Preprints
https://doi.org/10.5194/acp-2022-495
https://doi.org/10.5194/acp-2022-495
 
12 Aug 2022
12 Aug 2022
Status: this preprint is currently under review for the journal ACP.

Microphysical Characteristics of Super Typhoon Lekima (2019) and Its Impacts on Polarimetric Radar Remote Sensing of Precipitation

Yabin Gou1,2,3, Haonan Chen3, and Lulin Xue4 Yabin Gou et al.
  • 1Hangzhou Meteorological Bureau, Hangzhou 310051, China
  • 2Zhejiang Institute of Meteorological Sciences, Hangzhou 321000, China
  • 3Colorado State University, Fort Collins, CO 80523, USA
  • 4National Center for Atmospheric Research, Boulder, CO 80307, USA

Abstract. The complex precipitation microphysics associated with super typhoon Lekima (2019) and its potential impacts on the consistency of multi-source datasets and radar quantitative precipitation estimation has been disentangled using a suite of in situ and remote sensing observations around the disastrous waterlogging area near the groove windward slope (GWS) of Yan Dang Mountain and Kuo Cang Mountain, China. The dynamic microphysical processes, in which breakup overwhelms over coalescence as the main outcome of the collision of precipitation particles, noticeably changes the self-consistency between radar reflectivity (ZH), differential reflectivity (ZDR) and the specific differential phase (KDP), and their consistency with theoretical counterparts simulated with surface disdrometer measurements, which are quality-controlled in terms of fall velocity characteristics of different hydrometeors to remove wind effects, hailstones and graupels. The overwhelming breakup accounts for phenomenon that high concentration rather than size contributes more to large ZH of the storm and the large deviation of attenuation-corrected ZDR from its expected values (DR). As a result, although a comparable performance of ZH-based rainfall estimates R() and KDP-based rainfall estimates R(KDP) can be achieved, R(ZH, ZDR) tends to overestimate precipitation. R(ZH, DR) performs the best among all rainfall estimators and it is less sensitive to the potential microphysical processes, owning to the improved self-consistency between radar-measured ZH, ZDR and KDP and their consistency with surface counterparts.

Yabin Gou et al.

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Yabin Gou et al.

Yabin Gou et al.

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Short summary
This article investigates the complex precipitation microphysics associated with super typhoon Lekima (2019) using a host of in situ and remote sensing observations, including rain gauge and disdrometer data, and polarimetric radar observations. The impacts of precipitation microphysics on multi-source data consistency and radar precipitation estimation are quantified. It is concluded that the dynamical precipitation microphysical processes must be considered in radar precipitation estimation.
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