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Analysis of low level cloud prediction in the KMA Local Data Assimilation and Prediction System(LDAPS)

기상청 국지예보모델의 저고도 구름 예측 분석

  • Received : 2017.11.25
  • Accepted : 2017.12.29
  • Published : 2017.12.31

Abstract

Clouds are an important factor in aircraft flight. In particular, a significant impact on small aircraft flying at low altitude. Therefore, we have verified and characterized the low level cloud prediction data of the Unified Model(UM) - based Local Data Assimilation and Prediction System(LDAPS) operated by KMA in order to develop cloud forecasting service and contents important for safety of low-altitude aircraft flight. As a result of the low level cloud test for seven airports in Korea, a high correlation coefficient of 0.4 ~ 0.7 was obtained for 0-36 leading time. Also, we found that the prediction performance does not decrease as the lead time increases. Based on the results of this study, it is expected that model-based forecasting data for low-altitude aviation meteorology services can be produced.

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References

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