[논문]동아시아 여름철 대기의 강 단기 예측성 검증

김혜인; 권예은; 백승윤; 황재영; 손석우; 박향숙; 차은정

doi:10.14191/atmos.2024.34.2.083

동아시아 여름철 대기의 강 단기 예측성 검증
Evaluation of Short-Term Prediction Skill of East Asian Summer Atmospheric Rivers 원문보기

대기 = Atmosphere, v.34 no.2, 2024년, pp.83 - 95

김혜인 (서울대학교 지구환경과학부) , 권예은 (서울대학교 지구환경과학부) , 백승윤 (서울대학교 지구환경과학부) , 황재영 (서울대학교 지구환경과학부) , 손석우 (서울대학교 지구환경과학부) , 박향숙 (국립기상과학원 예보연구부) , 차은정 (국립기상과학원 예보연구부)

Abstract ▼ AI-Helper

Atmospheric rivers (ARs) are closely related to local precipitation which can be both beneficial and destructive. Although several studies have evaluated their predictability, there is a lack of studies on East Asian ARs. This study evaluates the prediction skill of East Asian ARs in the Korean Integrated Model (KIM) for 2020~2022 summer. The spatial distribution of AR frequency in KIM is qualitatively similar to the observation but overestimated. In particular, the model errors greatly increase along the boundary of the western North Pacific subtropical high as the forecast lead time increases. When the prediction skills are quantitatively verified by computing the Anomaly Correlation Coefficient and Mean Square Skill Score, the useful prediction skill of daily AR around the Korean Peninsula is found up to 5 days. Such prediction limit is primarily set by the wind field errors with a minor contribution of moisture distribution errors. This result suggests that the improved prediction of atmospheric circulation field can improve the prediction of East Asian summer ARs and the associated precipitation.

주제어

표/그림 (10)

그림 Fig. 1. Spatial distribution of 850 hPa geopotential height (gpm, black contoured), IVTA (kg m^-1 s^-1, shaded) and ARs (purple contoured) for every 2 days from 0000 UTC June 02, 2020 to 0000 UTC June 08, 2020 from (a-d) ERA5. (e-h) Same as in (ad) but from KIM forecast at each lead time, initialized at 0000 UTC June 01, 2020.
그림 Fig. 2. Summer (JJA) climatology of the AR frequency (%, shaded) and 850 hPa geopotential height (gpm, black contoured) from (a-d) ERA5 and (e-h) KIM during 2020~2022. The forecast lead time τ is method to KIM forecasts. The red box indicates the region of South Korea (124.5º~130.5ºE, 33º~39ºN).
그림 Fig. 3. (a-d) Biases (KIM minus ERA5) and (e-h) RMSE of the AR frequency during 2020~2022 at each lead time.
그림 Fig. 4. (a) Climatology (red for KIM and blue for ERA5) and model biases (green bars) of the AR frequency averaged over the South Korea (see the box in Fig. 2a) at each lead time. (b) The RMSE of the AR frequency averaged over the South Korea at each lead time. The black dashed lines indicate the lead time when RMSE is saturated.
그림 Fig. 5. (a-d) ACC and (e-h) MSSS for the AR frequency of KIM forecasts at each lead time.
그림 Fig. 6. The ACC (red) and MSSS (blue) of the AR frequency averaged over the South Korea at each lead time. The red and blue dashed lines indicate 0.6 and 0, respectively.
그림 Fig. 9. Decomposition of IVT biases from KIM over South Korea. The blue, red, and green indicate the IVT biases by moisture, those by wind biases, and those by nonlinear interactions of moisture and wind biases, respectively.
그림 Fig. 7. Decomposition of IVT biases from KIM at 5-day forecast. (a) IVT biases by moisture. (b) IVT biases by wind biases. (c) IVT biases by nonlinear interactions of moisture and wind biases.
그림 Fig. 8. 850 hPa geopotential height (gpm, black contoured) from ERA5 (gpm, black contoured), KIM (gpm, blue contoured) and geopotential height bias (gpm, shaded) during 2020~2022.
그림 Fig. 10. Biases of (a-d) the rainfall (mm day^-1, shaded) and (e-h) the AR-related rainfall (mm day^-1, shaded) during 2020~2022 at each lead time. The observation rainfall is based on CPC daily precipitation data.

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