• Title/Summary/Keyword: climate(氣候)

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Assessment of water supply reliability under climate stress scenarios (기후 스트레스 시나리오에 따른 국내 다목적댐 이수안전도 평가)

  • Jo, Jihyeon;Woo, Dong Kook
    • Journal of Korea Water Resources Association
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    • v.57 no.6
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    • pp.409-419
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    • 2024
  • Climate change is already impacting sustainable water resource management. The influence of climate change on water supply from reservoirs has been generally assessed using climate change scenarios generated based on global climate models. However, inherent uncertainties exist due to the limitations of estimating climate change by assuming IPCC carbon emission scenarios. The decision scaling approach was applied to mitigate these issues in this study focusing on four reservoir watersheds: Chungju, Yongdam, Hapcheon, and Seomjingang reservoirs. The reservoir water supply reliablity was analyzed by combining the rainfall-runoff model (IHACRES) and the reservoir operation model based on HEC-ResSim. Water supply reliability analysis was aimed at ensuring the stable operation of dams, and its results ccould be utilized to develop either structural or non-structural water supply plans. Therefore, in this study, we aimed to assess potential risks that might arise during the operation of reserviors under various climate conditions. Using observed precipitation and temperature from 1995 to 2014, 49 climate stress scenarios were developed (7 precipitation scenarios based on quantiles and 7 temperature scenarios ranging from 0℃ to 6℃ at 1℃ intervals). Our study demonstrated that despite an increase in flood season precipitation leading to an increase in reservoir discharge, it had a greater impact on sustainable water management compared to the increase in non-flood season precipitation. Furthermore, in scenarios combining rainfall and temperature, the reliability of reservoir water supply showed greater variations than the sum of individual reliability changes in rainfall and temperature scenarios. This difference was attributed to the opposing effects of decreased and increased precipitation, each causing limitations in water and energy-limited evapotranspiration. These results were expected to enhance the efficiency of reservoir operation.

The Development and Effects of Climate Literacy Program on Elementary School Students Focused on the Keeling Curve Activities Highlighting Inquiry Process (초등학생의 기후소양 함양을 위한 프로그램 개발 및 효과 : 탐구과정이 강조된 킬링 곡선(Keeling Curve) 활동을 중심으로)

  • Son, Jun-ho
    • Journal of the Korean Society of Earth Science Education
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    • v.9 no.3
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    • pp.292-308
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    • 2016
  • The purpose of this study was to find out the effects of climate change education program focused on the keeling curve activities highlighting inquiry process on elementary students' climate literacy. Most of the students have not been able to correctly understand just how serious phenomenon that the temperature rise of the last 100 years is. As a result, there is educational limitations in order to bring about a substantial change in the attitudes toward climate change. So the development program was applied to various questions and explored strategies in order to compare with past climate change data. The results described that 46 students in the experimental group had statistically significant effects on cognitive domain, critical thinking of affective domain and practical domain. In addition, as a result of the analysis of teachers' instructional perspectives and students interview, they supported the researcher's opinion that the developed program could help students improve the climate literacy.

Monthly Changes in Temperature Extremes over South Korea Based on Observations and RCP8.5 Scenario (관측 자료와 RCP8.5 시나리오를 이용한 우리나라 극한기온의 월별 변화)

  • Kim, Jin-Uk;Kwon, Won-Tae;Byun, Young-Hwa
    • Journal of Climate Change Research
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    • v.6 no.2
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    • pp.61-72
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    • 2015
  • In this study, we have investigated monthly changes in temperature extremes in South Korea for the past (1921~2010) and the future (2011~2100). We used seven stations' (Gangneung, Seoul, Incheon, Daegu, Jeonju, Busan, Mokpo) data from KMA (Korea Meteorological Administration) for the past. For the future we used the closest grid point values to observations from the RCP8.5 scenario of 1 km resolution. The Expert Team on Climate Change Detection and Indices (ETCCDI)'s climate extreme indices were employed to quantify the characteristics of temperature extremes change. Temperature extreme indices in summer have increased while those in winter have decreased in the past. The extreme indices are expected to change more rapidly in the future than in the past. The number of frost days (FD) is projected to decrease in the future, and the occurrence period will be shortened by two months at the end of the $21^{st}$ century (2071~2100) compared to the present (1981~2010). The number of hot days (HD) is projected to increase in the future, and the occurrence period is projected to lengthen by two months at the end of the $21^{st}$ century compared to the present. The annual highest temperature and its fluctuation is expected to increase. Accordingly, the heat damage is also expected to increase. The result of this study can be used as an information on damage prevention measures due to temperature extreme events.

