Second Annual AMS Student Conference


Estimating Snowfall Rates Uising Polarimetric Radar Data

Yarice Rodriguez, University of Illinois and UCAR/NCAR/SOARS, Urbana, IL

Using radar data to estimate snowfall rates is of great interest in regions of rough terrain. Snowfall rates can provide information on potential flood hazards, water resource problems, and aid in agricultural planning. Several attempts have been made estimating snowfall rates using radar data, but a sufficient method is not available. Therefore, in this study a technique is developed using polarimetric radar data to estimate snowfall from data recorded during the Mesoscale Alpine Programme (MAP).

MAP is a field experiment that took place in Northern Italy and whose goal was to understand heavy precipitation events including flash-floods. Data was collected remotely by S-Pol, which is the National Center for Atmospheric Research (NCAR) ground based S-Band dual linear switchable polarization radar with copolar and cross-polar components, plus NCAR's in-situ particle measuring system probes mounted on the Electra aircraft.

This study attempts to find a correlation between polarimetric variables and snowfall rates. In-situ aircraft data provides information on hydrometeor size, shape, and concentration. To estimate hydrometeor density and fall velocity, the aircraft data has to be compared to polarimetric information from S-Pol. For this purpose, it is important to create and validate a matching program that correlates points between aircraft flight tracks and radar scans. Such matching was realized for the first time among the scientific community at NCAR. This study will utilize this matching program to provide hydrometeor concentration, density, and fall velocity in a cloud, and thus determine snowfall rate.

Poster Session 5, Observations/Remote Sensing
Sunday, 9 February 2003, 5:30 PM-7:30 PM

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