• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.37-55
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• 2013

Previous studies have shown that Foehn was mainly observed in Young-seo area in Korea. However, they have failed to indicate the area where Foehn can be observed most frequently in Young-seo area and how Foehn is distributed in that area. This study targets HongCheon area in Young-seo province and examines the frequency and extent of Foehn in local scale through documenting a daily maximum air temperature map of Foehn. The period examined in this study is the months between March and June from 2003 to 2012. CoKriging method, which uses temperature and the altitude above sea, generates a higher level of accuracy in making daily maximum air temperature map of Foehn occurring days. We have found that Foehn is observed in certain areas, not all areas of HongCheon region, by compiling the daily maximum air temperature map. In particular, Foehn was found to be frequent and strong in the downstream of HongCheon river. In addition, we surveyed the residents of HongCheon about their perception of Foehn. They did not know whether high temperature and dryness in spring are caused by Foehn. The methods and techniques used to examine Foehn in local climate scale by this study will enhance the understanding of regional climate and contribute towards the research in this area. In particular, they can be applied to high temperature that recently occurred between spring and summer, excessive hotness in summers, agricultural plant growth in springs and etc.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.519-527
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• 2021

Background and objective: This study was conducted to establish a Plant Hardiness Zone (PHZ) map, investigate the effect of global warming on changes in PHZ, and elucidate the difference in the distribution of evergreen trees between the central and southern region within hardiness Zone 7b in Korea. Methods: Mean annual extreme minimum temperature (EMT) and related temperature fluctuation data for 40 years (1981 to 2020) in each of the meteorological observation points were extracted from the Open MET Data Portal of the Korea Meteorological Administration. Using EMT data from 60 meteorological observation points, PHZs were classified according to temperature range in the USDA Plant Hardiness Zone Map. Changes in PHZs for each decade related to the effects of global warming were analyzed. Temperature fluctuation before and after the day of EMT were analyzed for 4 areas of Seoul, Suwon, Suncheon, and Jinju falling under Zone 7b. For statistical analysis, descriptive statistics and ANOVA were performed using the IBM SPSS 22 Statistics software package. Results: Plant hardiness zones in Korea ranged from 6a to 9b. Over four decades, changes to warmer PHZ occurred in 10 areas, especially in colder ones. Based on the analysis of daily temperature fluctuation, the duration of sub-zero temperatures was at least 2 days in Seoul and Suwon, while daily maximum temperatures were above zero in Suncheon and Jinju before and after EMT day. Conclusion: It was found that the duration of sub-zero temperatures in a given area is an important factor affecting the distribution of evergreen trees in PHZ 7b.

• Journal of Korean Society of Forest Science
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• v.81 no.1
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• pp.40-52
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• 1992

The use of meteorological information is essential in the industrial society. More specialized weather services are required to perform better industrial activities including forestry. A topoclimatological technique, in this study, which makes use of empirical relationships between the topography and the weather in Cheju Island was applied to produce reasonable estimates of monthly air temperatures over remote land area where routine observations are rare. Altitude values of the 250m grid points were first read from a 1 : 25000 topographic map. The mean altitude and other valuable topographical variables were then determined for each $1km^2$ land area. Daily minimum, maximum and mean air temperature data were collected from 19 points in Cheju Island from June 1987 to September 1988. The data were analyzed and grouped into 36 sets by type of air temperature and by month. Each of data set was regressed to the topographical variables to delineate empirical relationships between the local air temperature and the site topography. The total of 36 regression equations were finally selected and the equations were used to calculate the monthly air temperature for each $1km^2$ land area. The outputs were presented in a fine-mesh grid map with a 6-level contour capability.