Development of Climate & Environment Data System for Big Data from Climate Model Simulations (대용량 기후모델자료를 위한 통합관리시스템 구축)

  • Lee, Jae-Hee;Sung, Hyun Min;Won, Sangho;Lee, Johan;Byu, Young-Hwa
    • Atmosphere
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    • v.29 no.1
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    • pp.75-86
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    • 2019
  • In this paper, we introduce a novel Climate & Environment Database System (CEDS). The CEDS is developed by the National Institute of Meteorological Sciences (NIMS) to provide easy and efficient user interfaces and storage management of climate model data, so improves work efficiency. In uploading the data/files, the CEDS provides an option to automatically operate the international standard data conversion (CMORization) and the quality assurance (QA) processes for submission of CMIP6 variable data. This option increases the system performance, removes the user mistakes, and increases the level of reliability as it eliminates user operation for the CMORization and QA processes. The uploaded raw files are saved in a NAS storage and the Cassandra database stores the metadata that will be used for efficient data access and storage management. The Metadata is automatically generated when uploading a file, or by the user inputs. With the Metadata, the CEDS supports effective storage management by categorizing data/files. This effective storage management allows easy and fast data access with a higher level of data reliability when requesting with the simple search words by a novice. Moreover, the CEDS supports parallel and distributed computing for increasing overall system performance and balancing the load. This supports the high level of availability as multiple users can use it at the same time with fast system-response. Additionally, it deduplicates redundant data and reduces storage space.

Review of Environmental Assessment for Climate Factors in Urban Planning (도시계획에서의 기후요소 평가기법에 관한 고찰)

  • Eum, Jeong-Hee
    • Journal of Environmental Policy
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    • v.11 no.1
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    • pp.27-48
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    • 2012
  • The aim of this paper is to review the environmental assessment of urban climatic factors relating to urban planning in Korea and Germany, and suggest efficient ways to consider climatic factors in the environmental assessment process for urban planning in Korea. For these purposes, current assessment systems concerning urban master plan and urban management plan in Korea were reviewed to know how urban climatic factors are assessed. Furthermore, two German cases of Strategic Environmental Assessment were investigated to know how urban climatic factors are assessed and considered in the urban and regional planning of Germany. Based on the results, efficient ways to consider climatic factors in the environmental assessment for urban planning were suggested from three aspects of factors, methods and available data for climate assessment.

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Cumulative GHG Reduction Impact Analysis by the Diffusion of Solar Thermal Energy Concerning Technologies for the Residential Sector (주거용 건물부문 태양열 기술 보급에 따른 누적 온실가스 감축 효과 분석)

  • Rhee, Dong-eun;Kim, Seung Jin;Jeon, Eui-Chan
    • Journal of Climate Change Research
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    • v.5 no.3
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    • pp.267-275
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    • 2014
  • A key driver for climate change caused by global average temperature rise is greenhouse gas cumulative emissions that stay for long term in the atmosphere. Although at the moment there is no GHG emission, global warming will continue owing to GHG cumulative emission. In this study, scenarios are developed based on two types of optimistic and conservative diffusion goal. There were a total of 6 alternatives scenarios. The objective of this study are to compare scenarios in terms of GHG cumulative emissions and alternative fuels. An object of analysis is the residential buildings and time frame of scenarios is set up by 2030. And this study uses the LEAP model that is a bottom-up energy model. In conclusion, It is important to set specific diffusion pathway for mitigating climate change virtually.

A Study on the Regional Climate Change Scenario for Impact Assessment on Water Resources (수자원 영향평가에 활용 가능한 지역기후변화 시나리오 연구)

  • Im, Eun-Soon;Kwon, Won-Tae;Bae, Deq-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.637-642
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    • 2006
  • 온실가스 증가로 인한 기후변화를 이해하고 전망함과 동시에, 다양한 영향평가 분야에 적합한 기후정보를 제공하기 위해서는 온실가스 증가 시나리오에 근거한 신뢰성 있는 기후변화 장기 시나리오가 필수적이다. 미래 기후변화에 따른 영향평가 연구의 신뢰도는 영향평가모델의 주요 입력자료로 사용되는 기후정보의 신뢰도가 가장 근본적인 문제라고 할 수 있다. 본 연구에서는 국제이론물리센터(International Center for Theoretical Physics, ICTP)에서 개발한 가장 최신의 지역기후모델인 RegCM3(Regional Climate Model Ver.3)을 도입하여 한반도에서의 상세 기후변화 시나리오를 생산할 수 있는 이중둥지격자시스템(double-nested system)을 구축하였다. 이를 이용하여 IPCC 권장배출 시나리오인 SRES(Special Report on Emission Scenarios) B2 시나리오에 근거한 ECHO-G(독일 MPI의 기후모델) 결과를 과거 30년(1971-2000)과 미래 30년(2021-2050)에 대하여 상세화하였다. 과거 시나리오의 검증을 통하여 다양한 시.공간 규모에 대한 불확실성을 평가하고, 이에 대한 신뢰도를 기반으로 미래 기후변화를 전망하였다.

