• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.1
• /
• pp.64-75
• /
• 2012

To predict the future distribution of forest vegetation, the present forest stand distributions of South Korea were represented by multinomial logit model with the following environmental variables: summer average precipitation, the coldest month average temperature, elevation, degree of base saturation, and soil organic matter. The future forest community was predicted by applying the MIROC3.2 hires A1B scenario. The future climate data were downscaled by statistically method. The coldest month average temperature increased $4.4^{\circ}C$, $6.0^{\circ}C$, and $9.4^{\circ}C$, and 3 months average precipitation changed -1.2%, 5.7%, and 5.3% for 2020s, 2050s, and 2080s respectively. For the projected summer precipitation and the coldest temperature, the future deciduous and mixed forests in the study area increased 56.9% and 8.3% and the coniferous forest decreased 11.2% in 2080s based on present.

• Ocean and Polar Research
• /
• v.34 no.2
• /
• pp.253-264
• /
• 2012

In the northwestern Pacific, spawning of the common squid, Todarodes pacificus, occurs at continental shelf and slope areas of 100-500 m, and the optimum temperature for the spawning and survival of paralarvae is assumed to be $18-23^{\circ}C$. To predict the spawning ground of Todarodes pacificus under future climate conditions, we simulated the present and future ocean circulations, using an East Asia regional ocean model (Modular Ocean Model, MOM version3), projected by two different global climate models (MPI_echam5, MIROC_hires), under an IPCC SRES A1B emission scenario. Mean climate states for 1990-1999 and 2030-2039 from 20th and 21th Century Climate Change model simulation (from the IPCC 4th Assessment Report) were used as surface conditions for simulations, and we examined changes in spawning ground between the 1990s and 2030s. The results revealed that the distribution of spawning ground in the 2030s in both climate models shifted northward in the East China Sea and East Sea, for both autumn and winter populations, compared to that of the 1990s. Also, the spawning area (with $1/6^{\circ}{\times}1/6^{\circ}$ grid) in the 2030s of the autumn and winter populations will decline by 11.6% (MPI_echam5) to 30.8% (MIROC_hires) and 3.0% (MPI_echam5) to 18.2% (MIROC_hires), respectively, from those of the 1990s.

• KCID journal
• /
• v.21 no.1
• /
• pp.89-98
• /
• 2014

This study is to evaluate the future potential impact of climate change on soil erosion loss in a metropolitan area using Revised Universal Soil Loss Equation(RUSLE) with land use information of the Ministry of Environment and rainfall data for present and future years(30-year period). The spatial distribution map of vulnerable areas to soil erosion was prepared to provide the basis information for soil conservation and long-term land use planning. For the future climate change scenario, the MIROC3.2 HiRes A1B($CO_2720ppm$ level 2100) was downscaled for 2040-2069(2040s) and 2070-2099(2080s) using the stochastic weather generator(LARS-WG) with average rainfall data during past 30 years(1980-2010, baseline period). By applying the climate prediction to the RUSLE, the soil erosion loss was evaluated. From the results, the soil erosion loss showed a general tendency to increase with rainfall intensity. The soil loss increased up to 13.7%(55.7 ton/ha/yr) in the 2040s and 29.8%(63.6 ton/ha/yr) in the 2080s based on the baseline data(49.0 ton/ha/yr).

