Mitigation of Radar Partial Beam Blocking in urban environmentusing statistical analysis of dual-polarization parameters

Abstract:

Mitigation of Radar Partial Beam Blocking in urban environmentusing statistical analysis of dual-polarization parameters

DaeHyung Lee1, Choeng-lyong Lee1, Geunsu Lyu1, Wonbae Bang1,Hong-Mok Park1, GyuWon Lee1 and Alexander Ryzhkov2

1 Department of Astronomy and Atmospheric Sciences, Center for Atmospheric REmote sensing,Research and Training Team for Future Creative Astrophysicists and Cosmologists,Kyungpook National University, Daegu, Korea
2Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma, USA
*Corresponding author: gyuwon@knu.ac.kr

Korea Ministry of Environment (MOE) conducts various meteorological and hydrological researches for sudden flood monitoring and forecasting in the Seoul metropolitan area. As a part of these researches, two dual polarimetric X-band radars are installed in the Seoul metropolitan area. Due to the location, severe unexpected beam blocking area appear caused by artificial buildings, trees, sidelobes effect and small terrain. In this case, traditional digital elevation model (DEM) based beam blocking simulation and rain field mask which using standard deviation of radar variables are not enough to detect partial beam blocking area. Frequency of Occurrence of Reflectivity technique (FOR) is better technique for detection ground clutter using long-term reflectivity climatology. We extend FOR to several statistical parameters (STD., AVG. and texture), dual-polarization parameters (ZDR, ρHV) and combination of dual-polarization parameter.
Traditional beam blocking simulation which is based on DEM and rain field mask are compared with FOR based beam blocking mask. To validate utilization of extended FOR, lowest available rainfall estimation results are estimated by Hybrid Surface Rainfall (HSR). Used equations for radar correction and rainfall estimation are derived from two-dimensional video disdrometer data using T-matrix simulations. Rainfall estimation results are validated with surface rain gauges within radar observation range.

Acknowledgment
This study was funded by the Korea Environmental Industry & Technology Institute (KEITI) of the Korea Ministry of Environment (MOE) as “Advanced Water Management Research Program”. (79615)