• 한국환경과학회지
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• 제29권1호
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• pp.1-13
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• 2020

Recently, a heavy rainfall with high spatial variation occurred frequently in the Korean Peninsula. The meteorological event that occurred in Busan on 3 May 2016 is characterized by heavy rain in a limited area. In order to clarify the reason of large spatial variation associated with mountain height and location of low level jet, several numerical experiments were carried out using the dynamic meteorological Weather Research and Forecasting (WRF) model. In this case study, the raised topography of Mount Geumjeong increased a barrier effect and air uplifting due to topographic forcing on the windward side. As a result, wind speed reduced and precipitation increased. In contrast, on the downwind side, the wind speed was slightly faster and since the total amount of water vapor is limited, the precipitation on the downwind side reduced. Numerical experiments on shifting the location of the lower jet demonstrated that if the lower jet is close to the mountain, its core becomes higher due to the effect of friction. Additionally, the water vapor convergence around the mountain increased and eventually the precipitation also increased in the area near the mountain. Hence, the location information of the lower jet is an important factor for accurately predicting precipitation.

• 대기
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• 제18권4호
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• pp.299-316
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• 2008

The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.