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.271-271
• /
• 2015

The Ecuadorian coast has two different climate regions. One is humid region where the annual rainfall is above 2000 mm and rain falls in almost all months of the year, and the other is dry region where the annual rainfall can fall below 50 mm and rainfall can be very seasonal. The agriculture is frequently limited by the seasons during the year and the availability of rainfall amounts. The corn fields in Ecuador are cultivated during the rainy season, due to this reason. The weather conditions for optimum development of corn growth require a monthly average rainfall of 120 mm to 140 mm and a temperature range of $22^{\circ}C{\sim}32^{\circ}C$ for the dry region, and a monthly average rainfall of 200 mm to 400 mm and a temperature range of $25^{\circ}C{\sim}30^{\circ}C$ for the humid area. The objective of this study is to predict how the weather conditions are going to change in corn fields of the coastal region of Ecuador in the future decades. For this purpose, this study selected six General Circulation Models (GCM) including BCC-CSM1-1, IPSL-CM5A-MR, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, MRIC-CGC3 with different climate scenarios of the RCP 4.5, RCP 6.0, and RCP 8.5, and applied for the period from 2011 to 2100. The climate variables information was obtained from the INAMHI (National Institute of Meteorology and Hydrology) in Ecuador for the a base line period from 1986 to 2012. The results indicates that two regions would experience significant changes in rainfall and temperature compared to the historical data. In the case of temperature, an increment of $1^{\circ}C{\sim}1.2^{\circ}C$ in 2025s, $1.6^{\circ}C{\sim}2.2^{\circ}C$ in 2055s, $2.1^{\circ}C{\sim}3.5^{\circ}C$ in 2085s were obtained from the dry region while less increment were shown from the humid region with having an increment of $1^{\circ}C$ in 2025s, $1.4^{\circ}C{\sim}1.8^{\circ}C$ in 2055s, $1.9^{\circ}C{\sim}3.2^{\circ}C$ in 2085s. Significant changes in rainfall are also projected. The rainfall projections showed an increment of 8%~11% in 2025s, 21%~33% in 2055s, and 34%~70% in 2085s for the dry region, and an increment of 2%~10%, 14%~30% and 23%~57% in 2025s, 2055s and 2085s decade respectively for humid region.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2014.10a
• /
• pp.1-24
• /
• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.307-307
• /
• 2019

General Ciculation Model (GCM) 모형에 대한 평가를 본 연구에서 수행한다. 모형의 적용을 위해서는 국지적 일 강우량 및 기온자료를 이용한다. 31개의 GCM 모의를 통해 도출되는 결과가 성능 평가에서 활용되었다. 일 최대, 최소 기온와 강우량이 파키스탄 지역을 대상으로 모의되었다. 모의를 위해서는 Gridded 데이터가 적용되었으며 각각 Asian Precipitation-Highly-Resolved Observational Data Integration Toward Evaluation, Berkeley Earth Surface Temperature, Princeton Global Meteorological Forcing, Climate Prediction Centre에 해당된다. GCM의 순위를 결정하기 위해서는 Symmetrical Uncertainty 방법이 이용된다. 결과를 통해서 Gridded 데이터의 종류에 따라 가장 높은 효율을 나타내는 GCM의 공간 분포가 달라진다는 점을 확인하였다. 이러한 특성은 기온과 강우량 자료 모두에서 확인된다. 기온의 경우에는 Commonwealth Scientific and Industrial Research Organization, Australia-MK3-6-0과 Max Planck Institute-ESM-LR이 우수한 결과를 모의하는 것으로 나타났다. 반면 강우량의 경우에는 EC-Earth와 MIROC가 우수한 것으로 나타났다. 파키스탄 지역에서의 기온 및 강우량 자료의 합리적 반영을 위해서는 ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES, MIRCO5와 같은 6개 GCM을 이용하였을 때 다양한 기상 인자를 고려한 모의가 가능한 것으로 평가된다.

• Journal of Korea Water Resources Association
• /
• v.52 no.5
• /
• pp.337-347
• /
• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

• Korean Journal of Plant Taxonomy
• /
• v.50 no.2
• /
• pp.154-165
• /
• 2020

Coastal regions are experiencing habitat changes due to coastal development and global warming. To estimate the future distribution of coastal plants on the Korean Peninsula due to climate change, the potential distribution of ten species of coastal plants was analyzed using the MaxEnt program. The study covered the eastern, western, and southern coastal areas of the Korean Peninsula. We used the distributional data of coastal plants of the East Asian region and the 19 climate variables of WorldClim 2.0. The future potential distribution was estimated using future climate variables projected from three general circulation models (CCSM4, MIROC-ESM, and MPI-ESM-LR), four representative concentration pathways (2.5, 4.5, 6.0, and 8.5), and two time periods (2050 and 2070). The annual mean temperature influenced the estimation of the potential distribution the most. Under predicted future distribution scenarios, Lathyrus japonicus, Glehnia littoralis, Calystegia soldanella, Vitex rotundifolia, Scutellaria strigillosa, Linaria japonica, and Ixeris repens are expected to show contracted distributions, whereas the distribution of Cnidium japonicum is expected to expand. Two species, Salsola komarovii and Carex kobomugi, are predicted to show similar distributions in the future compared to those in the present. The average potential distribution in the future suggests that the effects of climate change will be greater in the west and the south coastal regions than in the east coastal region. These results will be useful baseline data to establish a conservation strategy for coastal plants.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.48-48
• /
• 2011

