Variational Assimilation of Slant-Path Wet Delay Measurements from a Hypothetical Ground-Based GPS Network. Part I: Comparison with Precipitable Water Assimilation

With the recent advance in Global Positioning System (GPS) atmospheric sensing technology, slant wet delay along each ray path can be measured with a few millimeters accuracy. In this study, the impact of slant wet delay is assessed on the short-range prediction of a squall line. Since the current GPS observation network in the central United States is not of high enough density to capture the mesoscale variation of moisture in time and space, a set of observing system simulation experiments is performed to assimilate slant wet delay data from a hypothetical network of ground-based GPS receivers using the four-dimensional variational data assimilation technique. In the assimilation of slant wet delay data, significant changes in moisture, temperature, and wind fields within the boundary layer were found. These changes lead to a stronger surface cold front and stronger convective instability ahead of the front. Consequently, the assimilation of slant wet delay produces a considerably improved 6-h forecast of a squall line in terms of rainfall prediction and mesoscale frontal structure.