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Optimization of Z-R relationship in the summer of 2014 using a micro genetic algorithm
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 Title & Authors
Optimization of Z-R relationship in the summer of 2014 using a micro genetic algorithm
Lee, Yong Hee; Nam, Ji-Eun; Joo, Sangwon;
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The Korea Meteorological Administration has operated the Automatic Weather Stations, of the average 13 km horizontal resolution, to observe rainfall. However, an additional RADAR network also has been operated in all-weather conditions, because AWS network could not observed rainfall over the sea. In general, the rain rate is obtained by estimating the relationship between the radar reflectivity (Z) and the rainfall (R). But this empirical relationship needs to be optimized on the rainfall over the Korean peninsula. This study was carried out to optimize the Z-R relationship in the summer of 2014 using a parallel Micro Genetic Algorithm. The optimized Z-R relationship, , using a micro genetic algorithm was different from the various Z-R relationships that have been previously used. However, the landscape of the fitness function found in this study looked like a flat plateau. So there was a limit to the fine estimation including the complex development and decay processes of precipitation between the ground and an altitude of 1.5km.
Micro genetic algorithm;Z-R relationship;Quantitative precipitation estimation;RADAR rain-rate;
 Cited by
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