• Atmosphere
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• v.34 no.1
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.183-183
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• 2019

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.615-631
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• 2012

This study provides an evaluation for capability of Integrated Climate and Air quality Modeling System (ICAMS) on future regional scale climate projection. Temperature and precipitation are compared between ground-level observation data and results of regional models (MM5) for the past 30 years over the Korean peninsula. The ICAMS successfully simulates the local-scale spatial/seasonal variation of the temperature and precipitation. The probability distribution of simulated daily mean and minimum temperature agree well with the observed patterns and trends, although mean temperature shows a little cold bias about $1^{\circ}C$ compared to observations. It seems that a systematic cold bias is mostly due to an underestimation of maximum temperature. In the case of precipitation, the rainfall in winter and light rainfall are remarkably simulated well, but summer precipitation is underestimated in the heavy rainfall phenomena of exceeding 20 mm/day. The ICAMS shows a tendency to overestimate the number of washout days about 7%. Those results of this study indicate that the performance of ICAMS is reasonable regarding to air quality predication over the Korean peninsula.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.187-199
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• 2017

We attempted to assess the impact of climate change on rice yields in Cambodia and to investigate adaptation strategies to climate change including more drastically shifting the planting dates and considering more fertilizer application levels. The potential yields of two wet season rice cultivars (Sen Pidao and Phka Rumduol) under two climate change scenarios in Cambodia were simulated using the CERES-Rice model. Field experiments conducted at the Cambodian Agricultural Research and Development Institute (CARDI), in 2010, 2011, and 2013 and climate variables from the HadGEM3-RA model were collected for this study. Compared with the baseline (1991-2000), yields of Sen Pidao rice will decrease under climate change and yields of Phka Rumduol rice could increase or decrease depending on fertilizer rates and the periods (2040s, 2050s, and 2080s). In general, the variations in the simulated effects of climate change on yields were more sensitive at fertilizer N100-N200 and less sensitive at fertilizer N0-N50. It is likely that forward shifts of planting date from the baseline plating date for the two cultivars in the future can be more benefitted than backward shifts. It is concluded that the CERES-Rice model can be useful to provide efficacious adaptation strategies in Cambodia.

• Korean Journal of Plant Taxonomy
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• v.40 no.4
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• pp.202-207
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• 2010

The most useful criteria and selection procedures of biological indicators have been developed in Korea because they have taken into account local and national concerns on biological responses against climate change. On the basis of these criteria and selection procedures, 100 climate-sensitive biological indicator species were selected to predict biodiversity distribution shift by climate change and manage biological resources integratedly at the national level. It is expected that selection and monitoring of biological indicators by climate change will provide significant information to prepare protective strategies of vulnerable species against climate change and adaptive policies under the changing environment in Korea. In this paper, we have reviewed what kinds of criteria were considered in selecting bioindicators to assess responses of biological organisms against climate change. Definition and selection steps of bioindicators were proposed, and the 100 species of climate- sensitive biological indicators were selected out of 33,253 taxa reported in Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.22-38
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• 2012

Adaptation of climate change is necessary to avoid unexpected impacts of climate change caused by human activities. Vulnerability refers to the degree to which system cannot cope with impacts of climate change, encompassing physical, social and economic aspects. Therefore the quantification of climate change impacts and its vulnerability is needed to identify vulnerable regions and to setup the proper strategies for adaptation. In this study, climate change vulnerability is defined as a function of climate exposure, sensitivity, and adaptive capacity. Also, we identified regions vulnerable to ozone due to climate change in Korea using developed proxy variables of vulnerability of regional level. 18 proxy variables are selected through delphi survey to assess vulnerability over human health sector for ozone concentration change due to climate change. Also, we estimate the weighting score of proxy variables from delphi survey. The results showed that the local regions with higher vulnerability index in the sector of human health are Seoul and Daegu, whereas regions with lower one are Jeollanam-do, Gyeonggi-do, Gwangju, Busan, Daejeon, and Gangwon-do. The regions of high level vulnerability are mainly caused by their high ozone exposure. We also assessed future vulnerability according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1FI, A1T, A1B, B2, and B1 scenarios in 2020s, 2050s and 2100s. The results showed that vulnerability increased in all scenarios due to increased ozone concentrations. Especially vulnerability index is increased by approximately 2 times in A1FI scenarios in the 2020s. This study could support regionally adjusted adaptation polices and the quantitative background of policy priority as providing the information on the regional vulnerability of ozone due to climate change in Korea.

• Atmosphere
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• v.18 no.2
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• pp.83-95
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• 2008

In this study we have investigated the preceding eighteen large-scale climate indices with a lead time from zero to twelve months that have an influence on the variability of temperature and precipitation in Korea in order to understand which climate indices are overall available as predictors for long-range forecasting. We also have studied the dynamic link between preceding large-scale climate indices and regional climate using singular value decomposition analysis (SVDA) and correlation analysis (CA). Based on the coupled mode between large-scale circulation and regional climate, and correlation pattern between the preceding large-scale climate indices and large-scale circulation, the level of significance on climate indices as a predictor for monthly mean temperature and precipitation was evaluated for 5 and 1% level.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.195-201
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• 2013

Local governments are establishing their own greenhouse gas reduction goal and are playing a important role to respond to climatic changes. However, there are difficulties in quantitative analyses such as estimation of future greenhouse gas emission and computation of reduction potential, which are procedures required to establish mid to long term strategies to realize of low carbon society by each local governments. Also, reduction measures must reflect characteristics of each local government, since the reduction power of each local government can differ according to characteristics of each. In order to establish strategies that reflect characteristics of local governments, types of greenhouse gas emission from cities were classified largely into residential city, commercial city, residential commercial city, agriculture and fishery city, convergence city, and industrial city. As a result of analyzing basic unit of greenhouse gas emission by local government during 2007 in terms of per population, household and GRDP based on the type classification, significant results were deduced for each type. To manage the amount of the national greenhouse gas, reduction measures should be focused on the local governments that emits more than the average of each type's GHG emission.

• Atmosphere
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• v.30 no.2
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.