• Title/Summary/Keyword: Representative Concentration Pathway(RCP)

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Comparison of climate extremes under different RCP-SSP scenarios (RCP 및 SSP 기후변화 시나리오 기반 극한기후사상 전망 비교)

  • Jae-Ung Yu;Ji sung Kim;Yoon Jeong Kwon;Jangwon Moon;Hyun-Han Kwon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.285-285
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    • 2023
  • 기후변화로 인한 변동성의 증가는 돌발 홍수, 홍수량 증가로 이외에도 강우 사상의 변화, 가뭄의 빈도 및 강도의 증대 등의 문제를 이어질 수 있다. 이러한 기후변화에 대응하기 위하여 기후변화 시나리오를 제시하고 이를 정책적으로 반영할 수 있도록 하고 있다. 기존 IPCC 5차 보고서에 활용한 RCP(Representative Concentration Pathway) 시나리오에서는 온실가스 농도변화만을 반영하고 있으나, 최근 IPCC 6차 보고서에서는 사회적인 노력과 경제적 구조 등 전반적인 기후정책, 사회 불균형 등을 고려한 SSP(Shared Socio-economic Pathways) 시나리오를 제시하였다. 본 연구에서는 2가지 기후변화 시나리오의 차이점과 유사점을 강수 중심으로 평가하였다. 기존의 RCP 시나리오에 비하여 극한 강우 사상의 변화를 비교 및 평가하기 위하여 CORDEX-EA에서 제공하는 지역기후모델(Regional Climate Model; RCM) 기반에 시나리오를 수집하여 극한기후지수를 산정하였다. 극한기후사상을 비교하기 위하여 WMO에서 활용하는 ETCCDI(Expert Team on Climate Change Detection and Indices) 지수 중 강우 관련 지수인 R10mm, RX1day, RX5day, RD95P, RD99P, SDII를 선정하여 시나리오 별로 결과를 비교하여 제시하였다. 또한, 기존의 연대기 기준의 평가방식에서 탈피하여 동일한 기온 상승 시점에 따라 변화를 확인하기 위한 분석절차를 수립하였다. 즉, 1.5℃, 2℃, 3℃ 및 4℃ 상승한 시점의 ETCCDI 지수를 산정하여 극한기후사상을 비교 및 평가하였다.

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Spatio-temporal variability of future wind energy over the Korean Peninsular using Climate Change Scenarios (기후변화 시나리오를 활용한 한반도 미래 풍력에너지의 시공간적 변동성 전망)

  • Kim, Yumi;Lim, Yoon-Jin;Lee, Hyun-Kyoung;Choi, Byoung-Choel
    • Journal of the Korean Geographical Society
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    • v.49 no.6
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    • pp.833-848
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    • 2014
  • The assessment of the current and future climate change-induced potential wind energy is an important issue in the planning and operations of wind farm. Here, the authors analyze spatiotemporal characteristics and variabilities of wind energy over Korean Peninsula in the near future (2006-2040) using Representative Concentration Pathway(RCP) scenarios data. In this study, National Institute of Meteorological Research (NIMR) regional climate model HadGEM3-RA based RCP 2.6 and 8.5 scenarios are analyzed. The comparison between ERA-interim and HadGEM3-RA during the period of 1981-2005 indicates that the historical simulation of HadGEM3-RA slightly overestimates (underestimates) the wind energy over the land (ocean). It also shows that interannual and intraseasonal variability of hindcast data is generally larger than those of reanalysis data. The investigation of RCP scenarios based future wind energy presents that future wind energy density will increase over the land and decrease over the ocean. The increase in the wind energy and its variability is particularly significant over the mountains and coastal areas, such as Jeju island in future global warming. More detailed analysis presents that the changes in synoptic conditions over East Asia in future decades can influence on the predicted wind energy abovementioned. It is also suggested that the uncertainty of the predicted future wind energy may increase because of the increase of interannual and intra-annual variability. In conclusion, our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

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Assessment on Damage Risk of Corn for High Temperature at Reproductive Stage in Summer Season Based on Climate Scenario RCP 8.5 and 4.5

  • Seo, Myung-Chul;Cho, Hyeon-Suk;Kim, Jun-Hwan;Sang, Wan-Gyu;Shin, Pyeong;Lee, Geon Hwi
    • Korean Journal of Soil Science and Fertilizer
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    • v.50 no.1
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    • pp.1-11
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    • 2017
  • In order to assess risk of high temperature damages about corn during reproduction stages in the future, we carried out analysis of climate change scenarios RCP (Representative Concentration Pathway) 4.5 and RCP8.5 distributed by KMA (Korea Meteorological Administration) in 2012. We established two indexes such as average of annual risk days of high temperature damage which express frequency and strengthen index of high temperature damage. As results of producing maps for 157 cities and counties about average of annual risk days of high temperature damage during total periods of scenarios, the risk of high temperature in RCP8.5 was evaluated to increase at all over nation except inland area of Gangwon province, while RCP4.5 showed similar to present, or little higher. The maps of annual risk days of high temperature damage with 10 years interval in RCP8.5 prospected that the risk for damaging corn growth would increase rapidly from 2030's. The largest risk of high temperature damage in the future of RCP8.5 was analyzed at Changnyeong county located east-south inland area in Kyeongnam province, while the smallest of risk counties were Pyeongchang, Taebaek, Inje, and Jeongseon. The prospect at 12 counties which is large to produce corn at present and contains large plains have been showed that there will be only a little increase of risk of high temperature at Goesan, Yangpyeong, Hongcheon, Seosan, and Mooju until 2060's. But considering strengthen index of high temperature damage, most regions analyzed would be prospected to increase rapidly after 2030's. To cope with high temperature damage of corn in the future, we should develop various practical technologies including breeding adapted varieties and controlling cultivation periods.