본 연구에서는 미래 기후변화가 하천 및 호소수질에 미치는 영향을 평가하고자 유역 수문-수질 모의가 가능한 SWAT(Soil and water assessment tool) 모형과 호소수질 모의가 가능한 WASP(Water Quality Simulation Program) 모형을 연계운영하여 충주호를 포함하는 충주댐 유역($6,642.0km^2$)에 적용하였다. 이를 위해 IPCC(Intergovernmental panel on climate change)에서 제공하는 A1B 배출시나리오를 포함하는 MIROC3.2 hires 모형의 결과로부터 충주댐 유역의 총 6개 기상관측소에 대한 과거 30년(1997~2006) 실측자료를 바탕으로 미래 온도와 강수에 대한 편이보정(Bias correction) 및 Change Factor Method로 상세화(Downscaling)하여 미래 기후자료(2020s, 2050s, 2080s)를 생산하였다. 미래 연평균 온도는 기준년도인 2000년에 비해 최대 $+4.8^{\circ}C$(2080s)의 온도증가를 보였으며, 강수량의 경우 여름과 가을 강수량이 다소 감소하였으나 연평균 강수량은 최대 +34.4%(2080s) 증가하는 것으로 전망되었다. 먼저, SWAT 모형을 이용한 기후변화에 따른 댐 유입량은 39.8%(2080s) 증가는 것으로 분석되었으며 유역의 유출특성 변화로 인한 유사량은 지표유출변화에 기인하여 봄과 겨울에 증가하는 경향과 함께 -14.5%(2020s) ~ +27.3%(2080s)의 변화를 보이는 것으로 분석되었다. 영양물질에 대한 오염부하량은 2080s에서 T-N이 증가추세를 보이며 최대 87.3% 까지 증가하는 반면, T-P는 유사량과 유사한 변화패턴을 보이며 최대 48.4%까지 감소하는 것으로 분석되었다. 호소수질 모델링을 위한 충주호의 Segment 구성은 충주댐1 지점에서부터 충주댐4 지점까지 전체 수표면적 $65.7km^2$에 대하여 상층과 하층 총 760개로 구성하였으며, SWAT 모형에 의한 충주호 유입하천 소유역에서의 미래 유출 및 영양물질 자료를 WASP 모형의 초기값으로 입력하여 수체 내의 BOD, Chl-a, T-N, T-P 변화 분석을 실시하였다. 이와 같이 지구 온난화에 의한 기후변화는 강우특성 변화에 따른 가뭄과 홍수 등 극한 기상현상의 발생, 유역 물순환 체계 변화를 야기 시키므로서 수자원 부존량 변화에 영향을 미칠 뿐만 아니라 기온상승에 따른 수온변화, 비점오염물질의 거동에도 변화를 초래하여 하천 및 호소 수질에 큰 영향을 미칠 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.57-61
• /
• 2009

본 연구에서는 SWAT(Soil and Water Assessment Tool) 모형을 이용하여 미래 기후변화가 댐 유역의 하천수질에 미치는 영향을 분석하였다. 충주댐 상류유역($6,585.1km^2$)에 대해 민감도 분석을 통해 최적의 유출및 유사관련 매개변수를 선정하였으며, 충주호 유입하천 상류 2개 지점/영월1, 영월2)과 유역 출구점을 대상으로 일별 유출량 및 월별 수질자료를 바탕으로 모형의 보정(1998-2000)및 검증(2001-2003)을 실시하였다. 미래 기후자료는 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 SRES/Special Report on Emission Scenarios) A2, A1B, B1 기후변화시나리오의 MIROC3.2 hires와 ECHAM5-OM 모델의 결과 값을 이용하였다. 먼저 과거 30년 기후자료(1977-2006, baseline)를 바탕으로 각 모델별 20C3M(20th Century Climate Coupled Model)의 모의 결과 값을 이용하여 강수와 온도를 보정한 뒤 Change Factor(CF) Method로 Downscaling 하였으며, 미래 기후변화 시나리오는 2020s, 2050s, 2080s의 세 기간으로 나누어 각각 분석 하였다. 기후변화 시나리오 적용에 따른 SWAT 모의결과로부터 기후변화가 수문학적 거동 및 하천수질에 미치는 영향을 평가하였다.