基于遥感监测的秦岭南北积雪日数时空变化及影响因素

以海拔依赖型变暖为理论基础，研究山地积雪对气候变暖的响应机制，是当前气候变化研究的热点问题。基于2000—2019年MODIS积雪物候数据，对秦岭南北积雪日数时空变化进行分析，探讨了秋冬两季厄尔尼诺指数（NINO）、青藏高原气压对积雪异常的影响。结果表明：(1) 2013年后秦岭南北气候由“变暖停滞”转为“增温回升”，积雪日数随之呈现转折下降，积雪日数≥10 d栅格占比由前期的35.1%下降为8.6%。(2)在垂直地带规律上，秦岭山地以1950～2000 m为临界点，大巴山区以1600～1650 m为临界点，低海拔地区积雪日数随海拔增加速率要低于高海拔地区。2100～3150 m海拔带是积雪日数的垂直变化的关键带；(3)在影响因素上，NINO C区、NINO Z区秋冬海温和青藏高原冬季高压，是秦岭山地、汉江谷地和大巴山区积雪异常的有效指示信号。当赤道太平洋中部秋冬海温偏低，且青藏高原冬季高压偏低时，上述3个子区积雪日数异常偏多。(4)在环流机制方面，相对于积雪日数偏少年，秦岭南北积雪日数偏多年1—2月0℃等温线位置偏南，低温环境为增加冰雪物质积累、延缓冰雪消融提供了气温条件；1月区域存...

Spatiotemporal variation of snow cover days and influencing factors in north and south Qinling Mountains based on remote sensing monitoring

It is a hot issue in climate change research to study the response mechanism of mountain snow cover to climate warming based on elevation-dependent warming. Based on Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover phenology datasets from 2000 to 2019, we analyzed the spatiotemporal variation of snow cover days in the north and south of the Qinling Mountains by the methods of trend and detrended correlation analysis. Meanwhile, we identified the influencing factors of snow cover days from the perspectives of sea surface temperature (SST) in autumn and winter of the equatorial Pacific, high pressure over the Qinghai-Tibet Plateau, respectively. The results are as follows: (1) after 2013, climate condition in the north and south of the Qinling Mountains shifted from "warming hiatus" to "warming up", followed by declining snow cover days. And the proportion of areas with snow cover more than 10 days decreased from 35.1% to 8.6%. (2) We identified 1950-2000 m in the Qinling Mountains and 1600-1650 m in the Daba Mountains as transition zones of snow cover days. Above the transition zone, the increasing rate of snow cover days with altitude is higher than that of the low altitude area. Particularly, the altitudinal belt between 2100 m and 3150 m is the sensitivity zone of snow cover days to climate change. On the basis of the reference period of 2000-2004, we find that the elevation with 40, 60 and 80 days of snow cover increased by 100 m, 100 m and 150 m for the period of 2015-2019. (3) The SST in autumn and winter over NINO C and NINO Z regions and the winter high pressure over Qinghai-Tibet Plateau are two effective indicators of snow cover days anomaly in the Qinling Mountains, Hanjiang Valley and Daba Mountains. The lower SST of the central equatorial Pacific in autumn and winter, or the lower the winter high pressure over the Qinghai-Tibet Plateau is, the more excessive snow cover days would occur. (4) In terms of circulation mechanism, during the years with more snow cover days, the 0 ℃ isotherm in January and February was southerly, providing the proper temperature for increasing snow and ice accumulation and delaying snow and ice melting. Moreover, there was a weak water vapor convergence zone in January, which provided water vapor conditions for increasing snow and ice accumulation. The findings can enrich our understanding of winter climate change and provide early warning information of snow anomaly in the subtropical and warm-temperate zones in China.