顾及区域相对高程的中国区域加权平均温度模型

针对区域相对高程对T_m模型影响研究领域的空缺，基于已有的对流层顶经验模型，讨论区域相对高程对T_m模型的影响，并在此基础上构建中国区域的h₀T_m回归模型，同时建立青藏高原地区的区域模型h₀T_m-Qz。模型检验结果表明：1）以ERA5格网数据为参考值，h₀T_m模型的RMS为2.43 K，相比于Bevis公式和GPT2w-1模型，精度分别提高了1.15 K(32%)和0.63 K(21%)；2）以探空数据为参考值，h₀T_m模型的RMS为2.48 K，相比于Bevis公式和GPT2w-1模型精度分别提高了1.19 K(32%)和2.06 K(45%)，h₀T_m模型在中国区域表现出较低的误差和良好的稳定性，尤其是在中国西部地区表现出更为显著的优势；3）顾及区域相对高程的青藏高原区域模型h₀T_m-Qz相较于该地区的单因子（T_s）区域模型T_sT_m-Qz和Bevis公式，精度分别提高了0.54 K(19%)和2.50 K(51%)。

A Weighted Mean Temperature Model Considering the Regional Relative Elevation for China

Based on the existing tropopause empirical model, we discuss the influence of regional relative elevation on T_m model. Based on this, the h₀T_m regression model of China region and the regional modelh₀T_m-Qz of Qinghai-Tibet plateau region are established. The results show that: 1) Taking ERA5 grid data as reference values, the root mean square error (RMS) ofh₀T_m model is 2.43 K, which is 1.15 K (32%) and 0.63 K (21%) higher than that of Bevis formula and GPT2w-1 model, respectively; 2) taking radiosonde data as reference values, the RMS ofh₀T_m model is 2.48 K, which is 1.19 K (32%) and 2.06 K (45%) higher than that of Bevis formula and GPT2w-1 model, respectively especially in western China, the h₀T_m model shows more significant advantages; 3) the regional modelh₀T_m-Qz of Qinghai-Tibet plateau, which takes into account the relative elevation of the region, is better than the single factor (surface) model in this region. The accuracy of the single factor (T_s) regional model T_sT_m-Qz and Bevis formula is improved by 0.54 K (19%) and 2.50 K (51%), respectively.