泛第三极关键节点区域高分辨率格网化气温数据集（2000-2016）

气温数据集来源于全球陆地数据同化系统(GLDAS)，该系统利用卫星和地面观测数，并基于先进的地表建模和数据同化技术，模型模拟初始化使用土壤湿度和来自LSM气候学的其他状态场,最终生成最优地表状态（例如土壤湿度和地表温度）和通量场，已广泛应用于全球变化与水循环研究中。原始气温数据为0.25˚×0.25˚的格网数据。以主要覆盖东南亚和中东的关键节点为研究区域，基于2001至2016年的森林冠层覆盖度数据，利用GEE对数据进行研究区的掩模裁剪并重采样，最终得到了34个关键节点区域2001-2016 16天合成的气温格网数据。

The temperature dataset is derived from the Global Land Data Assimilation System (GLDAS), which utilizes satellite and ground observation data. Based on advanced land surface modeling and data assimilation techniques, the model simulation is initialized with soil moisture and other state fields from LSM climatology, ultimately generating optimal land surface states (e.g., soil moisture and surface temperature) and flux fields. It has been widely applied in global change and water cycle research. The original temperature data are gridded data with a resolution of 0.25˚×0.25˚. Taking key nodes mainly covering Southeast Asia and the Middle East as the research areas, mask cropping and resampling of the data for the study regions were performed using GEE based on the forest canopy coverage data from 2001 to 2016. Finally, gridded temperature data synthesized every 16 days from 2001 to 2016 were obtained for 34 key node areas.