2025/09/30 by Thundathil, Rohith, Zus, Florian, Dick, Galina +1
Earth and Planetary Sciences · Engineering · Environmental Science · #500 Naturwissenschaften und Mathematik::550 Geowissenschaften #GNSS data assimilation #GNSS positioning and interference #Geologie::550 Geowissenschaften #Meteorological Phenomena and Simulations #Soil Moisture and Remote Sensing #ZTD #network density sensitivity #numerical weather prediction #tropospheric gradients #weather forecasting #zenith total delay
paper · doi:10.14279/depositonce-24701
openalex publication_date 2025/09/30 · openalex created_date 2025/11/11 · openalex updated_date 2026/07/01
The assimilation of global navigation satellite system (GNSS) zenith total delays (ZTDs) into numerical weather models improves weather forecasts. In addition, the GNSS tropospheric gradient (TG) estimates provide valuable insight into the moisture distribution in the lower troposphere. In this study, we utilize a newly developed forward operator for TGs to investigate the sensitivity effects of incorporating TGs into the Weather Research and Forecasting model at varying station network densities. We assimilated ZTD and TGs from dense and sparse station networks (0.5 and 1°, respectively). Through this study, we found that the improvement in the humidity field with the assimilation of ZTD and TGs from the sparse station network (1° resolution) is comparable to the improvement achieved by assimilating ZTD only from the dense station network (0.5° resolution). These results encourage the assimilation of TGs alongside ZTDs in operational weather forecasting agencies, especially in regions with few GNSS stations. Conversely, assimilating TGs alongside ZTDs from sparse GNSS networks can be a cost-effective way to enhance the accuracy of the model fields and subsequent forecast quality.