간행물
기후연구 KCI 등재 Journal of Climate Research
- 발행기관 건국대학교 기후연구소
- 자료유형 학술지
- 간기 계간
- ISSN 1975-6151 (Print)2288-8772 (Online)
- 수록기간 2006 ~ 2021
- 주제분류 사회과학 > 지리학 사회과학 분류의 다른 간행물
- 십진분류KDC 453DDC 551
권호리스트/논문검색
제8권 제3호 통권19호 (2013년 9월) 5건
1.
2013.09
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This study examines the relationship between urbanization rate and extreme climate indices in South Korea for the period 1981-2010. In the analysis five extreme climate indices related to air temperature and four types urbanization rates are used. In particular, this paper adopts frequency of warm nights(TN90p), intra-annual extreme temperature range(ATR), growing season length(GSL), number of frost days(FD) and heat warm spell duration indicator(HWDI) as extreme climate indices. As a measure of urbanization rate, four kinds of urbanization rate are used: (1) three urbanization rates within a radius of 1km, 5km or 10km of weather station and (2) a urbanization rate of sub-watershed where weather station is located. The trend of extreme climate indices is calculated based on Mann-Kendall trend analysis and Sen’s slope, and this trend is contrasted with urbanization rates in eleven climatic regions. The results show that TN90p, GSL, and FD have a relatively high correlation with urbanization rate. This study also shows that a urbanization rate within a radius of 1km of weather station affects GSL and FD. while a urbanization rate within 5km buffer zone of weather station affects TN90p. It is Daegwallyeong, Inje, Yangpyeong, and Hongcheon where extreme climate indices responded sensitively despite the low urbanization rates of these areas. Continual attention is needed to these areas because they are relatively sensitive to climate changes of synoptic scale.
2.
2013.09
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In this study, we developed IS-HYPS(Independent Slopes Hypsometric) method in order to complement the weakness of existing MK-PRISM (Modified Korean-Parameter-elevation Regressions an Independent Slopes Model) version 1.1, and verified the IS-HYPS by applying the method to daily temperature data for recent 11 years from 2000 to 2010. Analysis Results show that IS-HYPS method is nicely applicable in regions where elevation of target grid is high and elevation of surrounding stations are not distributed evenly. Verification results also show that RMSE (Root Mean Square Error) of IS-HYPS method is about 20 % smaller than that of MK-PRISM 1.1 (0.44°C for daily mean temperature, 0.47°C for daily maximum temperature, and 0.58°C for daily minimum temperature) and have a trend to estimate temperature lower than MK-PRISM 1.1. The favorable condition to apply the method found to be the regions where the difference in standard deviation of elevation of observation stations is larger than 70m between with and without target grid inside the searching range of radius, indicating that MK-PRISM version 2.0 can produce temperature grid data reasonably well by applying the IS-HYPS selectively to the best condition.
3.
2013.09
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This paper generated time-series temperature maps and analyzed the characteristics of temperature distributions from monthly average temperature observations between 2010 and 2011 in Jirisan areas using topographic data and geostatistics. From variogram modeling, all months except May to August showed that the spatial variability of temperature was the greatest along the direction perpendicular to coasts. Monthly temperature has negative correlations with elevation and distances from coasts and especially the correlation between temperature and distances from coasts was very weak in summer like the variogram modeling result. For temperature distribution mapping, kriging with a trend and ordinary kriging were separately applied as a univariate kriging algorithm by considering the spatial variability structures of temperature. Simple kriging with varying local means was applied as a multivariate kriging algorithm for integrating topographic data sets. From the cross validation results, the use of topographic data in spatial prediction of temperature showed the improved predictive performance, compared with univariate kriging. This improvement in predictive performance was dependent mainly on mean and variation values of monthly temperature and the spatial auto-correlation strength of residuals, as well as the correlation between topographic data and temperature. Based on these analysis results, spatial variability analysis using variogram is effectively used to account for spatial characteristics of monthly temperature and the correlation with topographic data. Topographic data can also be a useful information source for reliable temperature mapping.
4.
2013.09
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TCI(tourism climatic index) is a measure of the suitability of climate for outdoor sightseeing, which combines seven climate variables. Based on the TCI, we analyse the present climate resources for tourism in Gangwon-do and assess the recent changes. We use daily meteorological data from 11 stations in Gangwon-do. First, we compare mean annual cycles of the TCI for 5 stations(Gangneung, Sokcho, Wonju Chuncheon, and Daegwallyeong). This comparison reveals that range of the annual cycle is from minimum 35(for Daegwallyeong in January) to maximum 80(for Wonju in May and September). Daegwallyeong which is located in highland is characterized by summer season peak pattern while other regions have low TCI values in hot summer. In long-term trend of the TCI, Gangneung has increasing trends in February, April and December, whereas it has significant decreasing trends in summer and fall(June to October). In case of Daegwallyeong, increasing trends are found in February, November and December, and relatively steep declining trends in summer season. The overall decreasing trend in summer season is a common feature in Gangwon-do. Decreasing trends at Gangneung in August and September might be mostly explained by the increasing trend of rainfall amount in those months. Meanwhile, increasing trends of the TCI in winter season might be a positive impact of climate warming on the tourism sector.
5.
2013.09
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In analyzing the inundation area attributed to the sea level brought about by climate change, previous researchers derived a different inundation area from the actual one by applying a uniform sea level rise without taking into account the regional mean sea level. This study has attempted to analyze the inundation area by devising a sea-level rise scenario that considers the regional mean sea level of the study area. In addition, a comparative analysis was conducted on the area of inundation vulnerabilities between the sea level rise scenario that takes into account the regional mean sea level and one that does not. As a result of study, an error between the actual mean sea level and topographic elevation was corrected by using the height of the tide observation data of the area. Next, a total of nine scenarios on the sea level rise of the Taean region (SLR-T 1.1~SLR-T 3.3) were devised using the IPCC SRES scenario, RCP 8.5 scenario, height of the tide data and storm surge height, among others. Finally, the results showed that the inundation area by scenario was at least 4.17km2(SLR-T 1.1) up to 168.41km2(SLR-T 3.3), which was about 45% less than that of the scenario devised without considering the mean sea level that reflects the regional differences. In other words, results of the analysis on the inundation area using conventional methods turned out to be wider than that of the actual inundation area.