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Correlation analysis between climate indices and Korean precipitation and temperature using empirical mode decomposition : II. Correlation analysis (경험적 모드분해법을 이용한 기상인자와 우리나라 강수 및 기온의 상관관계 분석 : II. 상관관계 분석)

  • Ahn, Si-Kweon;Choi, Wonyoung;Shin, Hongjoon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.49 no.3
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    • pp.207-215
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    • 2016
  • In this study, it is analyzed how large scale climate variation has an effect on climate systems over Korea using correlation analysis between climate indices and Intrinsic Mode Functions (IMFs) of precipitation and temperature. For this purpose, the estimated IMFs of precipitation and temperature from the accompanying paper were used. Furthermore, cross correlation coefficients and lag time between climate indices and IMFs were calculated considering periodicities and tendencies. As results, more accurate correlation coefficients were obtained compared with those between climate indices and raw precipitation and temperature data. We found that the Korean climate is closely related with climate variations of $El-Ni{\tilde{n}}o$ in terms of periodicity and its tendency is followed with increasing sea surface temperature due to climate change.

Investigating Data Preprocessing Algorithms of a Deep Learning Postprocessing Model for the Improvement of Sub-Seasonal to Seasonal Climate Predictions (계절내-계절 기후예측의 딥러닝 기반 후보정을 위한 입력자료 전처리 기법 평가)

  • Uran Chung;Jinyoung Rhee;Miae Kim;Soo-Jin Sohn
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.2
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    • pp.80-98
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    • 2023
  • This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

Development and Application of a Methodologyfor Climate Change Vulnerability Assessment-Sea Level Rise Impact ona Coastal City (기후변화 취약성 평가 방법론의 개발 및 적용 해수면 상승을 중심으로)

  • Yoo, Ga-Young;Park, Sung-Woo;Chung, Dong-Ki;Kang, Ho-Jeong;Hwang, Jin-Hwan
    • Journal of Environmental Policy
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    • v.9 no.2
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    • pp.185-205
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    • 2010
  • Climate change vulnerability assessment based on local conditions is a prerequisite for establishment of climate change adaptation policies. While some studies have developed a methodology for vulnerability assessment at the national level using statistical data, few attempts, whether domestic or overseas, have been made to develop methods for local vulnerability assessments that are easily applicable to a single city. Accordingly, the objective of this study was to develop a conceptual framework for climate change vulnerability, and then develop a general methodology for assessment at the regional level applied to a single coastal city, Mokpo, in Jeolla province, Korea. We followed the conceptual framework of climate change vulnerability proposed by the IPCC (1996) which consists of "climate exposure," "systemic sensitivity," and "systemic adaptive capacity." "Climate exposure" was designated as sea level rises of 1, 2, 3, 4, and 5 meter(s), allowing for a simple scenario for sea level rises. Should more complex forecasts of sea level rises be required later, the methodology developed herein can be easily scaled and transferred to other projects. Mokpo was chosen as a seaside city on the southwest coast of Korea, where all cities have experienced rising sea levels. Mokpo has experienced the largest sea level increases of all, and is a region where abnormal high tide events have become a significant threat; especially subsequent to the construction of an estuary dam and breakwaters. Sensitivity to sea level rises was measured by the percentage of flooded area for each administrative region within Mokpo evaluated via simulations using GIS techniques. Population density, particularly that of senior citizens, was also factored in. Adaptive capacity was considered from both the "hardware" and "software" aspects. "Hardware" adaptive capacity was incorporated by considering the presence (or lack thereof) of breakwaters and seawalls, as well as their height. "Software" adaptive capacity was measured using a survey method. The survey questionnaire included economic status, awareness of climate change impact and adaptation, governance, and policy, and was distributed to 75 governmental officials working for Mokpo. Vulnerability to sea level rises was assessed by subtracting adaptive capacity from the sensitivity index. Application of the methodology to Mokpo indicated vulnerability was high for seven out of 20 administrative districts. The results of our methodology provides significant policy implications for the development of climate change adaptation policy as follows: 1) regions with high priority for climate change adaptation measures can be selected through a correlation diagram between vulnerabilities and records of previous flood damage, and 2) after review of existing short, mid, and long-term plans or projects in high priority areas, appropriate adaptation measures can be taken as per this study. Future studies should focus on expanding analysis of climate change exposure from sea level rises to other adverse climate related events, including heat waves, torrential rain, and drought etc.

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