缺乏充分探讨。鉴于此,本研究基于中国气象局1979—2019年全国2 295个气象观测站点的逐日最高气温数据,采用阈值法识别骤冷骤热现象,并结合Mann-Kendall趋势检验法与线性回归模型,探究其时空演变规律及影响因素。研究发现:1)空间上,青藏高原周边地区为全国骤冷(9.37次)、骤热(9.24次)现象年均频率最高的区域,而川渝地区增幅最为显著,华南地区虽频率较低但呈快速上升趋势,东北地区的频率接近全国平均水平但呈下降趋势;2)时间上,骤冷骤热现象年变化模式均符合正弦波模式,其中春季频率显著高于其他季节,全国60%以上的站点骤冷骤热现象频率呈上升趋势;3)归因分析显示,北极涛动(AO)正相位的加剧对东北地区骤冷现象频率下降具有一定影响,而太阳短波辐射量的增加则是影响东部及西南地区骤热事件频率上升的关键因素。本研究可为我国各区域制定有效的气候变化适应策略提供科学依据。
The increase in short-term temperature extremes, despite global warming, poses significant threats to ecosystems and society. However, most research has predominantly focused on absolute temperature changes rather than their direction, specifically, rapid cooling and heating events. Using daily maximum temperature data from 2 295 meteorological stations across China (1979-2019) provided by the National Meteorological Administration, this study employed the threshold method to identify such events. It systematically explored their spatiotemporal patterns and driving mechanisms by combining the Mann-Kendall trend test with linear regression models. The results show that the frequency was highest around the Tibetan Plateau (9.37 for cooling and 9.24 for heating events per year). While the Sichuan-Chongqing region experienced the most significant increase in these temperatures, southern China showed a rapid upward trend from a relatively low baseline. In contrast, northeastern China exhibited a declining trend. The annual pattern of both cooling and heating events follows a sinusoidal wave, peaking significantly in spring. Over 60% of the stations show increasing trends. Attribution analysis indicates that the intensified positive phase of the Arctic Oscillation influenced the decrease in rapid cooling events in the northeast, while increased solar shortwave radiation was a key factor driving the rise in rapid heating events in eastern and southwestern China. This study can provide a scientific foundation basis for formulating effective climate change adaptation strategies across various regions of China.
陈赟 , 沈浩 , 王晓慧 , 等 , 2023 . 基于Mann-Kendall趋势检验的城市能源碳达峰评估方法 [J]. 上海交通大学学报 , 57 ( 7 ): 928 - 938 .
杜勤勤 , 张明军 , 王圣杰 , 等 , 2018 . 中国气温变化对全球变暖停滞的响应 [J]. 地理学报 , 73 ( 9 ): 1748 - 1764 .
杜懿 , 王大刚 , 祝金鑫 , 2021 . 基于CMIP5的中国西北地区暖湿化演变研究 [J]. 水资源与水工程学报 , 32 ( 5 ): 61 - 69+77 .
马鹏里 , 张强 , 杨兴国 , 等 , 2006 . 近地层日最高最低气温变化特征 [J]. 气象科技 , 34 ( 1 ): 83 - 87 .
张龙斌 , 王璐 , 孟磊 , 等 , 2024 . 1981—2020年北京地区气温时空变化特征分析 [J]. 气象水文海洋仪器 , 41 ( 1 ): 60 - 63+67 .
ANKRAH J , MONTEIRO A , MADUREIRA H , 2024 . Temperature variability in coastal Ghana: A day-to-day variability framework [J]. Theor Appl Climatol , 155 ( 7 ): 6351 - 6370 .
BATHIANY S , DAKOS V , SCHEFFER M , et al , 2018 . Climate models predict increasing temperature variability in poor countries [J]. Sci Adv , 4 ( 5 ): eaar5809 .
CAI W , NG B , WANG G , et al , 2022 . Increased ENSO sea surface temperature variability under four IPCC emission scenarios [J]. Nat Clim Change , 12 ( 3 ): 228 - 231 .
