• International Journal of Contents
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• 제17권1호
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• pp.61-70
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• 2021

As the resolution of climate change scenario data applied with regional models increased, Earth System Grid Federation (ESGF) was established around major climate-related organizations to jointly operated and manage large-scale climate data. ESGF developed standard software to provide model output, observation data management, dissemination, and analysis using Peer to Peer (P2P) computing technology. Roles of each institution were divided into index and data nodes. Therefore, ESGF data node was established at APEC Climate Center in Korea on behalf of Asia to share data on climate change scenarios of CORDEX-East Asia (CORDEX-EA) to study climate changes in Eastern Asia. Climate researchers are expected to play a large role in researching causes of global warming and responding to climate change by providing CORDEX-EA regional model data to the world through ESGF data node.

• Communications for Statistical Applications and Methods
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• 제24권1호
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• 한국기후변화학회지
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• 제7권3호
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.51-53
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• 2015

As abnormal climate phenomena occur more frequently due to climate change, damage which results from meteorological disaster increases accordingly and its scale and variety are becoming wider. This paper draws out planning and design elements and application techniques to build cities more adaptive to climate change from urban development cases in US and Europe. An urban model is suggested, that enables built environment to be more resilient to risks caused by climate change is applicable to urban development projects in practice.

• Ocean and Polar Research
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• 제34권4호
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• pp.431-444
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• 2012

We simulated and compared present and future ocean circulation in the East China Sea using an East Asia Regional Ocean model. Mean climate states for 1990~1999 and 2030~2039 were used as surface conditions for simulations of present and future ocean circulation, which were derived from the simulations of three different global climate models, ECHAM5-MPI, GFDL-CM2.0 and MIROC3.2_hires, for the 20th century and those of 21st century as projected by the IPCC SRES A1B. East Asia Regional Ocean model simulated the detailed patterns of temperature, salinity and current fields under present and future climate conditions and their changes instead of the simple structures of global climate models. To some extent, there are consistent ocean circulation changes derived from the three pairs corresponding to the global climate model in so much as the temperature increases not only in winter but summer at both the surface and bottom and that temperature and salinity changes are prominent near the Chinese coast and in the Changjiang bank. However, the simulated circulations are different among each other depending on the prescribed atmospheric conditions not only under present climate but also with regard to future climate conditions. There is not a coincident tendency in ocean circulation changes between present and future simulations derived from the three pairs. This suggests that more simulations with different pairs are needed.

• 한국농공학회논문집
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• 제57권2호
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• pp.1-13
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• 2015

The Coupled Model Intercomparison Project Phase 5 (CMIP5), coordinated by the World Climate Research Programme in support of the Intergovernmental Panel on Climate Change (IPCC) AR5, is the most recent, provides projections of future climate change using various global climate models under four major greenhouse gas emission scenarios. There is a wide selection of climate models available to provide projections of future climate change. These provide for a wide range of possible outcomes when trying to inform managers about possible climate changes. Hence, future agrometeorological indicators estimation will be much impacted by which global climate model and climate change scenarios are used. Decision makers are increasingly expected to use climate information, but the uncertainties associated with global climate models pose substantial hurdles for agricultural resources planning. Although it is the most reasonable that quantifying of the future uncertainty using climate change scenarios, preliminary analysis using reasonable factors for selecting a subset for decision making are needed. In order to narrow the projections to a handful of models that could be used in a climate change impact study, we could provide effective information for selecting climate model and scenarios for climate change impact assessment using maximum/minimum temperature, precipitation, reference evapotranspiration, and moisture index of nine Representative Concentration Pathways (RCP) scenarios.

• 한국농공학회논문집
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• 제54권2호
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• pp.67-75
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• 2012

Different from other natural hazards including floods, drought advances slowly and spreads widely, so that the preparedness is quite important and effective to mitigate the impacts from drought. Evaluation and forecast the status of drought for the present and future utilizing the meteorological scenario for agricultural drought can be useful to set a plan for agricultural drought mitigation in agriculture water resource management. In this study, drought climate scenario model on the basis of historical drought records for preparing agricultural drought mitigation was developed. To consider dependency and correlation between various climate variables, this model was utilized the historical climate pattern using reference year setting of four drought levels. The reference year for drought level was determined based on the frequency analysis result of monthly effective rainfall. On the basis of this model, drought climate scenarios at Suwon and Icheon station were set up and these scenarios were applied on the water balance simulation of reservoir water storage for Madun reservoir as well as the soil moisture model for Gosam reservoir watershed. The results showed that drought climate scenarios in this study could be more useful for long-term forecast of longer than 2~3 months period rather than short-term forecast of below one month.

