HR: 10:59h
AN: SF12A-04    [Abstracts]
TI: Micro Rain Radar data visualization tool
AU: * Diederich, M
EM: malte.diederich@uni-bonn.de
AF: Meteorological Intitut University Bonn, Auf dem Hgel 20, Bonn, 53121 Germany
AU: Simmer, C
EM: csimmer@uni-bonn.de
AF: Meteorological Intitut University Bonn, Auf dem Hgel 20, Bonn, 53121 Germany
AB: We present a method for visualizing the consequences of variability in drop size distribution (DSD) of precipitation on the parameters radar reflectivity and rain rate. The displayed data are those of the Micro Rain Radar (MRR-2), which measures the vertical Doppler spectrum in multiple altitudes to estimate the DSD using the relation between drop diameter and terminal fall velocity. The relation between radar reflectivity factor Z and the rain rate R has been the subject of much research for the last 40 years since it is of central importance for the quantitative estimation of precipitation. Usual representations of occurring Z-R relations as power laws in logarithmic scatter-plots without information on temporal evolution have sometimes led to misunderstandings concerning the nature of the variability of these rain properties, as well as to misjudgements on the correct approach for Z-R approximation. Researchers have repeatedly tried to find connections between appearance of rain structures in weather radar data with Z-R relation in order to exploit spatial structure to improve quantitative precipitation estimations. The recent more versatile instrumentation for DSD measurement gives the opportunity to combine more information on precipitation structure (spatial and temporal variability, vertical reflectivity profile, occurring melting layer). The intent of the chosen representation of Z/R ratio as a function of time and rain intensity in connection with the corresponding vertical reflectivity profiles is to have a fast and easy way to understand the nature of the precipitation process as well as the implications for the quantitative measurement of rain rate with weather radar. Using the presented tool for quick visualization has been extremely useful while analyzing long periods of measurements with the desired time resolution and necessary information for rain classification. Additional available observations such as weather radar scans, disdrometer, rain gauge, or wind speed measurements may be incorporated to better understand errors and deviations from other precipitation measuring instrument.
DE: 1854 Precipitation (3354)
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 0320 Cloud physics and chemistry
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting