A freezing rain storm explored with a C‑band polarimetric weather radar using the QVP methodology.
On 23rd December 2012, a warm frontal atmospheric system caused significant freezing rain at the Vienna International Airport. Analyses of Austrian C‑band polarimetric weather radar data reveal cloud microphysical insights in the internal structure of such systems accompanied by the transition from...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Borntraeger
2017-04-01
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Series: | Meteorologische Zeitschrift |
Subjects: | |
Online Access: | http://dx.doi.org/10.1127/metz/2016/0807 |
Summary: | On 23rd December 2012, a warm frontal atmospheric system caused significant freezing rain at the Vienna International Airport. Analyses of Austrian C‑band polarimetric weather radar data reveal cloud microphysical insights in the internal structure of such systems accompanied by the transition from snow toward ice pellets and subsequent freezing rain and warm rain. Polarimetric radar data are exploited using a recently suggested quasi-vertical profiles (QVP) technique. This method allows to analyze the evolution of the melting layer height and other important microphysical signatures as well as the following precipitation development with high temporal and vertical resolution. Because the QVP polarimetric radar data are represented in a height vs time format which is fully compatible with the format the data from vertically pointing remote sensors such as cloud radars or wind profilers are displayed, their combined use is very efficient for understanding and monitoring microphysical processes leading to precipitation formation. This is demonstrated by the joint analysis of the polarimetric and profiler data at the Vienna airport. The QVP methodology is particularly effective for monitoring weather in the terminal areas of airports because of its local coverage and high precision as well as its potential for nowcasting. The methodology is very easy to implement and its use along with traditional techniques for weather radar data analysis using PPIs and reconstructed RHIs looks very promising. |
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ISSN: | 0941-2948 |