COUMOU D , RAHMSTORF S , 2012 . A decade of weather extremes [J]. Nature Clim Change , 2 ( 7 ): 491 - 496 .
DU Y , WANG D , ZHU J , et al , 2022 . Intercomparison of multiple high-resolution precipitation products over China: Climatology and extremes [J]. Atmos Res , 278 : 106342 .
GE J , LIU Q , ZAN B , et al , 2022 . Deforestation intensifies daily temperature variability in the northern extratropics [J]. Nat Commun , 13 ( 1 ): 5955 .
HUTH R , KRAUSKOPF T , 2025 . European climatology of day-to-day surface air temperature difference in multiple data sets [J]. Int J Climatol , 45 ( 8 ): e8839 .
JUNG M , REICHSTEIN M , SCHWALM C R , et al , 2017 . Compensatory water effects link yearly global land CO 2 sink changes to temperature [J]. Nature , 541 ( 7638 ): 516 - 520 .
KARL T R , KNIGHT R W , PLUMMER N , 1995 . Trends in high-frequency climate variability in the twentieth century [J]. Nature , 377 ( 6546 ): 217 - 220 .
LIN H , YANG Y , WANG S , et al , 2023 . Evaluation of MSWX bias-corrected meteorological forcing datasets in China [J]. Sustainability , 15 ( 12 ): 9283 .
LIU Q , FU C , XU Z , 2024 . Revisiting two indices measuring high-frequency daily variability [J]. Int J Climatol , 44 ( 8 ): 2792 - 2807 .
LIU Q , TAN Z M , SUN J , et al , 2020 . Changing rapid weather variability increases influenza epidemic risk in a warming climate [J]. Environ Res Lett , 15 ( 4 ): 044004 .
LU E , ZENG Y , LUO Y , et al , 2014 . Changes of summer precipitation in China: The dominance of frequency and intensity and linkage with changes in moisture and air temperature [J]. J Geophys Res Atmos , 119 ( 22 ): 12575 - 12587 .
NEUKOM R , BARBOZA L A , ERB M P , et al , et al , 2019 . Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era [J]. Nat Geosci , 12 ( 8 ): 643 - 649 .
PAAIJMANS K P , BLANFORD S , BELL A S , et al , 2010 . Influence of climate on malaria transmission depends on daily temperature variation [J]. Proc Natl Acad Sci USA , 107 ( 34 ): 15135 - 15139 .
TONG X , WANG P , WU S , et al , 2022 . Urbanization effects on high-frequency temperature variability over South China [J]. Urban Clim , 42 : 101092 .
WAN H , KIRCHMEIER-YOUNG M C , ZHANG X , 2021 . Human influence on daily temperature variability over land [J]. Environ Res Lett , 16 ( 9 ): 094026 .
WANG X , WU G , QIN Y , 2022 . Day-to-day temperature variability in China during last 60 years relative to Arctic oscillation [J]. Earth Space Sci , 9 ( 12 ): e2022EA002587 .
WU F T , FU C , QIAN Y , et al , 2017 . High-frequency daily temperature variability in China and its relationship to large-scale circulation [J]. Int J Climatol , 37 ( 2 ): 570 - 582 .
XIAO Y , MENG C , HUANG S , et al , 2021 . Short-term effect of temperature change on non-accidental mortality in Shenzhen, China [J]. Int J Environ Res Public Health , 18 ( 16 ): 8760 .
XU Q , WEI S , LI Z , et al , 2025 . A new evaluation of observed changes in diurnal temperature range [J]. Geophys Res Lett , 52 ( 2 ): e2024GL113406 .
XU W , LI Q , WANG X L , et al , 2013 . Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices [J]. J Geophys Res Atmos , 118 ( 17 ): 9708 - 9720 .
ZHAN Z , ZHAO Y , PANG S , et al , 2017 . Temperature change between neighboring days and mortality in United States: A nationwide study [J]. Sci Total Environ , 584 : 1152 - 1161 .
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621
