研究极端暖事件,对于应对气候变化、制定防灾减灾政策具有重要的理论价值与实际意义。利用1961—2017年中国地面气温日值格点数据集和1961—2050年CMIP6气候模式数据,通过模拟精度验证,筛选出模拟效果较好模式进行多模式集合平均,采用气候倾向率和反距离加权法（IDW）对新疆过去及未来6—9月极端暖事件日数、频率和强度时空变化进行研究。结果表明：过去57 a,新疆极端暖事件日数、频率和强度呈增加趋势,倾向率分别为0.2 d·(10a)^-1、0.02次·(10a)^-1和0.04 ℃·(10a)^-1;极端暖事件日数和频率的空间分布具有南疆高于北疆的特征,高发区为南疆西部,而强度则为北高南低的空间分布特征,高值区分布在北疆。未来33 a,在SSP245与SSP585情景下,新疆极端暖事件日数、频率和强度均呈显著增加趋势;相对于1961—2017年平均极端暖事件日数分别增加21 d和28 d,平均极端暖事件频率分别增加1.6次和1.8次,平均极端暖事件强度分别升高1.2 ℃和1.3 ℃,且SSP585情景下增速更显著;极端暖事件日数和频率高发区位于南疆中部,强度高发区仍在北疆;南疆极端暖事件日数、频率和强度增幅均大于北疆。伊朗副热带高压、西太平洋副热带高压位置的变化与土壤湿度变化会影响新疆极端暖事件的强弱。

Studying climate extreme events and extreme warm events provides theoretical and practical value to tackle climate change and formulate disaster reduction and prevention policies. In this article, multimodel averaging was modeled by selecting climate models yielding better simulation results using simulation accuracy verification based on Chinese daily surface temperature datasets from 1961 to 2017 and CMIP6 climate model data from 1961 to 2050. We used climate tendency rates and inverse distance weight methods to study spatiotemporal changes over time, including frequency and intensity of extreme warm events in Xinjiang from June to September in the past and future. During the last 57 years, the number of days and frequency and intensity of extreme warm events in Xinjiang were 0.2 d·(10a)^-1, 0.02 times·(10a)^-1, 0.04 ℃·(10a)^-1, respectively, showing an increased trend. The spatial distribution of days and frequency of extreme warm events were higher in southern Xinjiang than northern regions and the highest incidence area was the west of southern Xinjiang. While the spatial distribution of intensity in extreme warm events was high in the north and low in the south, northern Xinjiang showed the highest intensity area. In the following 33 years, the days, frequency, and intensity of extreme warm events were predicted to increase significantly, where the days of extreme warm events will increase by 21 days and 28 days under SSP245 and SSP585 scenarios, respectively. Compared with average levels from 1961 to 2017, the frequency of extreme warm events will increase by 1.6-and 1.8-fold and the intensity of extreme warm events will increase by 1.2 ℃ and 1.3 ℃. In addition, the increasing trend under SSP585 is more significant. High incidence areas for number of days and frequency of extreme warm events are located in the middle of southern Xinjiang. The high incidence area for intensity of extreme warm events is located in southern Xinjiang. An increase in the number of days, frequency, and intensity of extreme warm events in southern Xinjiang is greater than northern Xinjiang. Finally, changes in the position of Iran subtropical high pressure, western Pacific subtropical high pressure, and changes in soil moisture can influence the severity of extreme warm events in Xinjiang.