Thursday, 31 August 2017
Zurich DEFG (Swissotel Chicago)
The radar rainfall estimation is usually differing from raingauge rainfall due to vertical evolution of precipitation, intrinsic difference between two measurements, different spatio-temporal representativeness. Korea Meteorological Administration (KMA) has developed the adjustment techniques of radar rainfalls based on raingauge measurements, Radar-AWS Rainrate (RAR). In order to provide the gauge-adjusted radar rainfall in real time, RAR system computes new coefficient “a” and exponent “b” in Z-R relationship based on pairs of radar rainfall and raingauge rainfall.
The performance and stability of RAR is subjected to pre-processing of raingauge rainfall. The current RAR system utilizes TRMM-GSP algorithm as pre-processing of raingauge rainfall. The temporal variation of RAR increases at the beginning and the end stages of rainfall due to artificial errors in rainfall from TRMM-GSP algorithm. In this study, we developed the new technique for raingauge process, Weather Radar Center-Rain Gauge Process (WRC-RGP), to replace the existing TRMM-GSP algorithm and improved the rainfall estimation technique by obtaining improved “a” and “b” in Z-R relationship.
For comparative evaluation of new WRC-RGP technique with TRMM-GSP algorithm, from May 2015 to October 2015, the correlation coefficients of raingauge rainfall from WRC-RGP and TRMM-GSP were 0.951 and 0.998, respectively. After applying WRC-RGP algorithm, the biases were significantly reduced from 0.82mmh-1 to 0.01mmh-1 and the root mean square errors (RMSEs) decrease from 0.71mmh-1 to 0.06mmh-1, respectively.
WRC-RGP technique leads to significant improvements of RAR system’s performance. We found that the temporal variation of coefficient “a” and exponent “b” in Z-R relation more suitable when WRC-RGP was applied. And RAR overestimations have been reduced due to stable Z-R relationship. The accuracy of RAR technique has been also improved.
In order to obtain stable and improved “a” and “b”, we will investigate the statistical characteristics of “a” and “b” of Z-R fitting curve in RAR system. We are planning to develop raingauge-adjusted technique for radar rainfall estimation of dual-polarization radar.
The performance and stability of RAR is subjected to pre-processing of raingauge rainfall. The current RAR system utilizes TRMM-GSP algorithm as pre-processing of raingauge rainfall. The temporal variation of RAR increases at the beginning and the end stages of rainfall due to artificial errors in rainfall from TRMM-GSP algorithm. In this study, we developed the new technique for raingauge process, Weather Radar Center-Rain Gauge Process (WRC-RGP), to replace the existing TRMM-GSP algorithm and improved the rainfall estimation technique by obtaining improved “a” and “b” in Z-R relationship.
For comparative evaluation of new WRC-RGP technique with TRMM-GSP algorithm, from May 2015 to October 2015, the correlation coefficients of raingauge rainfall from WRC-RGP and TRMM-GSP were 0.951 and 0.998, respectively. After applying WRC-RGP algorithm, the biases were significantly reduced from 0.82mmh-1 to 0.01mmh-1 and the root mean square errors (RMSEs) decrease from 0.71mmh-1 to 0.06mmh-1, respectively.
WRC-RGP technique leads to significant improvements of RAR system’s performance. We found that the temporal variation of coefficient “a” and exponent “b” in Z-R relation more suitable when WRC-RGP was applied. And RAR overestimations have been reduced due to stable Z-R relationship. The accuracy of RAR technique has been also improved.
In order to obtain stable and improved “a” and “b”, we will investigate the statistical characteristics of “a” and “b” of Z-R fitting curve in RAR system. We are planning to develop raingauge-adjusted technique for radar rainfall estimation of dual-polarization radar.
Acknowledgement
The research id 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.
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