• 한국기후변화학회지
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• 제7권4호
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• pp.407-419
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• 2016

The low flow is the necessary and important index to establish national water planning, however there are lots of uncertainty in the low flow estimation. Therefore, the objectives of this study are to assess the climate change uncertainty and the effects of hydrological models on low flow estimation. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods and 2 hydrological models were applied for evaluation. The study area were selected as Chungju dam and Soyang river dam basin, and the 30 days minimum flow is used for the low flow evaluation. The results of the uncertainty analysis showed that the hydrological model was the largest source of uncertainty about 41.5% in the low flow projection. The uncertainty of hydrological model is higher than the other steps (RCM, statistical post-processing). Also, VIC model is more sensitive for climate change compared to SWAT model. Therefore, the hydrological model should be thoroughly reviewed for the climate change impact assessment on low flow.

• 한국농공학회논문집
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• 제60권6호
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• pp.83-96
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• 2018

The objective of this study was to estimate the climate change impact on water quantity and quality to Saemanguem watershed using SWAT (Soil and water assessment tool) model. The SWAT model was calibrated and validated using observed data from 2008 to 2017 for the study watershed. The $R^2$ (Determination coefficient), RMSE (Root mean square error), and NSE (Nash-sutcliffe efficiency coefficient) were used to evaluate the model performance. RCP scenario data were produced from 10 GCM (General circulation model) and all relevant grid data including the major observation points (Gusan, Jeonju, Buan, Jeongeup) were extracted. The systematic error evaluation of the GCM model outputs was performed as well. They showed various variations based on analysis of future climate change effects. In future periods, the MIROC5 model showed the maximum values and the CMCC-CM model presented the minimum values in the climate data. Increasing rainfall amount was from 180mm to 250mm and increasing temperature value ranged from 1.7 to $5.9^{\circ}C$, respectively, compared with the baseline (2006~2017) in 10 GCM model outputs. The future 2030s and 2070s runoff showed increasing rate of 16~29% under future climate data. The future rate of change for T-N (Total nitrogen) and T-P (Total phosphorus) loads presented from -26 to +0.13% and from +5 to 47%, respectively. The hydrologic cycle and water quality from the Saemanguem headwater were very sensitive to projected climate change scenarios so that GCM model should be carefully selected for the purpose of use and the tendency analysis of GCM model are needed if necessary.

• 한국지리정보학회지
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• 제14권3호
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• pp.136-149
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• 2011

본 연구의 목적은 IPCC A1B 온실가스 배출 시나리오에 따른 전지구 기후모형(global climate model, GCM)을 바탕으로 구축된 KMA-RCM(Korea meteorological administration-regional climate model)을 GIS를 활용하여 규모 상세화 기법을 개발하고 검증을 통하여 기후변화 시나리오의 불확실성을 줄이는 것이다. 연구지역은 남한 전역이며, 연구 대상 기간은 1971년부터 2100년까지이다. KMA-RCM의 규모 상세화 결과의 최적화를 위해 GIS 공간보간기법 중 기온에는 Co-Kriging, 강우에는 IDW을 활용하여 고도에 따른 기온 감율을 적용하였다. 최종 연구 결과로 총 1971년도부터 2100년의 월별 평균 기온 및 강우량이 도출되었다. 평균기온의 경우 130년 동안 $1.39^{\circ}C$ 상승하고, 강우량의 경우 271.23mm가 증가하는 것으로 파악되었다. 본 연구결과의 검증을 위하여 2001년부터 2010년까지 75개 자동기상관측지점(automated weather station, AWS) 실측자료와 동기간의 미래 기후예측값과의 상관관계를 분석하였다. 평균기온의 경우 상관계수가 0.98로 매우 높게 나타났으며 강우량의 경우 0.56으로 기온에 비해 상관관계가 낮게 분석되었다. 본 연구에서는 기존의 기후변화 시나리오 규모 상세화 연구에서 사용되던 GIS 방법론을 고도에 따른 기온감율을 적용하는 기법을 개발하였다. 이를 통하여 보다 현실성 높은 지역적 규모의 미래 기후변화 시나리오를 구축하고 이의 불확실성을 줄이기 위하여 연구를 진행하였다.