Abstract
Compared with the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) network, the X-band weather radar network developed by National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has greatly improved the remote sensing of weather in the lower atmosphere. Quantitative Precipitation Estimation (QPE) is one of the important goals of this meteorological radar network and it is also serving as an important tool to monitor rainfall intensity and total rainfall amount. A K <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dp</inf> -based rainfall algorithm was developed using the measurements of K <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dp</inf> values from the dual-polarization radars in CASA network to provide high spatial and temporal resolution rainfall estimates. In addition, a Fourier-space, linear system-based nowcasting method was implemented to use these rainfall estimates as input to generate short-term forecasts of rainfall. Incorporating distributed hydrological models, the high resolution precipitation estimation and nowcasting results in CASA can lead to signicant improvement in urban flood warnings and advisories resulting in substantial savings of life and property.
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