对流层经验模型在中国VLBI站上的优化分析

利用2010~2012年的IGS天顶对流层延迟(ZTD)序列、ERA5格网数据积分ZTD序列,在中国4个VLBI站点上对目前常用的经验模型进行优化,分别建立Local_ERA和Local_ZTD模型。基于2013~2014年IGS并址站点ZTD数据,将改进后的2种模型与全球GPT2w模型、SHAO-Gm模型进行对比。结果表明,改进后的Local_ERA、Local_ZTD模型精度相近,相对于GPT2w、SHAO-Gm模型平均精度在4个VLBI站点上都有提高,尤其在水汽季节性变化较强的北京站改进效果明显;其中Local_ERA平均精度略高于Local_ZTD,比GPT2w模型精度提高7.90%,比SHAO-Gm模型精度提高21.26%。

Optimization Analysis of Tropospheric Delay Empirical Models on VLBI Sites in China

VLBI data processing contains real-time and after-action calculation modes. In VLBI real-time mode, tropospheric delay correction can provide forecast value, and a high precision tropospheric empirical model is needed to realize the real-time correction of tropospheric delay. Currently, various applications require high-precision tropospheric empirical models to achieve real-time correction of tropospheric delay. In this paper, the IGS zenith tropospheric delay (ZTD) sequence and the ERA5 grid data integration ZTD sequence from 2010 to 2012 are used to establish empirical models on four VLBI sites in China as Local_ERA and Local_ZTD respectively. Based on the 2013-2014 IGS site ZTD, the two improved models are compared with the global GPT2w and SHAO-Gm models. The results show that the improved Local_ERA and Local_ZTD models have similar precision. The average accuracy of the model has improved at four VLBI sites, compared to GPT2w and SHAO-Gm, especially in the Beijing station with strong seasonal variation of water vapor. The average accuracy of Local_ERA is slightly higher than that of Local_ZTD, which is 7.90% higher than that of GPT2w model, and 21.26% higher than SHAO-Gm model.