Hurricane Laura (2020): A Comparison of Drop Size Distribution Moments Using Ground and Radar Remote Sensing Retrieval Methods

• Published in: Journal of geophysical research. Atmospheres 2022-08, Vol.127 (16), p.n/a
• Main Authors: Brauer, Noah S., Alford, A. Addison, Waugh, Sean M., Biggerstaff, Michael I., Carrie, Gordon D., Kirstetter, Pierre E., Basara, Jeffrey B., Dawson, Daniel T., Elmore, Kimberly L., Stevenson, Jeffrey, Moore, Robert W.
• Format: Article
• Language: English
• Subjects: cloud microphysics; disdrometer observations; polarimetric radar; precipitation processes; space‐borne radar; tropical cyclones
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1029/2021JD035845

Hurricane Laura was the strongest hurricane to make landfall in Louisiana since 1969 with maximum sustained winds of 130 knots. One University of Oklahoma Shared Atmospheric Mobile and Teaching Polarmetric Radar (SR1‐P), and four portable in situ precipitation stations (PIPSs) equipped with parsivel disdrometers were spatially and temporally collocated with two NASA Global Precipitation Measurement Mission Dual‐frequency Precipitation Radar overpasses. The combined retrieval methods were able to quantify and compare drop size distribution moments and radar‐inferred precipitation processes before, during, and after the storm center made landfall. It was found that the magnitude of collision‐coalescence dominant precipitation decreased from before to after landfall. Further, the presence of a bright‐band becomes more evident across all percentiles in the post‐landfall overpass, indicating an increase in stratiform precipitation compared to convective precipitation after Laura moved inland. The PIPS showed an increase in mean drop size from 1.0 mm before landfall to as high as 4.0 mm in the eyewall, while decreasing to below 1.0 mm as Laura continued to move inland with a decrease in maximum echo top height of 0.5–1.0 km. Last, the Dual‐frequency Precipitation Radar (DPR) algorithm overestimated the normalized intercept parameter by 0.5–1.0 m−3 mm−1 compared to the PIPS implying differences in measured drop number concentration, potentially due to differences in measurement footprint or assumptions in the DPR retrieval algorithm. These findings can potentially be used to improve the DPR particle size distribution algorithm in tropical cyclones. Plain Language Summary Understanding the dominant precipitation processes in tropical cyclones (TCs) is important for quantifying the potential for flash flooding in warning operations and improving precipitation forecasts from numerical models. Hurricane Laura (2020) provided a unique opportunity to analyze precipitation processes throughout its evolution as numerous radars and instruments were deployed in various portions of the storm. As each observational method has advantages and disadvantages, a joint analysis between all sensors allows for a direct comparison of rainfall characteristics to better understand the evolution and distribution of precipitation in landfalling TCs. The results suggest that the space‐borne radar may be overestimating rainfall concentration compared to the ground‐based instruments, and co