Real-time high-resolution tropospheric delay mapping based on GFS forecasts and GNSS

The tropospheric delay is difficult to be modeled accurately resulting from the high variability of atmospheric water vapor, especially under the conditions of sparse station distribution and large elevation differences, which poses challenges for real-time precise positioning. In this contribution, a real-time high-resolution (0.01° × 0.01°) zenith tropospheric delay (ZTD) model considering sparse stations and topography variations (named GFNSS) is established by integrating the information from the Global Forecast System (GFS) and Global Navigation Satellite System (GNSS). GNSS observations and GFS forecasts in the Hong Kong area are selected for the experiments. The performance of ZTDs derived from GFNSS is assessed and validated with the real-time GNSS ZTDs obtained by the precise point positioning method and the IGS post-processed ZTD products. Results show that the root mean square error (RMSE) of GFNSS ZTDs is 5.5 mm and 12.8 mm when validated with real-time and post-processed ZTD, while those for ZTD derived from the low-order surface model (LSM) are 8.8 mm and 19.0 mm, presenting a reduction of 37.5% and 32.6%, respectively. The sensitivity of model performance to the number of modeling stations and elevation differences is also evaluated. The results reveal that the GFNSS model is resistant to station number and presents high accuracy and stability with the RMSE values varying between 4.0 and 6.0 mm as the modeling station number decreases from 13 to 4, while the RMSE for the LSM model increases dramatically from 4.0 to 27.4 mm. Meanwhile, the GFNSS model achieves an RMSE value of 5.8 mm when the elevation differences are over 300 m, indicating a notable 84.9% reduction compared to that of LSM (RMSE of 38.5 mm).