New ZTD estimation model for areas with large elevation differences by integrating the GFS with GNSS

Abstract The Global Forecast System (GFS) of the National Center for Environmental Prediction (NCEP) can produce an hourly forecast output for estimating zenith tropospheric delay (ZTD) at any altitude on grid points. This study proposes a new ZTD estimation model for areas with large elevation differences by integrating GFS forecasts with global navigation satellite system (GNSS) observations. First, the vertical variation characteristic of ZTD is modeled using an exponential function based on GFS forecasts. Subsequently, the extreme gradient boosting (XGBoost) method is applied to calibrate the remaining GFS ZTD residuals using GNSS observations, establishing a mapping relationship between GFS ZTD residuals and GNSS ZTD residuals. By combining the exponential function model with the pre-trained XGBoost model, high-accuracy ZTD forecasts can be achieved. The Yunnan Province in China was selected as a typical area with large elevation differences for experiments. GFS forecasts and GNSS ZTD products at 26 stations of the Crustal Movement Observation Network of China (CMONOC) were used as training data, while 130 GNSS stations from the continuously operating reference stations (CORS) network were used for verification. Results showed that separating the vertical variation characteristic of ZTD can improve the accuracy of the established XGBoost model by approximately 54.96%. Compared with GFS ZTD forecasts and the generalized regression neural network (GRNN) model, the accuracy of ZTD derived from the proposed model was improved by approximately 39.42% and 8.71%, respectively. Meanwhile, the accuracy of the proposed model remains stable across different times of the day and altitude ranges. For areas with few CMONOC stations participating in training, our proposed model also demonstrates good performance. These results verify that GFS forecasts and GNSS observations can complement each other to achieve high-accuracy ZTD forecasts in areas with large elevation differences, which is also important for real-time GNSS applications.