• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1018-1022
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• 2008

2007년 Intergovernmental Panel on Climate Change(IPCC) 4차보고서 이후로 지구 온난화에 대한 다양한 부분에 영향 분석 연구가 더욱 활발하게 진행되고 있으며, 그 가운데 수자원 즉 육상의 물 순환은 인간 활동과 생태계 전반에 대한 직접 영향으로 인해 기후변화 정책 수립 시 그 중요성이 더욱 부각되고 있다. 현재까지, 많은 연구에 있어서 Global Circulation Model (GCM)을 직접 축소기법을 이용한 후 이를 수문 모형에 입력하여 수자원 영향 분석을 실시해오고 있다. 국외를 중심으로 기존 GCM보다 해상도가 높은 Regional Climate Model(RCM)을 이용한 분석이 일부 시행되고 있으나, 국내에서는 자료의 가용 여부 및 적용성의 검토가 아직 미비한 실정이다. 이러한 관점에서 본 연구에서는 27km의 해상도를 갖는 기상청 RegCM3 RCM에서 도출된 10일 간격 기후변화 SRES 시나리오 자료에 대한 적합성을 평가하고자 한다. 적합성을 평가 하기위해서 국내 주요지점에 근접한 격자자료를 RCM으로부터 추출하고 이에 대한 수문학적 특성치 분석, 저빈도 분석(low frequency analysis), 극치사상의 분포형태 등을 실측 강수자료와 다양한 형태로 비교 검토하여 RCM 자료의 적합성을 평가하였다.

• Water Engineering Research
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• v.6 no.2
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• pp.63-71
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• 2005

Nowadays Climate disasters are frequently happening due to occasional occurrences of EI Nino and La Nina events and among them, water shortage is one of the serious problems. To cope with this problem, climate model simulations can give very helpful information. To utilize the climate model for enhancing the water resources planning techniques, probabilistic measures of the effectiveness of global climate model (GCM) simulations of an indicator variable for discriminating high versus low regional observations of a target variable are proposed in this study. The objective of this study is to present the various analysis methods to find the suitable application methods of GCM information for Korean water resources planning. The basic formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. The various methods for adopting correct association, changing the window size, discrimination condition, and the use of temporally down scaled data were proposed to find out the suitable way for Korean water resources planning.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.69-79
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• 2017

In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.1-12
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• 2015

The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.58-67
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• 2020

Terrestrial ecosystems influence climate change via their climate regulation function, which is manifested within the carbon, water, and energy circulation between the atmosphere and surface. However, it has been challenging to quantify the climate regulation of terrestrial ecosystems and identify its regional distribution, which provides useful information for establishing regional climate-mitigation plans as well as facilitates better understanding of the interactions between the climate and land processes. In this study, a land surface model (LSM) that represents the land-atmosphere interactions and plant phenological variations was introduced to assess the contributions of terrestrial ecosystems to atmospheric warming or cooling effects over East Asia over the last half century. Three main climate-regulating components were simulated: net radiation flux, carbon exchange, and moisture flux at the surface. Then, the contribution of each component to the atmospheric warming or cooling (negative or positive feedback to the atmosphere, respectively) was investigated. The results showed that the terrestrial ecosystem over the Siberian region has shown a relatively large increase in positive feedback due to the enhancement of biogeochemical processes, indicating an offset effect to delay global warming. Meanwhile, the Gobi Desert shows different regional variations: increase in positive feedback in its southern part but increase in negative one in its eastern part, which implies the eastward movements of desert areas. As such, even though the LSM has limitations, this model approach to quantify the climate regulation is useful to extract the relevant characteristics in its spatio-temporal variations.

• Atmosphere
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• v.26 no.4
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• pp.711-716
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• 2016

The dynamical model forecasts using state-of-art general circulation models (GCMs) have some limitations to simulate the real climate system since they do not depend on the past history. One of the alternative methods to correct model errors is to use the canonical correlation analysis (CCA) correction method. CCA forecasts at the present time show better skill than dynamical model forecasts especially over the midlatitudes. Model outputs are adjusted based on the CCA modes between the model forecasts and the observations. This study builds a canonical correlation prediction model for subseasonal (June) precipitation. The predictors are circulation fields over western North Pacific from the Global Seasonal Forecasting System version 5 (GloSea5) and observed snow cover extent over Eurasia continent from Climate Data Record (CDR). The former is based on simultaneous teleconnection between the western North Pacific and the East Asia, and the latter on lagged teleconnection between the Eurasia continent and the East Asia. In addition, we suggest a technique for improving forecast skill by applying the ensemble canonical correlation (ECC) to individual canonical correlation predictions.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.100-102
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• 1999

We have analyzed AVHRR global data set for obtaining aerosol and cloud microphysical parameters, i. e., optical thickness and size index of particle polydispersions. From the results, it is found that the cloud optical thickness increases with increasing aerosol column number, which seems to be caused mainly by decreasing cloud particle radius, The cloud liquid water path was observed to be relatively constant without a significant dependence on the aerosol number. Further comparison of the satellite results with a general circulation model simulation.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.757-765
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• 2012

The purpose of this study was to estimate the spatial-temporal NPP(Net Primary Productivity) and SCS(Soil Carbon Storage) of forest ecosystem under climate change in the capital area of South Korea using Mapss-Century1 (MC1), one of Dynamic Global Vegetation Models (DGVMs). The characteristics of the NPP and SCS changes were simulated based on a biogeochemical module in this model. As results of the simulation, the NPP varies from 2.02 to 7.43 tC $ha^{-1}\;yr^{-1}$ and the SCS varies from 34.55 to 84.81 tC $ha^{-1}$ during 1971~2000 respectively. Spatial mean NPP showed a little decreasing tendency in near future (2021~2050) and then increased in far future (2071~2100) under the condition of increasing air temperature and precipitation which were simulated by the A1B climate change scenario of Intergovernmental Panel on Climate Change (IPCC). But it was estimated that the temporal change of spatial mean NPP indicates 4.62% increasing tendency in which elevation is over 150m in this area. However, spatial mean SCS was decreased in the two future periods under same climate condition.

• Atmosphere
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• v.18 no.4
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• pp.507-524
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• 2008

In this paper, future climate changes over East Asia($20^{\circ}{\sim}50^{\circ}N$, $100^{\circ}{\sim}150^{\circ}E$) are projected by anthropogenic forcing of greenhouse gases and aerosols using coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1, A1B and A2 scenarios. Before projection future climate, model performance is assessed by the $20^{th}$ Century (20C3M) experiment with bias, root Mean Square Error (RMSE), ratio of standard deviation, Taylor diagram analysis. The result of examination of the seasonal uncertainty of T2m and PCP shows that cold bias, lowered than that of observation, of T2m and wet bias, larger than that of observation, of PCP are found over East Asia. The largest wet bias is found in winter and the largest cold bias is found in summer. The RMSE of temperature in the annual mean increases and this trend happens in winter, too. That is, higher resolution model shows generally better performances in simulation T2m and PCP. Based on IPCC SRES scenarios, East Asia will experience warmer and wetter climate in the coming $21^{st}$ century. It is predict the T2m increase in East Asia is larger than global mean temperature. As the latitude goes high, the warming over the continents of East Asia showed much more increase than that over the ocean. An enhanced land-sea contrast is proposed as a possible mechanism of the intensified Asian summer monsoon. But, the inter-model variability in PCP changes is large.