Investigating the Optimal Spatial Resolution for Assimilating GNSS PWV Into an NWP System to Improve the Accuracy of Humidity Field

Abstract

Over the past few decades, the ground-based global navigation satellite systems (GNSSs) tropospheric sounding technique has undergone rapid development and has proven to be highly effective in sensing atmospheric variables. Through the utilization of the maturing data assimilation technique, GNSS products, e.g., precipitable water vapor (PWV), can be effectively integrated into a numerical weather prediction (NWP) model, thereby significantly bolstering its performance. In this study, to further refine this practice, a comprehensive investigation of the optimal spatial resolutions for assimilating near real-time PWV into the Weather Research and Forecasting model to improve the accuracy of atmospheric humidity field was conducted under different weather conditions in the context of Victoria, Australia. Results revealed that the optimal spatial resolutions under the heavy rainfall and normal conditions were 46.40 and 55.10 km, respectively. Therefore, the overall optimal spatial resolution for assimilating PWV was ultimately determined as 46.40 km, which can capture the necessary details and improve the accuracy of humidity field across different weather scenarios. Specifically, by incorporating PWV into an NWP model using the optimal spatial resolution, the accuracy of atmospheric humidity fields under the heavy rainfall and normal conditions were significantly improved by 26.0% and 24.7%, respectively. Therefore, the findings have considerable implications for further advancing the assimilation technique and offer valuable insights for the construction and deployment of GNSS ground infrastructure in future scenarios.

Keywords

• Data assimilation
• global navigation satellite systems (GNSSs)
• humidity field
• precipitable water vapor (PWV)
• spatial resolution
• weather research and forecasting model