일 최고 및 최저 기온에 대한 UMOS (Updateable Model Output Statistics) 시스템 개발
Development of Updateable Model Output Statistics (UMOS) System for the Daily Maximum and Minimum Temperature
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초록
An updateable model output statistics (UMOS) system for daily maximum and minimum temperature (TM and Tm) 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 TM and Tm 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.
Abstract
An updateable model output statistics (UMOS) system for daily maximum and minimum temperature (TM and Tm) 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 TM and Tm 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.
참고문헌 (17)
- MOS 기온예보모델 개발 및 현업 운영체계, "서영경", 기상청 디지털예보개발과, 189~, pp.DFS-TN-2006-5 (2006)
- 이민영, "칼만필터를 이용한 최고", 최저 기온 예보, 1999, pp.35(2), 283~289
- 이우진, "컴퓨터와 날씨예측", pp.284~ (2006), 광교이택스
- 통계적 방법을 이용한 최고, "최저 기온예보법", 조주영, 1993, TR93-1
- Caren, M., "Ceiling and visibility forecasts via neural networks", Wea. Forecasting, 22, pp.466~479 (2007)
- Glahn, H. R., "The use of model output statistics (MOS) in objective forecasting", J. Appl. Meteorol., 11, pp.1203~1211 (1972)
- MOS-2000, "Glahn, H. R.", NOAA, 2000, pp.169~, TDL office note 00-1
- Glahn, H. R., "The new digital forecast database of the National Weather Service", Bull. Amer. Meteor. Soc., 84, pp.195~201 (2003)
- Jacks, E., "New NGM-based MOS guidance for maximum", minimum temperature, probability of precipitation, cloud amount, and surface wind, 1990, pp.5, 128~138
- Kenneth A. H., "An evaluation of mesoscale-model-based model output statistics (MOS) during the 2002 Olympic and Paralympic winter games", Wea. Forecasting, 19, pp.200~218 (2002)
- Parvinder, M., "Forecasting maximum and minimum temperatures by statistical interpretation of numerical weather prediction model output", Wea. Forecasting, 18, pp.938~952 (2003)
- An updateable model output statistics scheme. World Meteorological Organization, Programme on short- and medium range weather prediction, "Ross, G. H.", PSMP, 45~48, pp.No. 25 (1987)
- Ross, G. H., "Model output statistics - an updateable scheme", Preprints of the 11th Conference on Probability and Statistics in Atmospheric Sciences, pp.93~97 (1989)
- William Y., "Strengths and weaknesses of MOS, running-mean bias removal, and Kalman filter techniques for improving model forecasts over the Western United States", Wea. Forecasting, 22, pp.1304~1318 (2007)
- Wilson, A. J., "The Canadian updateable model output statistics (UMOS) system: Design and development tests", Wea. Forecasting, 17, pp.206~222 (2002)
- Wilson, A. J., "The Canadian updateable model output statistics (UMOS) system: Validation against perfect prog", Wea. Forecasting, 18, pp.288~302 (2003)
- Zwiers, F. W., "On the role of statistics in climate research", Int. J. Climatol., 24, pp.665~680 (2004)