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This paper assesses the impact on short-range quantitative precipitation forecasts (QPFs) of assimilating zenith total delay (ZTD) and rainfall observations associated with a winter storm that occurred from 5-6 December 1997 in southern California. Assimilation of hourly rainfall improves the threat score by more than 300% within the assimilation window, but such an improvement drops quickly to 30% or lower beyond this window. The assimilation of ZTD observations does not produce a rainfall distribution as close to the observations as does the assimilation of rainfall within the assimilation window (only a 34% improvement). However, improvement in the QPFs beyond the window from the ZTD experiment is comparable to that from the rainfall experiment. Assimilation of ZTD and rainfall observations modifies the thermodynamic structures of the atmosphere, favoring development of precipitation in the observed rainy areas. The horizontal and vertical wind velocities are also adjusted consistent with the precipitation process. A spectral analysis of observed and simulated hourly rainfall, as well as the model forecast difference with and without data assimilation, indicates that rainfall assimilation adjusts the model variables on smaller scales (25 to 50 km) while the ZTD assimilation adjusts the model variables mainly on larger scales (> 50 km).

Impact on Short-Range Precipitation Forecasts from Assimilation of Ground-Based GPS Zenith Total Delay and Rain Gauge Precipitation Observations