The detailed characteristics of fog over South Korea were analyzed using the three-years quality controlled (QC) 237 visibility meter data operated by Korea Meteorological Administration. The fog (dense fog: DFog) frequency varies greatly with season and geographic location. The fog frequency at inland is highest in autumn, but at the West Coast in spring and summer. Fog occurs frequently from spring to autumn in the mountainous regions. Unlike the fog, the DFog is mostly prevalent in summer at land, mountain, and coastal regions. The large coefficients of variation of fog and DFog at the three regions and four seasons indicate that the locality of fog over South Korea is very high. The formation and dissipation (FaD) of fog show strong diurnal variations irrespective of geographic location and season, strongest at inland and weakest at sea. Fog usually occurs from night to sunrise and dissipates from early morning to late morning. The maximum FaD time of fog show seasonal variation with the seasonal change in solar elevation angle. The frequency of fog is inversely proportional to the duration time, mostly less than 3 hours regardless of season and geographic location. Also, the duration of DFog is mostly within 1-3 hours.

In order to clarify the impacts of thermal difference in atmospheric boundary layer due to the different sophistication of building information in Busan metropolitan areas, several numerical simulations were carried out. ACM (Albedo Calculation Model) and WRF (Weather Research and Forecasting) was applied for estimating albedo and meteorological elements in urban area, respectively. In comparison with coarse aggregated and small buildings, diurnal variation of albedo is highly frequent and its total value tend to be smaller in densely aggregated and tall buildings. Estimated TKE and sensible heat flux with sophisticatedly urban building parameterization is more resonable and valid values are mainly induced by urban building sophistication. The simulation results suggest that decreased albedo and increased roughness due to skyscraper plays an important role in the result of thermal change in atmospheric boundary layer.

The typical characteristics of seasonal winds were studied around the Pohang using two-stage (average linkage then k-means) clustering technique based on u- and v-component wind at 850 hpa from 2004 to 2006 (obtained the Pohang station) and a high-resolution (0.5 km grid for the finest domain) WRF-UCM model along with an up-to-date detailed land use data during the most predominant pattern in each season. The clustering analysis identified statistically distinct wind patterns (7, 4, 5, and 3 clusters) representing each spring, summer, fall, and winter. During the spring, the prevailed pattern (80 days) showed weak upper northwesterly flow and late sea-breeze. Especially at night, land-breeze developed along the shoreline was converged around Yeongil Bay. The representative pattern (92 days) in summer was weak upper southerly flow and intensified sea-breeze combined with sea surface wind. In addition, convergence zone between the large scale background flow and well-developed land-breeze was transported around inland (industrial and residential areas). The predominant wind distribution (94 days) in fall was similar to that of spring showing weak upper-level flow and distinct sea-land breeze circulation. On the other hand, the wind pattern (117 days) of high frequency in winter showed upper northwesterly and surface westerly flows, which was no change in daily wind direction.

As a pre-step research to make land-use planning in the region level, this study aims to analyze some probability pattern representing transition probabilities from farmland to others using the sequential detailed digital land-use maps. Kinki and Chubu regions of Japan, which have Osaka and Nagoya cities as their center places respectively, were selected as test regions in this study. The 10m grid land-use maps for four time series at every 5 year from 1977 to 1992 were used. In this study, the regions were divided into three sub-areas 10km, 20km, and 30km according to distance from center cities, respectively. The correlation coefficient (CC) between sub-areas with same distance in the two regions was calculated to analyze whether or not the two regions have common points in the pattern of land-use conversion probability from farmland to other types. The probability distribution of the converted areas which were moved to the urbanized area (residential, commercial, industrial, road, park and public facility areas) was about 40~70% for both all periods and sub-areas. According to distance from city centers, the probability moved to the urbanized area was about 60% at 10km area, and 40% at the 30km area, which means that the values we decreased gradually, while in the case moved to the forest and the etc areas, the values were increased slightly. The CC analysis from the paddy field and the dry field to the others separately showed that there is high correlation in the probability pattern between the two regions.