• 한국농공학회논문집
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• 제64권6호
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• pp.101-112
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• 2022

Extreme precipitation events have recently become a leading cause of disasters. Thus, investigating the variability and trends of extreme precipitation is crucial to mitigate the increasing impact of such events. Spatial distribution and temporal trends in annual precipitation and four extreme precipitation indices of duration (CWD), frequency (R10 mm), intensity (Rx1day), and percentile-based threshold (R95pTOT) were analyzed using the daily precipitation data of 10 observation stations in Chungcheong province during 1974-2020. The precipitation at all observation stations, except the Boryeong station, showed nonsignificant increasing trends at 95% confidence level (CL) and increasing magnitudes from the west to east regions. The high variability in mean annual precipitation was more pronounced around the northeast and northwest regions. Similarly, there were moderate to high patterns in extreme precipitation indices around the northeast region. However, the precipitation indices of duration and frequency consistently increased from the west to east regions, while those of intensity and percentile-based threshold increased from the south to east regions. Nonsignificant increasing trends dominated in CWD, R10 mm, and Rx1day at all stations, except for R10 mm at Boeun station and Rx1day at Cheongju and Jecheon stations, which showed a significantly increasing trend. The spatial distribution of trend magnitude shows that R10 mm increased from the west to east regions. Furthermore, variations in precipitation were very strongly correlated (99% CL) with R10 mm, Rx1day, and R95pTOT at all stations, except with wR10 mm at Cheongju station, which was strongly correlated with a 95% CL.

• 대기
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• 제31권5호
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• pp.607-623
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• 2021

This study presents projections of future extreme climate over the Korean Peninsula (KP), using bias-corrected data from multiple regional climate model (RCM) simulations in CORDEX-EA Phase 2 project. In order to confirm difference according to degree of greenhouse gas (GHG) emission, high GHG path of SSP5-8.5 and low GHG path of SSP1-2.6 scenario are used. Under SSP5-8.5 scenario, mean temperature and precipitation over KP are projected to increase by 6.38℃ and 20.56%, respectively, in 2081~2100 years compared to 1995~2014 years. Projected changes in extreme climate suggest that intensity indices of extreme temperatures would increase by 6.41℃ to 8.18℃ and precipitation by 24.75% to 33.74%, being bigger increase than their mean values. Both of frequency indices of the extreme climate and consecutive indices of extreme precipitation are also projected to increase. But the projected changes in extreme indices vary regionally. Under SSP1-2.6 scenario, the extreme climate indices would increase less than SSP5-8.5 scenario. In other words, temperature (precipitation) intensity indices would increase 2.63℃ to 3.12℃ (14.09% to 16.07%). And there is expected to be relationship between mean precipitation and warming, which mean precipitation would increase as warming with bigger relationship in northern KP (4.08% ℃^-1) than southern KP (3.53% ℃^-1) under SSP5-8.5 scenario. The projected relationship, however, is not significant for extreme precipitation. It seems because of complex characteristics of extreme precipitation from summer monsoon and typhoon over KP.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.174-174
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• 2023

The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.163-163
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• 2023

Flooding has become an increasing event which is one of the major natural disasters responsible for direct economic damage in South Korea. Driven by climate change, precipitation extremes play significant role on the flood damage and its further increase is expected to exacerbate the socioeconomic impact in the country. However, the empirical evidence associating changes in precipitation extremes to the historical flood damage is limited. Thus, there is a need to assess the causal relationship between changes in precipitation extremes and flood damage, especially in agricultural region like Chungcheong region in South Korea. The spatial and temporal changes of precipitation extremes from 10 synoptic stations based on daily precipitation data were analyzed using the ClimPACT2 tool and Mann-Kendall test. The four precipitation extreme indices consisting of consecutive wet days (CWD), number of very heavy precipitation wet days (R30 mm), maximum 1-day precipitation amount (Rx1day), and simple daily precipitation intensity (SDII), which represent changes in intensity, frequency, and duration, respectively, and the time series data on flooded area and flood damage from 1985 to 2020 were used to investigate the causal relationship in the ARDL-ECM framework and pairwise Granger causality analysis. The trend results showed that majority of the precipitation indices indicated positive trends, however, CWD showed no significant changes. ARDL-ECM framework showed that there was a long-run relationship among the variables. Further analysis on the empirical results showed that flooded area and Rx1day have significant positive impacts on the flood damage in both short and long-runs while R30 mm only indicated significant positive impact in the short-run, both in the current period, which implies that an increase in flooded area, Rx1day, and R30 mm will cause an increase in the flood damage. The pairwise Granger analysis showed unidirectional causality from the flooded area, R30 mm, Rx1day, and SDII to flood damage. Thus, these precipitation indices could be useful as indicators of pluvial flood damage in Chungcheong region of South Korea.

