• 한국수자원학회논문집
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• 제34권4호
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• pp.347-356
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• 2001

장래 $C0_2$의 증가에 따른 지구 기온의 상승은 그 정도의 차이는 있으나 불가피한 것으로 예측되고 있으며, 강수량의 경우는 대기대순환모형(General Circulation Model, GeM)의 종류에 따라 감소에서 증가까지 다양한 결과를 보이고 있다. 특히, 강수량의 변화는 평균적인 개념의 연평균, 계절평균이나 월 평균도 중요하지만 국가적인 재해와 관련된 홍수나 가뭄의 발생도 중요한 관심사항이 된다. 홍수나 가뭄의 발생변화를 적절히 예측하기 위해서는 기술적인 측면에서 대 기대순환모형의 결괴를 중규모 또는 소규모 대기모형에 연계히여 한반도를 중섬으로 해석하는 것이 필요하며, 궁극적으로는 수문 모형과의 연계를 통한 지변과 대기의 상호작용에 대한 고려가 이루어져야 한다. 그러나, 국내의 경우 아직까지 대기-수문 모형의 적용이 미미한 설정이다. 본 연구에서는 Kavvas 등 (1995)이 지표면 과정과 중규모 대기모형을 접합하여 개발한 국지규모 수분대기모형인 IRSHAM96 모형(Integrated Regional Scale Hydrologic/Atmospheric M Model)을 이용하여 지구온난화에 따른 한반도 기온의 변화를 분석하였다. 이를 통해 $C0_2$ 배증에 따라 한반도의 기온은 연평균 $2.5^{\circ}C$ 정도의 상숭승이 예측되었으며, 2월과 11월의 기온은 각각 $4.5^{\circ}C$와 $5.5^{\circ}C$의 높은 상승이 예상되어 겨울이라는 계절이 짧아질 수 있을 것으로 분석되었다. 이와 같은 계절적인 변화로 인해 한반도 생태계에 커다란 변화가 초래될 가능성이 높아질 수 있으며, 다른 계절의 기온도 상대적으로 높아질 것을 감안한다면 생태계에 커다란 재양일 수 있을 것이다. 또한 겨울철의 상대적으로 높은 기온 상승은 수자원의 특성에도 커다란 변화가 생길 수 있음을 시사하고 있다.

• 환경영향평가
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• 제21권5호
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• pp.735-743
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• 2012

Since the CBD(Conservation on Biological Diversity)'s 10th Conference of the Parties adopted the protocol on access to genetic resources and benefit sharing in Nagoya 2010, the importance of endangered species studies such as habitat distribution, protection and management have been more emerged. Corylopsis coreana, an endangered species in Korea, was isolated nationally and has been damaged by anthropogenic factors. In this paper, we identified the factors affecting C. coreana habitat at the national scale and regional scale using National Survey of Natural Environment and predicted the distribution of C. coreana. Annual precipitation, precipitation of wettest quarter, temperature seasonality and Digital Elevation Model(DEM) were derived as important factors at the national scale, and precipitation of wettest quarter, DEM and solar radiation on spring were identified as important factors at regional scale. Colylopsis distribution was affected by an effect of climate significantly at the national scale, and by additionally the microclimate and topography at regional scale. These findings will be used as the basis on habitat conservation and restoration plan and climate change.

• 대기
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• 제22권2호
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• pp.221-231
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• 2012

Representative Concentration Pathways (RCP) are the latest emission scenarios recommended to use for the fifth assessment report of Intergovernmental Panel on Climate Change. This study investigates the projection of extreme precipitation in South Korea during the forthcoming 21st Century using the generalized extreme value (GEV) analysis based on two different RCP conditions i.e., RCP 4.5 and 8.5. Maximum daily precipitation required for GEV analysis for RCP 4.5 and 8.5 are obtained from a high-resolution regional climate model forced by the corresponding global climate projections, which are produced within the CMIP5 framework. We found overall increase in frequency of extreme precipitation over South Korea in association with climate change. Particularly, daily extreme precipitation that has been occurred every 20 years in current climate (1980~2005) is likely to happen about every 4.3 and 3.4 years by the end of 21st Century (2070~2099) under the RCP 4.5 and 8.5 conditions, respectively.

• Journal of Forest and Environmental Science
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• 제30권2호
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• pp.189-200
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• 2014

The tropical wet evergreen, tropical semi evergreen and moist deciduous forest types are projected to be impacted by climate change. In the Western Ghats region, a biodiversity hotspot, evergreen forests including semi evergreen account for 30% of the forest area and according to climate change impact model projections, nearly a third of these forest types are likely to undergo vegetation type change. Similarly, tropical moist deciduous forests which account for about 28% of the forest area are likely to experience change in about 20% of the area. Thus climate change could adversely impact forest biodiversity and product flow to the forest dependent households and communities in Uttara Kannada district of the Western Ghats. This study analyses the distribution of non-timber forest product yielding tree species through a network of twelve 1-ha permanent plots established in the district. Further, the extent of dependence of communities on forests is ascertained through questionnaire surveys. On an average 21% and 28% of the tree species in evergreen and deciduous forest types, respectively are, non-timber forest product yielding tree species, indicating potential high levels of supply of products to communities. Community dependence on non-timber forest products is significant, and it contributes to Rs. 1199 and Rs. 3561/household in the evergreen and deciduous zones, respectively. Given that the bulk of the forest grids in Uttara Kannada district are projected to undergo change, bulk of the species which provide multiple forest products are projected to experience die back and even mortality. Incorporation of climate change projections and impacts in forest planning and management is necessary to enable forest ecosystems to enhance resilience.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.343-346
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• 2002

