Z-R Relationships Inferred from Rain Drop Size Distributions in Different Types of Rain Systems over Gulf of Mexico Coast

This study addresses uncertainties in radar-based precipitation estimates due to variable raindrop size distributions (DSDs) across different types of precipitation systems. Utilizing observations from the Micro Rain Radar (MRR) and Parsivel disdrometer at Texas A&M University-Corpus Christi, we investigate DSD variations in major rainfall events in 2023 and 2024. Initial analysis integrates data from disdrometers and rain gauges to summarize key rain events. DSDs derived from disdrometer observations are compared with MRR-Pro retrievals to assess the validity of Z-R relationship assumptions across precipitation types, including warm rain, cold fronts, thunderstorms, and tropical systems. The caveats of this approach include saturation of reflectivity from Mie scattering of K-band radiance by large rain drops in heavy rain. However, additional information from doppler velocity may provide an opportunity to assess the DSD and improve the Z-R relationship. The findings aim to improve spaceborne radar precipitation estimates and enhance understanding of precipitation processes.