TIGGE 자료를 이용한 2012년 12월 28일 한반도 강설사례 예측성 연구
Predictability Study of Snowfall Case over South Korea Using TIGGE Data on 28 December 2012
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참고문헌
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초록
This study compared ensemble mean and probability forecasts of snow depthamount associated with winter storm over South Korea on 28 December 2012 at five operationalforecast centers (CMA, ECMWF, NCEP, KMA, and UMKO). And cause of differencein predicted snow depth at each Ensemble Prediction System (EPS) was investigated by usingTHe Observing system Research and Predictability EXperiment (THORPEX) InteractiveGrand Global Ensemble (TIGGE) data. This snowfall event occurred due to low pressure passingthrough South Sea of Korea. Amount of 6 hr accumulated snow depth was more than 10cm over southern region of South Korea In this case study, ECMWF showed best predictionskill for the spatio-temporal distribution of snow depth. At first, ECMWF EPS has been consistentlyenhancing the indications present in ensemble mean snow depth forecasts from 7-daylead time. Secondly, its ensemble probabilities in excess of 2~5 cm/6 hour have been coincidedwith observation frequencies. And this snowfall case could be predicted from 5-day leadtime by using 10-day lag ensemble mean 6 hr accumulated snow depth distribution. In addition,the cause of good performances at ECMWF EPS in predicted snow depth amounts wasdue to outstanding prediction ability of forming inversion layer with below 0oC temperature inlow level (below 850 hPa) according to 35oN at 1-day lead time.
Abstract
This study compared ensemble mean and probability forecasts of snow depthamount associated with winter storm over South Korea on 28 December 2012 at five operationalforecast centers (CMA, ECMWF, NCEP, KMA, and UMKO). And cause of differencein predicted snow depth at each Ensemble Prediction System (EPS) was investigated by usingTHe Observing system Research and Predictability EXperiment (THORPEX) InteractiveGrand Global Ensemble (TIGGE) data. This snowfall event occurred due to low pressure passingthrough South Sea of Korea. Amount of 6 hr accumulated snow depth was more than 10cm over southern region of South Korea In this case study, ECMWF showed best predictionskill for the spatio-temporal distribution of snow depth. At first, ECMWF EPS has been consistentlyenhancing the indications present in ensemble mean snow depth forecasts from 7-daylead time. Secondly, its ensemble probabilities in excess of 2~5 cm/6 hour have been coincidedwith observation frequencies. And this snowfall case could be predicted from 5-day leadtime by using 10-day lag ensemble mean 6 hr accumulated snow depth distribution. In addition,the cause of good performances at ECMWF EPS in predicted snow depth amounts wasdue to outstanding prediction ability of forming inversion layer with below 0oC temperature inlow level (below 850 hPa) according to 35oN at 1-day lead time.
참고문헌 (24)
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