不同对流层天顶延迟模型在中国西北地区适应性研究

基于Fortran语言对GAMIT10.7软件进行二次开发，实现了Hopfield模型、Saastamoinen模型、Black模型、UNB3模型、EGNOS模型、GPT2w_1+Saastamoinen模型和GPT2w_5+Saastamoinen模型在中国西北地区的对流层延迟解算服务，并分析不同对流层延迟模型在西北地区的适应性问题。实验表明，在实测气象数据模型中，Saastamoinen模型在中国西北地区获取的天顶对流层延迟精度最高，各个测站平均bias值和RMS值分别是-1.67 cm、3.83 cm；Hopfield模型和Black模型精度相当。在非实测气象数据模型中，GPT2w_1+Saastamoinen模型精度最高，GPT2w_5+Saastamoinen模型次之，EGNOS模型最低。不同对流层延迟模型的精度均受季节变化影响，夏季bias的绝对值和RMS值最大，冬季最小，春季和秋季结果相当。

Research on the Adaptability of Different Tropospheric Zenith Delay Models in Northwest China

The GAMIT10.7 software is redeveloped based on the Fortran language. We use the Hopfield, Saastamoinen, Black, UNB3, EGNOS, GPT2w_1+Saastamoinen, GPT2w_5+Saastamoinen tropospheric zenith delay models to calculate the tropospheric delay in northwest China, and analyze the adaptability of different tropospheric delay models in the region. The experimental results show that in the measured meteorological data model: the Saastamoinen model the zenith tropospheric delay has the highest accuracy in northwest China. The average bias value and RMS value of each station are -1.67 cm and 3.83 cm, respectively. The Hopfield and Black models have the same accuracy. In the non-measured meteorological data models, the GPT2w_1+Saastamoinen model has the highest accuracy in obtaining the zenith tropospheric delay in northwest China, followed by the GPT2w_5+Saastamoinen model; the EGNOS model has the lowest accuracy. We find that the accuracy of different tropospheric delay models is affected by seasonality. For the seven tropospheric delay models, the absolute and RMS values of bias in summer are the greatest. The results are comparable in spring and autumn, and the absolute value of bias in winter and the RMS value is the smallest.