关键词: 气温, 增温趋势, 海拔依赖型增暖（EDW）, 均一化数据集

Abstract: Elevation dependent warming (EDW) exists in China, but there is no complete consensus among different studies regarding whether the warming rate intensifies (positive EDW) or weakens (negative EDW) with increasing elevation. Based on the daily homogenized temperature dataset from the meteorological stations with high spatial coverage currently in China, the EDW characteristics were analyzed in this study during 1961–2021 and multiple sub-periods within this timeframe. The results show that annual mean values of minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature (Tmean) all exhibit positive EDW, which is particularly pronounced over the Tibetan Plateau and its surrounding regions. The EDW of seasonal mean temperatures varies significantly. The seasonal average Tmax and Tmean have significant negative EDW in spring, and the same is true of Tmin since 1981, while the seasonal average Tmin, Tmax and Tmean in other seasons are mostly characterized by significant positive EDW. The EDW of monthly mean temperature shows certain temporal differences. Compared to Tmin and Tmean, the monthly variation in EDW for Tmax is the most pronounced across all periods. The positive EDW of Tmax reaches the strongest in November or December, and then weakens. By March or April, the negative EDW of Tmax reaches its peak before transitioning back to positive values by June, which then remain relatively stable through October. Considering the influence of latitude difference on EDW signal detection, separate analyses were conducted for different latitude bands, and the results are consistent with the above conclusions. This study reveals that, even within the same region, the strength of EDW can differ markedly across seasons, and the EDW signal may even reverse sign?shifting from positive to negative or vice versa. The EDW pattern in China are closely related to surface changes in high-elevation regions under the background of global warming. The EDW and its seasonal differences are likely caused by the radiation budget forcing associated with changes in snow cover and vegetation coverage.

Key words: Temperature, Warming rate, Elevation-dependent warming (EDW), Homogenized dataset