Development of Updateable Model Output Statistics (UMOS) System for the Daily Maximum and Minimum Temperature

An updateable model output statistics (UMOS) system for daily maximum and minimum temperature ($T_M$ and $T_m$) over South Korea based on the Canadian UMOS system were developed and validated. RDAPS (regional data assimilation and prediction system) and KWRF (Korea WRF) which have quite different physics and dynamics were used for the development of UMOS system. The 20 most frequently selected potential predictors for each season, station, and forecast projection time from the 68 potential predictors of the MOS system, were used as potential predictors of the UMOS system. The UMOS equations were developed through the weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data to ensure stable equations and a smooth transition of dependency from the old model to the new model. The UMOS equations are being updated by every 7 days. The validation results of $T_M$ and $T_m$ showed that seasonal mean bias, RMSE, and correlation coefficients for the total forecast projection times are -0.41-0.17 K, 1.80-2.46 K, and 0.80-0.97, respectively. The performance is slightly better in autumn and winter than in spring and summer. Also the performance of UMOS system are clearly dependent on location, better at the coastal region than inland area. As in the MOS system, the performance of UMOS system is degraded as the forecast day increases.

일 최고 및 최저 기온에 대한 UMOS (Updateable Model Output Statistics) 시스템 개발