秦岭作为我国的中央水塔和重要的生态屏障，气温变化对其水源涵养能力、生态系统稳定性以及区域气候调节功能有着重要影响。为探究统计降尺度偏差校正处理后的全球气候模式（NEX-GDDPCMIP6）数据对秦岭气温变化的模拟能力，预估未来气温变化，本文基于8个NEX-GDDP-CMIP6模式资料，对比 CN05. 1观测资料，评估了模式对秦岭年平均气温变化的模拟性能，预估了四种共享社会经济路径情景下（Shared Socioeconomic Pathway，SSP）区域未来气温变化。结果显示，NEX-GDDP-CMIP6各模式均能很好地再现1961-2014年观测的秦岭气温的分布型、空间趋势和时间变化特征，二者的相关系数分别为0. 90~0. 92、0. 51~0. 77和0. 46~0. 57，多模式集合平均（MME）模拟效果最好，与观测对应的相关系数分别为 0. 92、0. 65 和 0. 74。进一步基于 MME 预估的秦岭未来（2015-2100 年）气温持续增加，SSP 情景越高，增温幅度越大，SSP1-2. 6、SSP2-4. 5、SSP3-7. 0 和 SSP5-8. 5 情景下的增温趋势分别为0. 10 ℃·（10a）-1、0. 26 ℃·（10a）-1、0. 42 ℃·（10a）-1和0. 57 ℃·（10a）-1，趋势存在着海拔、纬向和经向依赖性，即：随海拔上升、纬度和经度增大而增大。相对于 1995-2014年参考时段，4种情景下秦岭在本世纪近期（2021-2040年）增温 0. 65~0. 97 ℃，中期（2041-2060年）增温 1. 37~2. 0 ℃，末期（2081-2100年）增温1. 39~4. 46 ℃。秦岭南、北坡未来气温变化一致，增温幅度近似秦岭平均，北坡增温大于南坡，SSP情景越高，北坡增温越快。研究结果可为秦岭生态保护及气候变化的适应性研究提供科学依据。

As China’s“Central Water Tower”and vital ecological barrier，the Qinling Mountains’temperature variability plays an important role in regional water conservation，ecosystem stability，and regional climate regulation. To evaluate the performance of statistically downscaled and bias-corrected Global Climate Models（GC‐ Ms）dataset（NEX-GDDP-CMIP6）in simulating observed temperature changes and further to project the future temperature variability over the Qinling Mountains，this study analyzes 8 NEX-GDDP-CMIP6 models against the CN05. 1 observational dataset. The assessment focuses on the models’ability to replicate observed annual mean temperature patterns，spatial trends，and temporal variability from 1961 to 2014. Furthermore，future temperature changes under the four Shared Socioeconomic Pathway（SSP）scenarios are projected for the period 2015-2100. The results demonstrate that 8 models effectively capture the observed spatial pattern，warming trends distribution and interannual variability，with corresponding correlation coefficients of 0. 90~0. 92，0. 51~ 0. 77，and 0. 46~0. 57 for 1961-2014，respectively. The multi-model ensemble mean（MME）outperforms individual models，with correlation coefficients of 0. 92，0. 65 and 0. 74 for the three metrics. The MME indicates a persistent warming trend over the Qinling Mountains，with the stronger warming under the higher SSP scenarios. The warming trends are projected increase at 0. 10 ℃·（10a）-1（SSP1-2. 6），0. 26 ℃·（10a）-1（SSP2-4. 5）， 0. 42 ℃·（10a）-1（SSP3-7. 0），and 0. 57 ℃·（10a）-1（SSP5-8. 5）for 2015-2100. Notably，the warming exhibit altitudinal，zonal，and meridional dependencies，intensifying with higher elevation，latitude，and longitude. Relative to the reference period（1995 -2014），the annual mean temperature is projected to increase by 0. 65~ 0. 97 ℃ in the near-term（2021-2040），1. 37~2. 0 ℃ in the mid-term（2041-2060），and 1. 39~4. 46 ℃ by the end-century（2081 -2100）under the four SSP scenarios. The temperature changes are temporally consistent across the North and South Slopes over the Qinling Mountains and following with the entire regional average. However，the North slope warms more rapidly than the South slope，particularly under high-emission scenarios （e. g. ，SSP5-8. 5），where North slope warming accelerates markedly. These findings provide critical insights for climate adaptation and ecological management in the Qinling Mountains.