• Journal of Korean Society on Water Environment
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• v.26 no.3
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• pp.482-490
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• 2010

In this study 17 GCMs' simulations of late 20th century climate in Korea are examined. A regionally averaged time series formed by averaging the temperature and precipitation values at all the Korean grid points. In order to compare general circulation models with observations, observed spatially averaged temperature and precipitation is calculated using 24 stations for 1971 to 2000. The annual mean difference between models and observed data are compared. For temperature, most models have a slight cold bias. The models with least bias in annual average temperature are NIES(MIROC3.2 hires), GISS(AOM) and INGV(SXG2005). For precipitation, almost all models have a dry bias, and for some the bias exceeds 50%. Models with lowest bias are NIES(MIROC3.2 hires), CCCma(CGCM3-T47) and MPI-M(ECHAM5-OM). The models' simulated seasonal cycles show that for temperature, CSIRO(Mk3.0) has the best followed by CCCma(CGCM3-T47) and CCCma(CGCM3-T63), and for precipitation, NIES(MIROC3.2 hires) has the best followed by CSIRO(Mk3.0) and CNRM(CM3). In the assessment using Taylor diagram, CCCma(CGCM3-T47) ranks the best for temperature, and NIES(MIROC3.2 hires) ranks the best for precipitation.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• Journal of Environmental Science International
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• v.16 no.3
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• pp.261-267
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• 2007

In this study, the Slab Ocean Model (SOM) is coupled with an Atmospheric General Circulation Model (AGCM) which developed in University of Kangnung based on the land surface model of Biosphere-Atmosphere Transfer Scheme (BATS). The purposes of this study are to understand radiative role of clouds considering of the atmospheric feedback, and to compare the Clouds Radiative Forcing (CRF) come from the analyses using the clear-cloud sky method and CGCM. The new CGCM was integrated by using two sets of the clouds with radiative role (EXP-A) and without radiative role (EXP-B). Clouds in this two cases show the negative effect $-26.0\;Wm^{-2}$ of difference of radiation budget at top of atmosphere (TOA). The annual global means radiation budget of this simulation at TOA is larger than the estimations ($-17.0 Wm^{-2}$) came from Earth Radiation Budget Experiment (ERBE). The work showed the surface negative effect with $-18.6 Wm^{-2}$ in the two different simulations of CRF. Otherwise, sensible heat flux in the simulation shows a great contribution with positive forcing of $+24.4 Wm^{-2}$. It is found that cooling effect to the surface temperature due to radiative role of clouds is about $7.5^{\circ}C$. From this study it could make an accurate of the different CRF estimation considering either feedback of EXP-B or not EXP-A under clear-sky and cloud-sky conditions respectively at TOA. This result clearly shows its difference of CRF $-11.1 Wm^{-2}$.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.229-233
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• 2008

기상청은 작년 말 전국 60개 지점 기상관측 자료 분석결과로부터 2007년 평균기온($13.5^{\circ}C$)이 1998년($13.6^{\circ}C$)에 이어 두 번째로 높게 나타났으며, 2007년 전국 강수량(1498.5mm)은 평년보다 13.9% 증가한 것을 확인하였다. 그리고 한반도 기후변화의 특징으로 기상 사상의 극값이 증가하고 있음을 추가로 언급한 바 있다. 과거에는 발생하지 않았던 고강도의 강우, 기온 상승과 같은 극치 사상의 잦은 출현빈도가 원인이 되고 있다. 그러나 이들 현상들은 일정한 패턴과 규칙에 따라 발생하지 않아 판단기준이나 경향성을 객관화 또는 정량화하기에 무리가 따른다. 본 논문에서는 기후변화가 우리나라의 극한 사상 변동과 그 영향을 분석하기 위하여 SRES B2 온난화가스시나리오와 YONU CGCM 으로부터 모의된 강우 시계열 자료를 이용하여 미래의 극치 사상의 경향성을 계절에 따라 비교 분석하였다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.205-205
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• 2011

