• 제목/요약/키워드: Multi-GCMs

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Hierarchical Bayesian Model을 이용한 GCMs 의 최적 Multi-Model Ensemble 모형 구축 (Optimal Multi-Model Ensemble Model Development Using Hierarchical Bayesian Model Based)

  • 권현한;민영미
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.1147-1151
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    • 2009
  • In this study, we address the problem of producing probability forecasts of summer seasonal rainfall, on the basis of Hindcast experiments from a ensemble of GCMs(cwb, gcps, gdaps, metri, msc_gem, msc_gm2, msc_gm3, msc_sef and ncep). An advanced Hierarchical Bayesian weighting scheme is developed and used to combine nine GCMs seasonal hindcast ensembles. Hindcast period is 23 years from 1981 to 2003. The simplest approach for combining GCM forecasts is to weight each model equally, and this approach is referred to as pooled ensemble. This study proposes a more complex approach which weights the models spatially and seasonally based on past model performance for rainfall. The Bayesian approach to multi-model combination of GCMs determines the relative weights of each GCM with climatology as the prior. The weights are chosen to maximize the likelihood score of the posterior probabilities. The individual GCM ensembles, simple poolings of three and six models, and the optimally combined multimodel ensemble are compared.

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여름강수량의 단기예측을 위한 Multi-Ensemble GCMs 기반 시공간적 Downscaling 기법 개발 (Development of Multi-Ensemble GCMs Based Spatio-Temporal Downscaling Scheme for Short-term Prediction)

  • 권현한;민영미
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.1142-1146
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    • 2009
  • A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

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Projecting the spatial-temporal trends of extreme climatology in South Korea based on optimal multi-model ensemble members

  • Mirza Junaid Ahmad;Kyung-sook Choi
    • 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.

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아시아 몬순특성을 고려한 다중 GCMs 선정방법 개발 및 평가 (Development and assessment of framework for selecting multi-GCMs considering Asia monsoon characteristics)

  • 김정배;김진훈;배덕효
    • 한국수자원학회논문집
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    • 제53권9호
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    • pp.647-660
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    • 2020
  • 본 연구에서는 아시아 몬순특성을 고려한 전지구모형(General Circulation model, GCM) 선정방법을 개발하고 방법의 적정성을 평가하였다. 몬순기후와 연관된 12개의 기후변수를 선정하였으며, GCM의 과거 기후재현성을 기준으로 모의성능 평가 매트릭스 및 평가체계를 구성하였다. 19개 GCM으로부터 아시아 몬순지역 및 과거(1976 ~ 2005년) 몬순기간에 대한 12개 기후변수를 관측자료와 비교하여 GCM의 기후모의 성능을 평가하였다. GCM의 평가순위 및 강수량 모의성능을 고려하여 적정 5개 GCM (NorESM1-M, bcc-csm1-1-m, CNRM-CM5, CMCC-CMS, CanESM2)을 선정하였다. 과거 몬순계절 및 월 평균 기후에 대하여 선정된 GCM의 기후재현성을 검증하였다. 선정된 5개 GCM은 12개 기후변수에 대한 아시아 지역의 관측 기후특성을 잘 재현하였으며, 전체 GCM을 사용하는 경우에 비해 모의값과 관측값 간의 오차를 줄일 수 있는 것으로 확인되었다.

기상자료 및 GCMs 예측결과를 활용한 단기 가뭄 예측 (Climate Information and GCMs Seasonal Forecasts Based Short-term Forecasts for Drought)

