Collaborative Research: Studies of the Microphysical Processes in Ice and Mixed-Phase Clouds and Precipitation Using Multiparameter Radar Observations Combined with Cloud Modeling

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Winter storms cause major disruptions to transportation, commerce, the power grid and public safety. The goal of this research project is to provide better information on the properties of clouds and precipitation during winter storms so that these events can be better forecast. The researchers will use advanced radar observations, and techniques to analyze that data, to study a variety of processes in winter storms that affect the types and amount of precipitation that falls at the surface. Better predictions of snowstorms are especially important for ground and air travel and this work has connections to the relevant operational forecast agencies. In addition, students will be trained in radar meteorology techniques, ensuring the advancement of the next generation of scientists.The research team will investigate the microphysics of cold-season storms, with a focus on the use of multi-frequency, dual-polarimetric radar observations. A unique combination of state-of-the-art tools in modern weather radar technology and explicit microphysical modeling will be used to derive a better understanding of the microphysics in winter storms, including dendritic growth, riming, aggregation aloft, and processes in the melting layer. The main observational tools will be the radar facilities at Stony Brook University, which are highlighted by the Ka-band scanning radar and W- and Ku-band profiling radars. Ground measurements will include the Multi-Angle Snowflake Camera (MASC), disdrometers, and Community Collaborative Rail, Hail and Snow Network (CoCoRaHS) observations. The main objectives of the work are to: 1) Explore synergy among polarimetric, multi-frequency, and Doppler radar measurements using innovative techniques for processing and representing multi-parameter radar data to provide information about microphysical and kinematic processes in ice and mixed-phase clouds, 2) Investigate novel radar methods for quantification of ice hydrometers, and 3) Develop a 1D cloud spectral bin model combined with a forward radar operator to simulate key microphysical processes of snow formation and provide recommendations for improving the parameterization these processes in large bulk and spectral bin models.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.