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
제13권 제4호 (2018년 12월) 7건
1.
2018.12
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This paper has identified detailed climate types and their geographical extents in the Republic of Korea using MK (Modified Korean)-PRISM (Parameter-elevation Regression on Independent Slopes Model) 1×1km high-resolution grid climate data and Trewartha climate classification. When considering 60 ASOS (The Automated Synoptic Observing Systems) stations, only four climate types were identified over South Korea. Three climate types, Dca (52%), Doa (28%) and Cfa (18%), were prevalent while Dcb type was only located at Daegwallyeong. When based on a high-resolution grid climate data, six climate types were identified including Dob and E types which were not detected with ASOS stations. High-resolution grid climate data reflected better and detailed geographical characteristics. Areas occupied by Cfa climate types were located along the narrow southern and Jeju coastal areas, dedicating only 6.9% of South Korea. Trewartha climate classification was also applied to 1km×1km RCP scenarios. The most distinct feature of future climate changes based on RCPs was a larger expansion of Cfa and Doa types with a drastic reduction of Dca and Dcb, indicating that a warmer and wetter climate would be prevalent over South Korea in the latter period of this century. Even for RCP2.6, all the coastal areas, some of Seoul metropolitan area, a large part of Daegu and Gwangju metropolitan areas would be classified as Cfa. For RCP8.5, 51.5% of South Korea would be occupied by the Cfas and 25.1% by the Doas, leaving only 23.2% of Dcas.
2.
2018.12
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In this study, uncertainty ranges for bias-corrected temperature and precipitation in seven metro-cities were estimated using nine GCM-RCM Matrix, and climate changes were predicted based on the corrected temperature and precipitation. During the present climate (1981-2005), both uncertainties for annual temperature and precipitation and differences in regional uncertainties were reduced by bias correction methods. Model’s systematic errors such as cold bias of surface air temperature and underestimated precipitation during the second-Changma period were improved by a bias correction method. Uncertainties of annual variations for bias corrected temperature and precipitation were also decrease. Furthermore, not only mean values but also extreme values were improved by bias correction methods. During the future climate (2021-2050), differences in temperature and precipitation between two RCP scenarios (RCP4.5/8.5) were not quite large. Temperature had an obvious increasing tendency, while future precipitation did not change significantly compared to present one in terms of mean values. Uncertainties for future biascorrected temperature and precipitation were also reduced. In mid-21st centuries, models prospected that mean temperature increased thus lower extremes associated with cold wave decreased and upper extremes associated with heat wave increased. Models also predicted that variations of future precipitation increased thus the frequency and intensity of extreme precipitation increased.
3.
2018.12
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Drought is one of the natural disasters that slowly begin to accumulate over a long period. Although there are many kinds of drought indices, one single universally accepted definition does not currently exist, which makes it difficult to evaluate drought severity comprehensively and objectively. This paper describes the comparisons of satellite-based drought indices such as SPI (Standardized Precipitation Index), NDDI (Normalized Difference Drought Index), NMDI (Normalized Multi-band Drought Index), VHI (Vegetation Health Index) and SDCI (Scaled Drought Condition Index) to analyze agricultural drought in Korea. Through an experiment using the five drought indices, we found that VHI and the SPI2 calculated from 2-month accumulated precipitation were highly correlated and appropriate to express agricultural drought in South and North Korea. Also, the SPI2 and VHI showed close relationships with hydro-meteorological factors and vegetation production variables. For future work, it is necessary to develop a comprehensive drought index which can cover various aspects of drought including precipitation, evapotranspiration, soil moisture, and vegetation state.
4.