A probabilistic framework for drought forecasting using hidden Markov models aggregated with the RCP8.5 projection

  • Chen, Si;Kwon, Hyun-Han;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.197-197
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    • 2016
  • Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.

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Prediction of potential habitats and distribution of the marine invasive sea squirt, Herdmania momus

  • Park, Ju-Un;Lee, Taekjun;Kim, Dong Gun;Shin, Sook
    • Korean Journal of Environmental Biology
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    • v.38 no.1
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    • pp.179-188
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    • 2020
  • The influx of marine exotic and alien species is disrupting marine ecosystems and aquaculture. Herdmania momus, reported as an invasive species, is distributed all along the coast of Jeju Island and has been confirmed to be distributed and spread to Busan. The potential habitats and distribution of H. momus were estimated using the maximum entropy (MaxEnt) model, quantum geographic information system (QGIS), and Bio-ocean rasters for analysis of climate and environment(Bio-ORACLE), which can predict the distribution and spread based only on species occurrence data using species distribution model (SDM). Temperature and salinity were selected as environmental variables based on previous literature. Additionally, two different representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) were set up to estimate future and potential habitats owing to climate change. The prediction of potential habitats and distribution for H. momus using MaxEnt confirmed maximum temperature as the highest contributor(77.1%), and mean salinity, the lowest (0%). And the potential habitats and distribution of H. momus were the highest on Jeju Island, and no potential habitat or distribution was seen in the Yellow Sea. Different RCP scenarios showed that at RCP 4.5, H. momus would be distributed along the coast of Jeju Island in the year 2050 and that the distribution would expand to parts of the Korea Strait by the year 2100. RCP 8.5, the distribution in 2050 is predicted to be similar to that at RCP 4.5; however, by 2100, the distribution is predicted to expand to parts of the Korea Strait and the East Sea. This study can be utilized as basic data to effectively control the ecological injuries by H. momus by predicting its spread and distribution both at present and in the future.

Analysis and estimation of species distribution of Mythimna seperata and Cnaphalocrocis medinalis with land-cover data under climate change scenario using MaxEnt (MaxEnt를 활용한 기후변화와 토지 피복 변화에 따른 멸강나방 및 혹명나방의 한국 내 분포 변화 분석과 예측)

  • Taechul Park;Hojung Jang;SoEun Eom;Kimoon Son;Jung-Joon Park
    • Korean Journal of Environmental Biology
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    • v.40 no.2
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    • pp.214-223
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    • 2022
  • Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

Prediction of future hydrologic variables of Asia using RCP scenario and global hydrology model (RCP 시나리오 및 전지구 수문 모형을 활용한 아시아 미래 수문인자 예측)

  • Kim, Dawun;Kim, Daeun;Kang, Seok-koo;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.49 no.6
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    • pp.551-563
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    • 2016
  • According to the 4th and 5th assessment of the Intergovernmental Panel on Climate Change (IPCC), global climate has been rapidly changing because of the human activities since Industrial Revolution. The perceived changes were appeared strongly in temperature and concentration of carbon dioxide ($CO_2$). Global average temperature has increased about $0.74^{\circ}C$ over last 100 years (IPCC, 2007) and concentration of $CO_2$ is unprecedented in at least the last 800,000 years (IPCC, 2014). These phenomena influence precipitation, evapotranspiration and soil moisture which have an important role in hydrology, and that is the reason why there is a necessity to study climate change. In this study, Asia region was selected to simulate primary energy index from 1951 to 2100. To predict future climate change effect, Common Land Model (CLM) which is used for various fields across the world was employed. The forcing data was Representative Concentration Pathway (RCP) data which is the newest greenhouse gas emission scenario published in IPCC 5th assessment. Validation of net radiation ($R_n$), sensible heat flux (H), latent heat flux (LE) for historical period was performed with 5 flux tower site-data in the region of AsiaFlux and the monthly trends of simulation results were almost equaled to observation data. The simulation results for 2006-2100 showed almost stable net radiation, slightly decreasing sensible heat flux and quite increasing latent heat flux. Especially the uptrend for RCP 8.5 has been about doubled compared to RCP 4.5 and since late 2060s, variations of net radiation and sensible heat flux would be significantly risen becoming an extreme climate condition. In a follow-up study, a simulation for energy index and hydrological index under the detailed condition will be conducted with various scenario established from this study.

