Past-time Radar Rainfall Estimates using Radar AWS Rainrate system with Local Gauge Correction method

Abstract:

The Weather Radar Center at Korea Meteorological Administration (KMA) has radar network for warnings for heavy rainfall and severe storms. We have been operating an operational real-time adjusted the Radar-Automatic Weather Station (AWS) Rainrate (RAR) system developed by KMA in 2006 for providing radar-based quantitative precipitation estimation (QPE) to meteorologists. This system has several uncertainty in estimating precipitation by radar reflectivity (Z) and rainfall intensity (R) relationship. To overcome uncertainty of the RAR system and improve the accuracy of QPE, we are applied the Local Gauge Correction (LGC) method which uses geo-statistical effective radius of errors of the QPE to RAR system in 2012. According to the results of previous study in 2014 (Lee et al., 2014), the accuracy of the RAR system with LGC method improved about 7.69% than before in the summer season of 2012 (from June to August). It has also improved the accuracy of hydrograph when we examined the accuracy of flood simulation using hydrologic model and data derived by the RAR system with LGC method. We confirmed to have its effectiveness through these results after the application of LGC method. It is required for high quality data of long term to utilize in hydrology field. To provide QPE data more precisely and collect past-time data, we produce that calculated by the RAR system with LGC method in the summer season from 2006 to 2009 and investigate whether the accuracy of past-time radar rainfall estimation enhance or not.

Keywords : Radar-AWS Rainrate system, Local gauge correction, past-time Radar rainfall estimation

Acknowledgements : This research is supported by "Development and application of Cross governmental dual-pol radar harmonization (WRC-2013-A-1)" project of the Weather Radar Center, Korea Meteorological Administration in 2015.