长三角地区GNSS大气水汽转换系数模型精化研究

根据长三角地区7个探空站基于积分法计算的2016年大气水汽转换系数（K值），利用多元线性拟合分别构建不顾及高程的Emardson-I精化模型和顾及高程的Emardson-H精化模型，并用2017年的K值验证两种模型的精度。实验结果表明，Emardson-H预报模型的MAE和RMS分别为0.001 297和0.001 616，略优于Emardson-I预报模型的0.001 303和0.001 620；基于两种新模型的GNSS-PWV反演精度相当，其MAE和RMS均优于0.6 mm。因此，Emardson-I模型以其无需实测气象参数和无需顾及高程在长三角地区的地基GNSS气象学实时应用中具有更好的效率优势。

Model Refinement of GNSS Atmospheric Water VaporConversion Coefficient in Yangtze River Delta

The atmospheric water vapor conversion coefficient (K) is one of the key parameters affecting the precision of GNSS precipitable water vapor (GNSS-PWV) inversed from ground-based GNSS meteorology. Based on the data from 7 radiosonde stations in the Yangtze river delta, we calculate the K values from 2016 by numerical integration and use a multivariate linear fitting method to establish two new models. One model is elevation independent (Emardson-I), and the other one is elevation dependent (Emardson-H). Finally, we validate these two new models using K values from 2017. The experimental results show that the MAE and RMS of the Emardson-H forecasting model are 0.001 297 and 0.001 616, which are slightly better than the Emardson-I forecasting model (0.001 303 and 0.001 620 respectively). GNSS-PWV inversion precisions of the two models are equivalent, and their MAE and RMS are both better than 0.6 mm. Therefore, as for the GNSS-PWV inversion in Yangtze river delta, Emardson-I model has better efficiency advantages in real-time application of ground-based GNSS meteorology as there is no need to measure meteorological parameters and elevation.