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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국기상학회 Asia-Pacific Journal of Atmospheric Sciences Journal of the Korean Meteorological Society Vol.43 No.1
- 발행연도
- 2007.2
- 수록면
- 59 - 75 (17page)
이용수
초록· 키워드
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This study presents 1) the quality of snowfall-depth forecasts using MM5, and 2) the sensitivity of predicted snowfall depth to microphysics schemes as well as horizontal grid size. Numerical experiments have been carried out for 22 snowfall cases over the Korean Peninsula in order to determine the evaluation of snowfall depth forecasts as well as 2 cases for sensitivity tests. Two snow ratio algorithms are considered: 1) snow ratio as a function of surface-air temperature, SR(T, PR), and 2) snow ratio as a function of the fraction of solid precipitation, SR(S<SUB>f</SUB>). SR(S<SUB>f</SUB>) is determined by simply multiplying the average snow ratio for dry snow with the predicted fraction of solid precipitation. The results of our simulation experiments using MM5 indicate that winter precipitation over the peninsula can be predicted with some success for majority of the cases considered in this study. Correlation between predicted and observed snowfall depths is significant in general, with 17 cases showing correlation coefficients of ≥ 0.55. The forecasts for 24-h snowfall depth attempted here appear to be useful when the area of heavy snowfall is significant (e.g., heavy snowfalls measured at more than 10 stations). Snowfall depth shows relatively stronger sensitivity to microphysics schemes than precipitation, when SR(S<SUB>f</SUB>) is used. For both cases, reduction of grid size appears to have improved the predictions in general, especially over mountainous areas, but it does not necessarily improve the forecast skills.
목차
Abstract
1. Introduction
2. Model and experimental design
3. Numerical simulation of winter precipitation
4. Sensitivity of snowfall simulation to microphysics and grid size
5. Summary
Acknowledgments
REFERENCES
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