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Revision with unchanged content. In the mid/high latitudes during cold seasons, a substantial portion of precipitation falls in the form of snow. Falling snow has been one of the last great unkonwns for the hydrological water cycle and radiation budget analyses in climate and weather researches. Given their extensive spatial and temporal coverage, satellite-based remote sensing methods are uniquely suited for global snowfall observations. However, in spite of tremendous developments in meteological satellite technology over the past several decades, developing satellite remote sensing techniques to provide accurate snowfall estimations is still very challenging work. The main focus of this work is to develop a snowfall retrieval algorithm based on Bayes theorem using high frequency microwave satellite data. This study also includes analyses of various observations from surface/aircraft field experments and radiative transfer modeling considering realistic nonspherical shapes of ice/snow particles, which will be very helpful to improve our knowledge and techniques of satellite remote sesning for wintertime precipitation measurements. The book is addressed to scientists and researchers in Satellite Meteorology, Climate/Weather forecasting, and Hydrology.

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Is working on satellite precipitation measurements and ground validations as a researcher at the Cooperative Institute for Research in the Atmosphere/Colorado State University after receiving her Ph. D. degree from Florida State University in 2006.

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