气候变化下，极端气温事件频发且日益加剧，严重威胁人类及生态系统安全。与单一极端高温或低温事件相比，气温在数天内的快速转换（即气温急转极端事件）可能造成更剧烈的影响。然而，此类气温急转极端事件的时空分布格局及驱动机制尚未明晰。为此，基于1961—2022 年中国均一化格点气温数据集，识别中国冷转暖和暖转冷两类气温急转极端事件，探究了其时空分布特征及其与海表温度异常的耦合关系。结果表明：①中国超90% 的区域气温急转极端事件年均发生频次达10 次以上，平均强度超过6.7 ℃。其中，内蒙古和东北地区为高频—高强区，云南、贵州和四川地区则为高频—低强区域。②近60 年以来，中国气温急转极端事件发生频率呈微弱下降趋势，但具有明显阶段性特征；1992 年之后气温急转极端事件下降趋势减弱，部分地区呈增加趋势；内蒙古、东北、云南及华北平原地区两类事件频次和强度均呈增加趋势，新疆及南方部分湿润地区呈下降趋势。③中国气温急转极端事件与海温异常存在3 个主要耦合模态，并分别与全球变暖、厄尔尼诺—南方涛动以及北太平洋涡旋振荡密切相关。海温异常通过调制气温、辐射及热通量等要素的波动性影响气温急转的发生。研究结果有助于深化对气温急转极端事件变化的认识，为极端骤变事件的预测与风险评估提供科学依据。

Abstract：Under global warming, extreme temperature events are occurring with increasing frequency and intensity, posing a serious threat to human societies and ecosystems globally. Compared with single extreme heat or cold events, rapid temperature whiplashes between cold and heat events within a few days cause more acute and severe impacts. However, the spatial patterns, trends, and potential driving factors of such whiplash events are yet to be understood. Using daily air temperature data from the China Homogenized Gridded Climate Dataset for 1961-2022, here we examine the spatiotemporal patterns of extreme temperature whiplash events in China, and investigate their relationships with sea surface temperature anomalies applying the Maximum Covariance Analysis (MCA). Our results show that: (1) extreme temperature whiplash events occurred more than 10 times annual in over 90% of the regions across China, with a mean intensity exceeding 6.7 ℃ . Spatially, Inner Mongolia and Northeast China emerge as high-frequency and high-intensity hotspots for both warm-to-cold and cold-to-warm whiplash events, while the regions such as Yunnan, Guizhou, and Sichuan are characterized as a high-frequency and low-intensity zones. Over the 1961-2022 period, both types of temperature whiplash events exhibit a weak declining trend across China, with an abrupt shift occurring around 1990. After 1992, both types show either a weakened declining trend or shifted to an increasing trend. Spatially, significant increases in frequency and intensity are observed over Inner Mongolia, Northeast China, Yunnan, and the North China Plain, whereas decreases are observed over Xinjiang and parts of the southern humid regions. (2) The MCA results reveal that the three leading modes represent the coupling relationship between extreme temperature whiplash events in China and global Sea Surface Temperature (SST) anomalies, accounting for 14.3%, 10.9%, and 7.3% of the total variance, respectively. These modes are mainly associated with global warming, the El Niño-Southern Oscillation (ENSO), and the North Pacific Gyre Oscillation (NPGO), respectively. (3) Further diagnostics of local physical processes indicate that SST anomalies influence extreme temperature whiplash events by modulating air temperature, radiation, and heat fluxes. These findings advance the understanding of the changes in extreme temperature whiplash events, providing a scientific basis for the prediction and risk assessment of such extreme events.