The Study of Adaptable Plant Species to the Change of Warmth Index by Using RCP4.5 and RCP8.5 Scenarios in Seoul City (RCP4.5와 8.5 시나리오를 이용한 온량지수 변화에 따른 서울시 적응 가능한 식물종 연구)

  • Kong, Seok-Jun;Kim, Jeong-Seob;Yang, Keum-Chul;Kim, Kyeong-Jin
    • Journal of Wetlands Research
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    • v.17 no.3
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    • pp.273-282
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    • 2015
  • This study suggested the adaptable plant species according to the change of warmth index (WI) through the Representative Concentration Pathway (RCP) 4.5 & 8.5 climate change scenarios from 2010 to 2099 in Seoul areas. From the scenario analysis results, we expected to change from the cool temperate souther forest zone to the warm temperate forest zone. We found the following adaptable 27 plant species: 6 species in the tree layer, Quercus serrata, Q. variabilis, Pinus densiflora, Q. acutissima, Styrax japonica and P. thunbergii etc.; 7 species in the shrub layer, Ligustrum obtusifolium, Lespedeza maximowiczii, Rhus trichocarpa, Callicarpa japonica, Rubus crataegifolius, Rosa multiflora, and Zanthoxylum piperitum etc.; 3 species in the herb layer, Oplismenus undulatifolius, Pteridium aquilinum var. latiusculum, and Commelina communis ect;, 11 species in the vine plants Smilax china, Cocculus trilobus, Parthenocissus tricuspidata, Lonicera japonica, Paederia scandens, Celastrus orbiculatus, Clematis apiifolia, Rubus parvifolius, Dioscorea batatas, Hydrangea serrata for. acuminata, Zelkova serrata etc.

Near Future Projection of Extreme Temperature over CORDEX-East Asia Phase 2 Region Using the WRF Model Based on RCP Scenarios (RCP 시나리오 기반 WRF를 이용한 CORDEX-동아시아 2단계 지역의 가까운 미래 극한기온 변화 전망)

  • Seo, Ga-Yeong;Choi, Yeon-Woo;Ahn, Joong-Bae
    • Atmosphere
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    • v.29 no.5
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    • pp.585-597
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    • 2019
  • This study evaluates the performance of Weather Research and Forecasting (WRF) model in simulating temperature over the COordinated Regional climate Downscaling EXperiment-East Asia (CORDEX-EA) Phase 2 domain for the reference period (1981~2005), and assesses the changes in temperature and its extremes in the mid-21st century (2026~2050) under global warming based on Representative Concentration Pathway (RCP) scenarios. MPI-ESM-LR forced by two RCP scenarios (RCP2.6 and RCP8.5) is used as initial and lateral boundary conditions. Overall, WRF can capture the observed features of temperature distribution reflecting local topographic characteristic, despite some disagreement between the observed and simulated patterns. Basically, WRF shows a systematic cold bias in daily mean, minimum and maximum temperature over the entire domain. According to the future projections, summer and winter mean temperatures over East Asia will significantly increase in the mid-21st century. The mean temperature rise is expected to be greater in winter than in summer. In accordance with these results, summer (winter) is projected to begin earlier (later) in the future compared to the historical period. Furthermore, a rise in extreme temperatures shows a tendency to be greater in the future. The averages of daily minimum and maximum temperatures above 90 percentiles are likely to be intensified in the high-latitude, while hot days and hot nights tend to be more frequent in the low-latitude in the mid-21st century. Especially, East Asia would be suffered from strong increases in nocturnal temperature under future global warming.

Future Prediction of Heat and Discomfort Indices based on two RCP Scenarios (기후변화 대응을 위한 RCP 시나리오 기반 국내 열지수와 불쾌지수 예측)

  • Lee, Suji;Kwon, Bo Yeon;Jung, Deaho;Jo, Kyunghee;Kim, Munseok;Ha, Seungmok;Kim, Heona;Kim, Byul Nim;Masud, M.A.;Lee, Eunil;Kim, Yongkuk
    • Atmosphere
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    • v.23 no.2
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    • pp.221-229
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    • 2013
  • There has been an increasing need to assess the effects of climate change on human health. It is hard to use climate data to evaluate health effects because such data have a grid format, which could not represent specific cities or provinces. Therefore, the grid-format climate data of South Korea based on RCP (Representative Concentration Pathway) scenarios were modified into area-format climate data according to the major cities or provinces of the country, up to the year 2100. Moreover, heat index (HI) and discomfort index (DI) databases were developed from the modified climate database. These databases will soon be available for experts via a Website, and the expected HI and DI of any place in the country, or at any time, can be found in the country's climate homepage (http://www.climate.go.kr). The HI and DI were analyzed by plotting the average indices every ten years, and by comparing cities or provinces with index level changes, using the geographic information system (GIS). Both the HI and DI are expected to continually increase from 2011 to 2100, and to reach the most dangerous level especially in August 2100. Among the major cities of South Korea, Gwangju showed the highest HI and DI, and Gangwon province is expected to be the least affected area in terms of HI and DI among all the country's provinces.