본 연구에서는 한반도의 유역별 대표 기상관측 지점을 선정하여 기후변화로 인하여 미래에 나타날 수 있는 가뭄의 경향성을 분석하였다. 분석을 위한 자료는 실제 강수량 자료(1974~1999년)와 A2시나리오를 따르는 5개의 GCMs(General Circulation Model) 자료를 통계적 상세화한 강수량 자료(1974~2099년)를 이용하여 산정한 지속기간 6개월의 SPI(Standardized Precipitation Index)를 사용하였다. 분석을 위한 대표 기상관측 지점으로는 춘천, 서울, 대전, 대구, 전주, 광주, 부산 지점을 선정하였으며 GCM으로는 호주(CSIRO : MK3), 미국(GFDL : CM2_1), 독일/한국(CONS : ECHO-G), 일본(MRI : CGCM2_3_2), 영국(UKMO : HADGEM1)의 GCM을 선정하였다. 가뭄의 통계적 특성을 분석하기 위하여 Mann-Kendall 검정을 통한 경향성 분석과 Wavelet Transform 분석을 통한 주기성 분석을 하였으며 Drought Spell을 이용하여 가뭄심도별 발생빈도를 보았다. 그 결과, 경향성 분석에서는 각 GCMs의 차이를 볼 수 있었으며 CSIRO : MK3.0, GFDL : CM2_1, MIUB : ECHO-G 모델에서는 전체적으로 가뭄이 완화되고 MRI : CGCM2_3_2, UKMO : HADGEM1 모델에서는 가뭄이 심화되는 것으로 나타났다. 주기성 분석에서는 춘천, 서울에서는 낮은 주기를 대전, 대구, 전주, 광주, 부산지점에서는 다소 긴 주기를 보여주었다. Drought-spell에 의한 분석에서는 전 관측지점에서 SPI의 이론적인 확률밀도 함수값과 유사하게 나타나고 있었으며 이를 통해, 미래에는 극심한 가뭄의 빈도가 증가하고 있는 것을 예측할 수 있었다.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.709-720
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• 2010

This paper describes the modeling of climate change impact on drought using a conceptual soil moisture model and presents the results of the modeling approach. The future climate series is obtained by scaling the historical series, informed by CCCma CGCM3-T63 with A2 green house emission scenario, using a daily scaling method that considers changes in the future monthly precipitation and potential evapotranspiration as well as in the daily precipitation distribution. The majority of the modeling results indicate that there will be more frequent drought in Korea in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.23-33
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• 2009

Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.189-193
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• 2008

본 연구는 충주댐 유역을 대상으로 미래의 기후변화, 그에 따른 식생상태, 그리고 미래의 토지이용 변화를 고려한 상태에서 SWAT-K 모형에 의한 수문순환인자들의 변화가 댐의 유입량에 미치는 영향을 파악하고자 한다. SWAT 모형의 검보정은 6년간($2000{\sim}2006$, 2001년 제외)의 댐유입량 자료를 이용하여 실시하였으며, Nash_Sutcliffe 모형효율은 $0.52{\sim}0.88$의 범위로 검보정되었다. 기후변화 시나리오는 IPCC에서 제공하고 있는 GCM들 중에서 CCCma CGCM2의 A2, B2 시나리오를 이용하였으며, 댐유역의 기후변화를 모의하기 위하여 과거 30년간($1977{\sim}2006$)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2030년, 2060년, 2090년 전후의 각 30년간의 미래 정보를 재생산하였다. 미래의 식생정보는 7년($2000{\sim}2006$)간의 MODIS 위성 영상에 의한 엽면적 지수를 월단위로 구축하여 엽면적 지수와 평균기온간의 상관회귀식을 도출하여 미래 기후변화에 따른 식생의 활력도를 예측하였다. 미래의 토지이용 변화는 CA-MArkov 기법을 개선, 적용하여 총 9개의 토지이용 항목에 대하여 각 항목별 예측을 실시하였다. 2000년의 기상자료 및 댐유입량을 기준으로 이상의 미래기후, 식생, 토지이용 에측 정보를 적용하여 미래의 댐유입량을 모의한 결과를 분석하였다. 그 결과 강수량 및 온도의 변동이 가장 크게 영향을 주어 유입량의 변화가 모의되었으며, 이에 따른 수문인자의 변동은 2000년 기준으로 증발산량, 토양수분의 변동을 분석하였다. 미래의 수문순환에 가장 큰 영향을 주는 수문인자는 토양수분으로 나타나, 미래에는 산림지역 및 토지이용 개발에 따른 토양수분의 함양량 유지를 위한 유역관리가 중요한 요인이 될 것으로 나타났다.