A Quantification Method for the Cold Pool Effect on Nocturnal Temperature in a Closed Catchment

Cold air on sloping surfaces flows down to the valley bottom in mountainous terrain at calm and clear nights. Based on the assumption that the cold air flow may be the same as the water flow, current models estimate temperature drop by regarding the cold air accumulation at a given location as the water-like free drainage. At a closed catchment whose outlet is blocked by man-made obstacles such as banks and roads, however, the water-like free drainage assumption is no longer valid because the cold air accumulates from the bottom first. We developed an empirical model to estimate quantitatively the effect of cold pool on nocturnal temperature in a closed catchment. In our model, a closed catchment is treated like a "vessel", and a digital elevation model (DEM) was used to calculate the maximum capacity of the cold pool formed in a closed catchment. We introduce a topographical variable named "shape factor", which is the ratio of the cold air accumulation potential across the whole catchment area to the maximum capacity of the cold pool to describe the relative size of temperature drop at a wider range of catchment shapes. The shape factor is then used to simulate the density profile of cold pool formed in a given catchment based on a hypsometric equation. The cold lake module was incorporated with the existing model (i.e., Chung et al., 2006), generating a new model and predicting distribution of minimum temperature over closed catchments. We applied this model to Akyang valley (i.e., a typical closed catchment of 53 $km^2$ area) in the southern skirt of Mt. Jiri National Park where 12 automated weather stations (AWS) are operational. The performance of the model was evaluated based on the feasibility of delineating the temperature pattern accurately at cold pool forming at night. Overall, the model's ability of simulating the spatial pattern of lower temperature were improved especially at the valley bottom, showing a similar pattern of the estimated temperature with that of thermal images obtained across the valley at dawn (0520 to 0600 local standard time) of 17 May 2011. Error in temperature estimation, calculated with the root mean square error using the 10 low-lying AWSs, was substantially decreased from $1.30^{\circ}C$ with the existing model to $0.71^{\circ}C$ with the new model. These results suggest the feasibility of the new method in predicting the site-specific freeze and frost warning at a closed catchment.

폐쇄집수역의 냉기호 모의를 통한 일 최저기온 분포 추정

본 연구에서는 폐쇄집수역의 냉기호 현상을 기존의 냉기집적효과와 연계하여 일 최저기온 분포를 모의할 수 있는 방법을 제시하였다. 집수역 내 찬 공기가 담길 '그릇'의 용적을 계산하고 '그릇'안에 집적되는 냉기량을 고도에 따라 표현하였다. 기존의 계곡지형 냉기류에 냉기호를 합산하여 냉기집적으로 인한 기온하강분을 계산하였다. 이때 냉기호의 '수면'은 일교차 조건에 따라 변화시켰다. 이 방법을 검증하기 위해 경남 하동군 악양계곡의 200m 이하 냉기호 형성지역에 기상관측기 10대에서 1분 단위로 기온을 측정하였다. 5월 17일 새벽에는 형제봉 정상에서 적외선 영상 복사계로 지면온도분포를 획득하였다. 개선된 소기후 모형을 적용하여 0530 LST의 기온 분포를 30m 해상도로 추정한 결과 그 양상이 적외선 열영상 분포와 유사하였다. 10개 기상관측지점에 해당하는 격자의 기온추정값을 추출하여 실측값과 비교한 결과, MAE는 1.01에서 0.60으로, RMSE 1.30에서 0.71으로 감소하여 집수역 출구에 가까운 저지대 평야부분에서 발생하는 기존 방법에 의한 오차가 개선되었다.