• 한국지역지리학회지
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• 제17권5호
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• pp.505-520
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• 2011

본 연구에서는 호우의 변화경향을 유역별로 분석하였다. 이를 위해 한국을 6개의 유역으로 나누고 호우와 관련된 7개의 극한강수지수를 분석하여 변화지속성을 파악하였다. 호우량은 호우일수보다 증가경향이 더 지속적이다. 일강수량이 50mm 이상 강수일수와 95 퍼센타일 이상 강수량의 증가경향이 가장 지속적이다. 호우관련지수는 분석기간 동안 대부분 증가경향이지만 한강 유역, 낙동강 상류지역, 동해안 지역이 다른 유역에 비해 증가경향이 뚜렷하다. 금강 유역과 섬진강 유역은 호우의 증가경향이 통계적으로 유의하지 않고 변동성이 크다. 호우의 증가경향은 1970년대 중반 이후 한강과 낙동강 유역에서 지속적이지만 2000년대 중반 이후 증가경향이 지속적으로 나타나는 지점들이 감소한다. 이는 최근 호우의 빈도와 강도가 더욱 불규칙해지고 있음을 의미한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.314-314
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• 2023

Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.

• 한국수자원학회논문집
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• 제49권6호
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• pp.509-518
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• 2016

본 연구는 1985년부터 2015년까지 지속기간에 따른 청미천 유역의 가뭄을 분석하였다. 가뭄의 정량적 평가를 위해 기상학적 가뭄지수와 수문학적 가뭄지수를 사용하였다. 기상학적 가뭄지수로는 강수량을 변수로 하는 SPI(Standarized Precipitation Index)와 강수량과 증발산량을 변수로 하는 SPEI(Standarized Precipitation Evapotranspiration Index)를 사용하였다. SWAT 모형의 모의를 통해 도출된 결과를 바탕으로 농업학적 가뭄지수인 PDSI(Palmer Drought Severity Index)와 수문학적 가뭄지수인 SDI(Streamflow Drought Index)를 적용하였다. 산정 결과, 극한 및 평균 가뭄의 평균에서 2015년과 2014년이 가장 가뭄에 취약함이 확인되었다. 빈도분석에 따른 가뭄의 변동성은 서로 다른 형태를 보였다. 또한 상관분석에서 극한 가뭄 및 평균 가뭄은 PDSI를 제외한 SPI, SPEI, SDI 가뭄지수간에는 높은 상관관계가 확인되었다. 하지만 각 가뭄지수는 서로 다른 극한가뭄의 시기 및 강도를 보였다. 따라서 가뭄분석시 다양한 특성을 지닌 가뭄지수를 활용하는 것이 필요하다.

• 한국지역지리학회지
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• 제21권2호
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• pp.394-410
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• 2015

본 연구에서는 우리나라의 극한고온, 극한저온, 극한강수의 발생 빈도 및 규모를 지역별로 분석하고 이에 대한 기후지역을 구분하였다. 열대일수는 해안보다 내륙에서 많았고, 서리일수는 고도와 위도의 특성이 잘 나타났다. 호우 일수는 남해안과 제주도에서 많았고, 경상북도 일대에서 적게 나타났다. 이후 주성분 분석과 군집분석을 통해 연구기간의 전 후반기 시기별 변화와 최근 30년 평균(1981~2010년)에 대한 극한기후지수에 대한 기후지역을 구분하였다. 열대일수의 경우 남북 방향으로 구분된 특징을 보였으며, 서리일수는 동해안 및 서해안, 제주도가 하나의 지역으로 구분되었고 호우일수는 경기도 및 강원도 이남 지역에서 동서 방향으로 구분된 특징을 보였다. 본 연구를 통하여 다양한 분야에서 기후변화 적응 및 완화에 대한 대응체계 마련에 도움이 될 것으로 기대된다.

• 한국농공학회논문집
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• 제59권4호
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• pp.65-74
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• 2017

North Korea is one of the high vulnerable countries facing the threat of natural disaster and has experienced more frequent disasters in recent years. These disasters have significantly led to food shortages and large reductions in crop yields. In 2015, both North Korean officials and international agencies had identified the extreme drought event, the worst in one hundred years according to the North Korean government. The objective of this study was an assessment of the extreme drought events in 2014~2015, and to apply climatic drought indices for drought monitoring in North Korea. Characteristics of the extreme drought in North Korea are examined by using the weekly-based Standardized Precipitation Evapotranspiration Index (SPEI). The drought characteristics illustrated by the SPEI results are compared with a Standardized Precipitation Index (SPI) results and drought impact information to understand how these indices can explain the drought conditions within the country. These results demonstrated that the SPEI could be an effective tool to provide improved spatial and temporal drought conditions to inform management decisions for drought policy.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.143-143
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• 2021

Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.