A multi-frequency approach to retrieve microphysical snowfall parameters for current and future NASA observation systems

An observation-based study will be presented that utilizes aircraft data from the 2003 Wakasa Bay AMSR Precipitation Validation Campaign to reduce uncertainties in the microwave remote sensing of frozen precipitation. Recently, significant advances have been made in the modeling of microwave scattering properties of realistic ice particles in the atmosphere, including complex aggregates of simpler “pristine” ice particles. However, few strategies have been developed to determine predominant ice crystal shapes in a given situation from radar reflectivity alone, which forces snowfall retrieval algorithms to make arbitrary assumptions about the scattering properties of the particles being measured. Recent modeling results, though, suggest that a multi-frequency approach may be key in developing a strategy to identify predominant ice crystal shape and areas of snowflake aggregation via radar reflectivity, which would provide a much-needed constraint on one of the most significant sources of uncertainty in current snowfall retrieval algorithms. To determine if the signatures predicted by these modeling results are indeed present in observations, triple-frequency radar data from Wakasa Bay will be analyzed. This analysis will provide valuable insight into the microphysics of frozen precipitation that can in turn be applied to more readily available single and dual-frequency systems and thus provide key guidance for precipitation retrieval algorithms that will be directly applicable to current and future NASA space-borne radar observation platforms such as the CloudSat, Global Precipitation Measurement (GPM), and Aerosol/Clouds/Ecosystem (ACE) missions, as well as field campaigns such as the Canadian CloudSat/CALIPSO Validation Project (C3VP) and the upcoming GCPEX (GPM Cold Season Precipitation Experiment).