J5.3 3DVAR Retrieval of 3D Moisture Field from Slant-path Water Vapor Observations of a High-resolution Hypothetical GPS Network

*It is very important to accurately characterize the three-dimensional distribution of water vapor in the atmosphere for the understanding and prediction of mesoscale and storm-scale weather, especially with regard to quantitative precipitation forecasting (Emanuel et al. 1995). Skills in these predictions have been improved rather slowly owing to the high spatial and temporal variability of water vapor. Thus, high resolution observations of three-dimensional water vapor should have capability to improve the prediction of precipitation and severe weather. In recent years, spacedand ground-based Global Positioning Systems (GPS) have been developed and become an important instrument that can potentially provide water vapor measurements with high resolution under virtually all weather conditions. Integrated water vapor can be derived from wet signal delay along each slant path between a GPS satellite in view and a ground-based receiver. This water vapor is called slant water vapor with an accuracy of a few millimeters (Braun et al. 2001). Most importantly, slant water vapor can provide vertical structure information of atmospheric moisture. In the recent years, encouraged by the potential of GPS water vapor sensing, researchers have begun the studies on the impact of GPS water vapor observations on short-range forecasting of convective weather. Kuo et al (1996), Guo et al (2000) and Ha et al (2002), using a 4DVAR system, identified positive impact of assimilating GPS water vapor data into mesoscale models on prediction. MacDonald et al (2002) demonstrated through Observing System Simulation Experiments (OSSE) and 3DVAR (three dimensional variational) analysis that a highresolution network of GPS receivers can recover the moisture field from the slant integrated water vapor. In their analysis, the integrated slant water vapor measurements are combined with the surface mois-