In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane’s population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.

This study is analysed on corelation between topographical conditions around 36 weather stations and climate data in South Korea. As a result of analysis, the altitude above sea level shows linear negative corelation with temperature. The low relative height sites appear that sunshine duration and temperature are the lowest and precipitation and precipitation duration are bigger than average by influences of surrounding landform. The relief amount shows high positive corelation with precipitation phenomena such as precipitation, precipitation duration and cloud amount. In terms of the aspect, southern slope sites show the highest daily minimum temperature and sunshine duration, and western slope sites show daily mean and maximum temperatures. The eastern close sites appear the lowest temperature and the highest humidity. The distance from coastline shows linear negative corelation with temperature data. The far distance sites from coastline appear that temperature, precipitation and precipitation duration are the lowest. In respect of landform structures, the piedmont areas show the highest moisture related indicators. The hill areas show the lowest humidity and cloud amount and the longest sunshine duration. Temperature and wind speed are low in basin areas.

Satellite data, with sea surface temperature(SST) by NOAA and sea level(SL) by Topex/poseidon, are used to estimate characteristics on the variations and correlations of SST and SL in the East Asian Seas from January 1993 through May 1998. We found that there are two climatic characteristics in the East Asian seas: the oceanic climate, the eastern sea of Japan, and the continental climate, the eastern sea of China, respectively. In the oceanic climate, the variations of SL have the high values in the main current of Kuroshio and the variations of SST have not the remarkable seasonal variations because of the continuos compensation of warm current by Kuroshio. In the continental climate, SL has high variations in the estuaries(the Yellow River, the Yangtze River) with the mixing the fresh water and the saline water in the coasts of continent and SST has highly the seasonal variations due to the climatic effect of continents. In the steric variations of summer, the eastern sea of Japan, the East China Sea and the western sea of Korea is increased the sea level about 10∼20㎝. But the Bohai bay in China have relatively the high values about 20∼30㎝ due to the continental climate. Generally the trends of SST and SL increased during all periods. That is say, the slopes of SST and SL is presented 0.29℃/year and 0.84㎝/year, respectively. The annual and semi-annual amplitudes have a remarkable variations in the western sea of Korea and the eastern sea of Japan. In the case of the annual peaks, there appeared mainly in the western sea of Korea and the eastern sea of Japan because of the remarkable variations of SL associated with Kuroshio. But in the case of the semi-annual peaks, there appeared in the eastern sea of Japan by the influence of current, and in the western sea of Korea by the influence of seasonal temperature, respectively. From our results, it should be believed that SST and SL gradually increase in the East Asian seas concerning to the global warming. So that, it should be requested to the international co-operation against to the change of the abnormal climate.