Convective Meteorology (Mesoscale Dynamics)

Improved Retrieval of Hydrometeor Mixing Ratios Using Polarimetric Radar Data and the Hydrometeor Classification Algorithm for Assimilation into Storm-Scale NWP Models

Jacob Carlin
OU School of Meteorology

01 November 2013, 3:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Hydrometeor mixing ratios for rain (qr), hail (qh) and snow (qs) are typically estimated from the radar reflectivity factor Z in the process of assimilating radar data into storm-scale numerical weather prediction (NWP) models with single-moment microphysics. The existing qr,h,s – Z relations are basic and assume a Rayleigh scattering regime. In addition, overly simplistic hydrometeor classification schemes that are only functions of Z and the background temperature T are typically used to identify the hydrometeor type before applying the qr,h,s – Z formula. Double-moment microphysics schemes are generally accepted to be superior to single-moment schemes, but difficulties also exist in their implementation as they require an estimate of the concentration of the various hydrometeor types.
This study, which describes the major principles for q retrievals in convective storms containing both rain and hail, employs the benefits of polarimetric radar observations, which offer additional insight into hydrometeor shape, behavior, composition, and orientation beyond the radar reflectivity factor. A broad range of hail size distributions were considered with the intent of making these retrievals widely applicable. The retrieval procedures were developed based on the results of polarimetric radar observations in hail-bearing storms, disdrometer measurements, and simulations using a one-dimensional model of melting hail combined with a forward radar operator. The methodology for the separate estimation of qr and qh in storms containing a rain-hail mixture is also presented and discussed. In addition, results from a thunderstorm simulation run using the Hebrew University Cloud Model (HUCM) were used to study Z-q relation differences for both rain and hail among different regions within the storm as well as their temporal evolution.

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