2018.12
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In this study, we identified heavy rain damage and rainfall characteristics for each region, and proposed Hazard-Triggering rainfall according to heavy rain damage scale focused on Gyeonggi-do. We classified the damage scale into three groups (total damage, over 100 million won, over 1 billion won) to identify the characteristics of heavy rain damage, and we determined criteria of the rainfall class for each rainfall variable (maximum rainfalls for the durations of 1, 3, 6, 12 hours) to identify the rainfall characteristics. We calculated the cumulative probability of heavy rain damage based on the rain criteria mentioned above to establish the Hazard-Triggering rainfall according to the heavy rainfall damage scale. Using the results, we establish the Hazard-Triggering rainfall for each rain variable according to heavy rain damage. Finally, this study calculated the assessment indicator (F1-Score) for classification performance to test the performance of the Hazard-Triggering rainfall. As the results, the classification performance of the Hazard-Triggering rainfall which proposed in this study was 11%, 30%, 10% higher than the criteria by KMA (Korea Meteorological Administration).
5.
2018.12
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A Quantile-based Matching (QM) method has been widely used to correct the biases in global and regional climate model outputs. The basic idea of QM is to adjust the Cumulative Distribution Function (CDF) of model for the projection period on the basis of the difference between the model and observation CDFs for the training period. Therefore, the CDF of observation on training period plays an important role in quantile-based matching. Also, ensembles are highly correlated because ensemble forecasts generated from a combination of randomly perturbed initial conditions and different convective schemes in numerical weather model. We discuss the dependence of the bias correction results obtained from Qunatile-based Matching when there is correlation between ensembles and the variance of observation is larger than that of model. A simulation study is employed to understand the relation and distributional characteristics of observation and model when applying Quantile-based Matching method.
6.
2018.12
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This study evaluated the performance of GFDL HiRAM, a fine resolution AGCM, in the simulation of GPI (Genesis Potential Index) of tropical cyclone and its temporal variation over the Western North Pacific (WNP). We analyzed the AMIP simulation by the AGCM for the 30-year (1979-2008) forced by observed sea surface temperatures as the lower boundary condition. Since GPI depends on the five large-scale environmental factors(850 hPa absolute vorticity, 700 hPa relative humidity, vertical wind shear, maximum potential intensity, and 500 hPa vertical velocity), the biases of the simulation are examined for these factors as well as GPI itself. The results are compared with the ECMWF Interim reanalysis (ERA-I), and the analyses show that both the mean spatial pattern and the seasonal cycle of GPI over the WNP are reasonably simulated by HiRAM. But the magnitude of GPI is significantly underestimated due to the combined contribution of negative biases in four factors excluding the low-level vorticity. It is demonstrated that the three leading modes of spatio-temporal variability of GPI in EOF analysis for ERA-I are associated with ENSO, climate change with long-term trends, and SST anomalies over the WNP. The response of GPI to ENSO is more or less captured by HiRAM, including the east-west shift of Typhoon genesis location. However, it is supposed that unrealistic response of GPI and its factors to La-Nina or eastern Pacific El-Nino is an important shortcoming of HiRAM. In addition, HiRAM fails to reproduce the characteristic spatiotemporal variation associated with the climate change mode of GPI. The key findings from this study provide helpful guidance for improvement of HiRAM.
7.
2018.12
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We examined if the enhanced forests could modify thermal climatic conditions in the southwestern China and its surrounding regions. We used the continuous time-series of annual forests fraction obtained from He et al. (2017) and sensible heat flux and temperatures from the European Center for Medium- Range Weather Forecasts reanalysis (ERA-Interim) for 1982-2011. In the linear regression trend analysis, the forests fraction, area-averaged over the southwestern China, significantly increased by 15.46% over the three decades. Significantly negative correlations of surface sensible heat flux during the summer growing season (June through August, JJA) with the area-averaged time-series of annual forests fraction were shown in the southwestern China. Correspondingly, the significantly negative correlations of JJA temperature at 925hPa with the annual forests fraction were observed in the southwestern China as well as the surrounding regions propagated to the east. The spatial patterns of negative correlations between the thermal climatic variables and forests fraction were consistent with the difference patterns of sensible heat flux and temperatures between high-fraction and low-fraction years of forests in the southwestern China. The results indicated that the enhanced forests in the southwestern China could reduce thermal energy transfer from land to atmosphere during JJA and, consequently, lower atmospheric temperatures. Based on the temperature trend analysis using the Chinese weather station data, we inferred that the forest-induced cooling effect might be one of the factors of relatively less summer warming, even cooling, trends in the southern China.