Toward more accurate determination of the water cycle in association with climate variability and change as well as baseline data on the impacts of this variability on water resources, the Coordinated Enhanced Observing Period (CEOP) was launched on July 1,2001. The preliminary data period, EOP-1, was implemented from July to September in 2001. The first annual enhanced observing period, EOP-3, is going to start on October 1,2002. CEOP is seeking to achieve a database of common measurements from both in situ and satellite remote sensing, model output, and four-dimensional data analyses (4DDA; including global and regional reanalyses) for a specified period. In this context a number of carefully selected reference stations are linked closely with the existing network of observing sites involved in the GEWEX Continental Scale Experiments, which are distributed across the world. The initial step of CEOP is to develop a pilot global hydro-climatological dataset with global consistency under the climate variability that can be used to help validate satellite hydrology products and evaluate, develop and eventually predict water and energy cycle processes in global and regional models. Based on the dataset, we will address the studies on the inter-comparison and inter-connectivity of the monsoon systems and regional water and energy budget, and a path to down-scaling from the global climate to local water resources, as the second step.

• 대기
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• 제31권5호
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1388-1392
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• 2008

Water resources management depends on dealing inherent uncertainties stemming from climatic and hydrological inputs and models. Dealing with these uncertainties remains a challenge. Streamflow forecasts basically contain uncertainties arising from model structure and initial conditions. Recent enhancements in climate forecasting skill and hydrological modeling provide an breakthrough for delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The approach here proposes integration and coupling of global climate models (GCM), multiple regional climate models, and numerous hydrological models to improve streamflow forecasting and characterize system uncertainty through generation of ensemble forecasts.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.229-229
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• 2015

Downscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods in order to assess whether each method can model the climate conditions at various spatial scales properly. This study introduces a fundamental research from Jang and Kavvas(2015) that precipitation variability from a popular statistical downscaling method (BCSD) and a dynamical downscaling method (MM5) that is based on the NCAR/NCEP reanalysis data for a historical period and on the CCSM3 GCM A1B emission scenario simulations for a projection period, is investigated by means of some spatial characteristics: a) the normalized standard deviation (NSD), and b) the precipitation change over Northern California region. From the results of this study it is found that the BCSD method has limitations in projecting future precipitation values since the BCSD-projected precipitation, being based on the interpolated change factors from GCM projected precipitation, does not consider the interactions between GCM outputs and local geomorphological characteristics such as orographic effects and land use/cover patterns. As such, it is not clear whether the popular BCSD method is suitable for the assessment of the impact of future climate change at regional, watershed and local scales as the future climate will evolve in time and space as a nonlinear system with land-atmosphere feedbacks. However, it is noted that in this study only the BCSD procedure for the statistical downscaling method has been investigated, and the results by other statistical downscaling methods might be different.

• Asian Journal of Innovation and Policy
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• 제10권2호
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• pp.212-235
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• 2021

In spite of the increasing popularity of the Ricardian model for the study of the impact of climate change on agriculture, there has been few attempts to examine the role of interregional spillovers in this framework and all of them rely on geographical proximity-based weighting schemes. We remedy to this gap by focusing on the spatial externalities of surface water flow used for irrigation purposes and demonstrate that farmland value, the usual dependent variable used in the Ricardian framework, is a function of the climate variables experienced locally and in the upstream locations. This novel approach is tested empirically on a spatial panel model estimated across the counties of the Southwest USA over 1997-2012. This region is one of the driest in the country, hence its agriculture relies heavily on irrigated surface water. The results highlight how the weather conditions in upstream counties significantly affect downstream agriculture, thus the actual impact of climate change on agriculture and subsequent adaptation policies cannot overlook the streamflow network anymore.

• 한국지리정보학회지
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• 제23권4호
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• pp.120-139
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• 2020

본 연구에서는 CLUE-s(Conversion of Land Use and its Effects at Small regional extent)와 RCP(Representative Concentration Pathway) 4.5 및 8.5 HadGEM3-RA(Hadley Centre Global Environmental Model version 3 Regional Atmosphere)시나리오를 사용하여 미래 농지이용 변화와 기후변화가 관개 필요수량에 미치는 영향을 평가하였다. 논산시(55,517.9ha)의 농지이용 항목으로 논, 밭, 시설재배지를 고려하고 DIROM (Daily Irrigation Reservoir Operation Model)을 이용해 탑정저수지 수혜구역(5,713.3ha)에 대한 관개 필요수량(Irrigation Water Requirement, IWR)을 추정하였다. CLUE-s를 이용한 미래 농지이용 변화를 모의하기 위해 환경부의 2007년, 2013년, 2019년의 토지피복도 6개 항목(수역, 시가지, 논, 밭, 산림, 시설재배지)을 적용하였다. 그 결과, 2100년은 2013년에 비해 논과 밭이 5.0%, 7.6% 감소했으며, 시설재배지는 24.7% 증가하는 것으로 전망되었다. 미래의 농지이용과 기후변화를 모두 고려한 경우의 RCP 4.5 및 RCP 8.5 모두 2090s(2090~2099) IWR은 미래 기후변화만 고려한 경우에 비해 논과 밭에서는 각각 2.1%, 1.0% 감소하고 시설재배지에서는 11.4% 증가하는 것으로 전망되었다.