92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Thursday, 26 January 2012
Retrievals of Warm-Rain Microphysics Using X-Band Polarimetric Radar Data
Hall E (New Orleans Convention Center )
Matthew R. Kumjian, CIMMS/Univ. of Oklahoma and NOAA/NSSL, Norman, OK ; and A. V. Ryzhkov, S. Trömel, M. Diederich, K. Mühlbauer, and C. Simmer
Manuscript (5.6 MB)

The evolution of rain drop size distributions (DSDs) beneath cloud base are governed by three main processes: growth of large drops (and subsequent depletion of small drops) by coalescence, depletion of large drops (and increase in concentration of smaller drops) by collisional breakup, and decrease of drop sizes across the spectrum (and depletion of the smallest drops) by evaporation. In heavier rain, the collisional processes (coalescence and breakup) dominate. Though there has been much research investigating the equation governing the rain DSD and its parameterizations for numerical weather prediction models, there is a general lack of observational studies detailing the vertical evolution of DSDs.

Dual-polarization radar data can be used for microphysical retrievals of such processes, allowing for experimental quantification of the impact of these warm-rain processes on the polarimetric radar variables. For this study, high-resolution vertical cross-sections (genuine RHI scans with 0.1⁰ elevation angle spacing) were collected with the X-band dual-polarization radar in Bonn, Germany (BOXPOL) in June 2011, during a period of warm-rain convective precipitation. Vertical profiles of the polarimetric radar variables extracted from these scans are used to retrieve DSD parameters. In doing so, we can quantify changes in the retrieved DSD owing to processes such as coalescence and identify when such processes are dominant (and when they are not). Such retrievals provide experimental evidence that can be used for comparison with various models and parameterizations of the warm-rain physical processes. Additionally, they provide a basis for better understanding of how such microphysical processes affect rainfall rate beneath cloud base, which can be used to improve the accuracy of remote quantitative precipitation estimation.

Supplementary URL: