중규모 기상 모델을 이용하여 안개와 같은 미세규모 국지현상을 정확히 재현하는 것은 매우 어려운 실정이다. 특히, 수치모델의 초기 입력 자료의 불확도는 수치모델의 예측 정확도에 결정적인 영향을 미치기 때문에 이를 보완하기 위한 자료동화 과정이 요구되어진다. 본 연구에서는 WRF (Weather Research and Forecasting) 모델을 이용하여 낙동강 지역에서 발생한 여름철 안개사례 재현실험을 대상으로 중규모 기상 모델의 한계를 검증하였다. 중규모 기상 모델에서 초기 및 경계장으로 사용되는 KLAPS (Korea Local Analysis and Prediction System)와 LDAPS (Local Data Assimilation and Prediction System) 분석장 자료를 이용하여 수치모델 모의 정확도 민감도 분석을 수행하였다. 또한 AWS (Automatic Weather System) 자료를 이용한 자료동화(Four-Dimensional Data Assimilation)에 의한 수치모델의 정확도 개선 정도를 평가하였다. 초기 및 경계장 민감도 분석 결과에서 LDAPS 자료를 입력 자료로 사용한 경우가 KLAPS 자 료 보다 기온과 이슬점온도, 상대습도에서 높은 정확도를 보였고, 풍속은 더 낮은 수준을 나타내었다. 특히, 상대습도에 서 LDAPS의 경우는 RMSE (Root Mean Square Error)가 15.9%, KLAPS는 35.6%의 수준을 보여 그 차이가 매우 크 게 나타났다. 또한 자료동화를 통하여 기온, 풍속, 상대습도의 RMSE가 각각 0.3 o C, 0.2ms−1 , 2.2% 수준으로 개선되었다.

Visibility and Automatic Weather System(AWS) data near Nakdong river were analyzed to characterize fog formation during 2012-2013. The temperature was lower than its nearby city – Daegu, whereas the humidity was higher than the city. 157 fog events were observed in total during the 2 year period. About 65% of the events occurred in fall (September, October, and November) followed by winter, summer, and spring. 94 early morning fog events of longer than 30 minutes occurred when south westerly wind speed was lower than 2 m/s. During these events, the water temperature was highest followed by soil surface and air temperatures due to the advection of cold and humid air from nearby hill. The observed fog events were categorized using a fog-type classification algorithm, which used surface cooling, wind speed threshold, rate of change of air temperature and dew point temperature. As a result, frontal fog observed 6 times, radiation 4, advection 13, and evaporation 66. The evaporation fog in the study area lasted longer than other reports. It is due to the interactions of cold air drainage flow and warm surface in addition to the evaporation from the water surface. In particular, more than 60% of the evaporation fog events were accompanied with cold air flows over the wet and warm surface. Therefore, it is needed for the identification of the inland fog mechanism to evaluate the impacts of nearby topography and land cover as well as water body.

This study presents the characteristics of nocturnal inversion layer and their effect on the concentration variations of surface air pollutants using tethersonde and automatic weather station (AWS, 2 layer tower) system in Ulsan during 2003. The method for the distinction of inversion intensity was decided based on the sum of nocturnal temperature gradient. As the results, there was a close correlation (correlation coefficient of 0.76) between the maximum inversion height obtained from tethersonde and the sum of nocturnal temperature gradient. The air pollutant concentration was also directly proportional to the inversion intensity. When the inversion intensity was strong in the nighttime, ozone (O3) concentration was lower, while nitrogen dioxide (NO2) concentration was higher. The carbon monoxide (CO) concentration was gradually higher according to the nocturnal inversion intensity, whereas sulfur dioxide (SO2) concentration was relatively constant. In addition, we found that there was no correlation between the inversion intensity and TSP concentration.