  • 권현한;문장원;송현섭;문영일
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.1186-1190
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    • 2009
  • 강수량이 예년에 비해 적은 양상은 여름강수량에 대한 부족으로 기인한다. 우리나라의 경우 장마기간의 강수와 태풍으로 인해 발생하는 강수가 전체 강수량에 많은 부분을 차지하고 있기 때문에 여름강수량이 적게 나타나게 되면 가을 가뭄 및 봄 가뭄에 대한 발생 압력도 그 만큼 커지게 되는 것이 일반적이다. 기존 연구들이 단순히 강수량을 가정하거나 시나리오를 기반으로 가뭄을 전망하는데 그치고 있으나 본 연구에서는 2009년 가뭄전망을 위해서 전지구기후모형(GCMs)의 3개월 기상예측 결과를 활용하고자 한다. 즉, APEC 기후예측 센터로부터 제공 받은 3개월 GCM Multi-Model Ensemble 예측 결과를 바탕으로 가뭄상태를 평가하였다. 따라서 본 연구의 목적은 Large-scale의 기후예측 시스템과 기상관측지점의 강수 및 온도를 연결시켜 가뭄을 전망할 수 있는 시스템을 구축하는데 있다. GCM 예측 결과를 바탕으로 2009년도 매월 강수량 및 평균 온도를 추정하여 PDSI 가뭄지수 산정에 이용하였다.

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Giant Cavernous Malformation : A Case Report and Review of the Literature

  • Son, Dong-Wuk;Lee, Sang-Weon;Choi, Chang-Hwa
    • Journal of Korean Neurosurgical Society
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    • 제43권4호
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    • pp.198-200
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    • 2008
  • Giant cavernous malformations (GCMs) occur very rarely and little has been reported about their clinical characteristics. The authors present a case of a 20-year-old woman with a GCM. She was referred due to two episodes of generalized seizure. Computed tomography and magnetic resonance image demonstrated a heterogeneous multi-cystic lesion of $7\times5\times5$ cm size in the left frontal lobe and basal ganglia, and enhancing vascular structure abutting medial portion of the mass. These fingings suggested a diagnosis of GCM accompanying venous angioma. After left frontal craniotomy, transcortical approach was done. Total removal was accomplished and the postoperative course was uneventful. GCMs do not seem differ clinically, surgically or histopathologically from small cavernous angiomas, but imaging appearance of GCMs may be variable. The clinical, radiological feature and management of GCMs are described based on pertinent literature review.

국내 농업기후지대 별 최적기후모형 선정을 통한 미래 벼 도열병 발생 위험도 예측 (Predicting Potential Epidemics of Rice Leaf Blast Disease Using Climate Scenarios from the Best Global Climate Model Selected for Individual Agro-Climatic Zones in Korea)

  • 이성규;김광형
    • 한국기후변화학회지
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    • 제9권2호
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    • pp.133-142
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    • 2018
  • Climate change will affect not only the crop productivity but also the pattern of rice disease epidemics in Korea. Impact assessments for the climate change are conducted using various climate change scenarios from many global climate models (GCM), such as a scenario from a best GCM or scenarios from multiple GCMs, or a combination of both. Here, we evaluated the feasibility of using a climate change scenario from the best GCM for the impact assessment on the potential epidemics of a rice leaf blast disease in Korea, in comparison to a multi?model ensemble (MME) scenario from multiple GCMs. For this, this study involves analyses of disease simulation using an epidemiological model, EPIRICE?LB, which was validated for Korean rice paddy fields. We then assessed likely changes in disease epidemics using the best GCM selected for individual agro?climatic zones and MME scenarios constructed by running 11 GCMs. As a result, the simulated incidence of leaf blast epidemics gradually decreased over the future periods both from the best GCM and MME. The results from this study emphasized that the best GCM selection approach resulted in comparable performance to the MME approach for the climate change impact assessment on rice leaf blast epidemic in Korea.

CORDEX-동아시아 2단계 영역에 대한 다중 RCM의 모의성능 및 불확실성 평가 (Evaluation of Performance and Uncertainty for Multi-RCM over CORDEX-East Asia Phase 2 region)

