기상청 기후예측시스템(GloSea6) 과거기후 예측장의앙상블 확대와 초기시간 변화에 따른 예측 특성 분석
Assessment of the Prediction Derived from Larger Ensemble Size and Different Initial Dates in GloSea6 Hindcast
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In this paper, the evaluation of the performance of Korea Meteorological Administratio(KMA) Global Seasonal forecasting system version 6 (GloSea6) is presented by assessingthe effects of larger ensemble size and carrying out the test using different initial conditionsfor hindcast in sub-seasonal to seasonal scales. The number of ensemble members increasesfrom 3 to 7. The Ratio of Predictable Components (RPC) approaches the appropriate signalmagnitude with increase of ensemble size. The improvement of annual variability is shown forall basic variables mainly in mid-high latitude. Over the East Asia region, there are enhancementsespecially in 500 hPa geopotential height and 850 hPa wind fields. It reveals possibilityto improve the performance of East Asian monsoon. Also, the reliability tends to become betteras the ensemble size increases in summer than winter. To assess the effects of using differentinitial conditions, the area-mean values of normalized bias and correlation coefficients are comparedfor each basic variable for hindcast according to the four initial dates. The results havebetter performance when the initial date closest to the forecasting time is used in summer. Onthe seasonal scale, it is better to use four initial dates, where the maximum size of the ensembleincreases to 672, mainly in winter. As the use of larger ensemble size, therefore, it is mostefficient to use two initial dates for 60-days prediction and four initial dates for 6-months prediction,similar to the current Time-Lagged ensemble method.
Abstract
In this paper, the evaluation of the performance of Korea Meteorological Administratio(KMA) Global Seasonal forecasting system version 6 (GloSea6) is presented by assessingthe effects of larger ensemble size and carrying out the test using different initial conditionsfor hindcast in sub-seasonal to seasonal scales. The number of ensemble members increasesfrom 3 to 7. The Ratio of Predictable Components (RPC) approaches the appropriate signalmagnitude with increase of ensemble size. The improvement of annual variability is shown forall basic variables mainly in mid-high latitude. Over the East Asia region, there are enhancementsespecially in 500 hPa geopotential height and 850 hPa wind fields. It reveals possibilityto improve the performance of East Asian monsoon. Also, the reliability tends to become betteras the ensemble size increases in summer than winter. To assess the effects of using differentinitial conditions, the area-mean values of normalized bias and correlation coefficients are comparedfor each basic variable for hindcast according to the four initial dates. The results havebetter performance when the initial date closest to the forecasting time is used in summer. Onthe seasonal scale, it is better to use four initial dates, where the maximum size of the ensembleincreases to 672, mainly in winter. As the use of larger ensemble size, therefore, it is mostefficient to use two initial dates for 60-days prediction and four initial dates for 6-months prediction,similar to the current Time-Lagged ensemble method.
참고문헌 (23)
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