  • 김진욱;김태준;김도현;김진원;차동현;민승기;김연희
    • 대기
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    • 제30권4호
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    • pp.361-376
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    • 2020
  • This study evaluates multiple Regional Climate Models (RCMs) in simulating temperature and precipitation over the Far East Asia (FEA) and estimates the portions of the total uncertainty originating in the RCMs and the driving Global Climate Models (GCMs) using nine present-day (1981~2000) climate data obtained from combinations of three GCMs and three RCMs in the CORDEX-EA phase2. Downscaling using the RCMs generally improves the present temperature and precipitation simulated in the GCMs. The mean temperature climate in the RCM simulations is similar to that in the GCMs; however, RCMs yield notably better spatial variability than the GCMs. In particular, the RCMs generally yield positive added values to the variability of the summer temperature and the winter precipitation. Evaluating the uncertainties by the GCMs (VARGCM) and the RCMs (VARRCM) on the basis of two-way ANOVA shows that VARRCM is greater than VARGCM in contrast to previous studies which showed VARGCM is larger. In particular, in the winter temperature, the ocean has a very large VARRCM of up to 30%. Precipitation shows that VARRCM is greater than VARGCM in all seasons, but the difference is insignificant. In the following study, we will analyze how the uncertainty of the climate model in the present-day period affects future climate change prospects.

Multi-GCMs을 활용한 논벼 필요수량의 불확성 및 민감도 기후영향평가 (Assessment of climate change impacts on uncertainty and sensitivity of paddy water requirement in South Korea using multi-GCMs)

  • 유승환;이상현;최진용;윤광식;최동호
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2016년도 학술발표회
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    • pp.516-516
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    • 2016
  • 기후변화는 농업생산량 감소와 식량 안보 문제와 같이 농업에 심각한 영향을 미칠 수 있다. 또한 기존의 농업수리 및 관개배수 시설 운영에 영향을 줄 수 있다. 따라서 지속가능한 농업 수자원 관리를 위해서는 기후변화의 영향을 고려한 장기적인 계획 수립이 필요하다. 따라서 본 연구에서는 논벼 지역의 설계용수량의 확률론적 분석을 통한 논벼 필요수량 및 설계용수량에 대한 기후변화영향 평가를 실시하였다. 이를 위해서 본 연구에서는 23개 GCM의 36개 산출물을 활용하여 Multi-model ensemble 구축하였다. 먼저 GCM별 증발산량과 유효우량을 산정한 결과 중부지역에서는 IPSL-CM5A 모델의 기후변화자료를 활용할 경우 증발산량과 유효우량이 타 GCM 모델들과 비하여 크게 산정되었다. 남부지역에서는 CanESM2 모델을 적용할 경우 가장 많은 증발산량과 유효우량이 모의되는 것으로 나타났다. 이처럼 GCM별로 다양한 결과가 모의되기 때문에 농업시설 설계에 적용되는 설계용수량의 경우 안전성을 위하여 Multi-GCM models을 활용할 필요가 있다. Multi-model ensemble의 RCP 4.5와 RCP 8.5 시나리오를 적용한 결과, 모든 경우에서 1995s(1981-2014)에 비해 설계용수량은 점차적으로 증가하는 것으로 나타났다. 평균 증가율은 RCP 4.5에서 중부지역이 9.4%, 남부지역이 6.0% 증가하는 것으로 나타난 반면, RCP 8.5에서는 중부지역이 11.1%, 남부지역이 8.2% 증가하는 것으로 나타났다. 또한 여러 GCM 산출물간의 불확실성은 RCP 4.5보다는 RCP 8.5 시나리오가, 중부 지역보다는 남부 지역이, 논벼 증발산량 보다는 유효우량이 더 큰 것으로 분석되었다. 본 연구는 향후 미래 가뭄 위험성을 최소화하기 위한 농업 수자원관리 전략수립에 활용될 수 있을 것이다. 또한 본 연구결과는 기후변화 영향 평가에 있어서 적합한 GCM 자료를 선택하는데 있어, 불확실성을 가늠할 수 있는 유용한 척도로 이용될 수 있을 것으로 기대된다.

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SWAT모형과 CMIP5 자료를 이용한 기후변화에 따른 농업용 저수지 기후변화 영향 평가 (Assessing the Climate Change Impacts on Agricultural Reservoirs using the SWAT model and CMIP5 GCMs)

  • 조재필;황세운;고광돈;김광용;김정대
    • 한국농공학회논문집
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    • 제57권5호
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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.