• Journal of Environmental Impact Assessment
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• v.21 no.1
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• pp.71-80
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• 2012

Against the backdrop of the clear impact of climate change, it has become essential to analyze the influence of climate change and relevant vulnerabilities. This research involved evaluating the impact of heat waves in Seoul, from among many local autonomous bodies that are responsible for implementing measures on adapting to climate change. To carry out the evaluation, the A1B scenario was used to forecast future temperature levels. Future climate scenario results were downscaled to $1km{\times}1km$ to result in the incorporation of regional characteristics. In assessing the influence of heat waves on people-especially the excess mortality-we analyzed critical temperature levels that affect excess mortality and came up with the excess mortality. Results of this evaluation on the impact of climate change and vulnerabilities indicate that the number of days on which the daily average temperature reaches $28.1^{\circ}C$-the critical temperature for excess mortality-in Seoul will sharply increase in the 2050s and 2090s. The highest level of impact will be in the month of August. The most affected areas in the summer will be Songpa-gu, Gangnam-gu, and Yeongdeungpo-gu. These areas have a high concentration of residences which means that heat island effects are one of the reasons for the high level of impact. The excess mortality from heat waves is expected to be at least five times the current figure in 2090. Adaptation plan needs to be made on drawing up long-term adaptation measures as well as implementing short-term measures to minimize or adapt the impact of climate change.

• Journal of Yeungnam Medical Science
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• v.36 no.3
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• pp.241-248
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• 2019

Background: Heatstroke is one of the most serious heat-related illnesses. However, establishing public policies to prevent heatstroke remains a challenge. This study aimed to investigate the most relevant climate elements and their warning criteria to prevent outdoor heatstroke (OHS). Methods: We investigated heatstroke patients from five major hospitals in Daegu metropolitan city, Korea, from June 1 to August 31, 2011 to 2016. We also collected the corresponding regional climate data from Korea Meteorological Administration. We analyzed the relationship between the climate elements and OHS occurrence by logistic regression. Results: Of 70 patients who had heatstroke, 45 (64.3%) experienced it while outdoors. Considering all climate elements, only mean heat index (MHI) was related with OHS occurrence (p=0.019). Therefore, the higher the MHI, the higher the risk for OHS (adjusted odds ratio, 1.824; 95% confidence interval, 1.102-3.017). The most suitable cutoff point for MHI by Youden's index was $30.0^{\circ}C$ (sensitivity, 77.4%; specificity, 73.7%). Conclusion: Among the climate elements, MHI was significantly associated with OHS occurrence. The optimal MHI cutoff point for OHS prevention was $30.0^{\circ}C$.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Atmosphere
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• v.34 no.1
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• Journal of Technology Innovation
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• v.30 no.4
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• pp.29-56
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• 2022

This study is a review paper on the contents and policy direction of the 'Transformative regional innovation policy'. The transformative regional innovation policy is a policy that develops countermeasures against climate crisis, aging, and polarization with a vision of system transformation from the perspective of local residents. The structure of the study is as follows. First, it deals with the characteristics of transformative regional innovation policy theory, which is distinguished from existing regional innovation policies. Next, studies related to major elements of transformative regional innovation policies, types of system transformation, and industrial formation are reviewed. The elements that differentiate the transformative regional innovation policy from existing policies are summarized and issues to be addressed in order to develop future discussions are drawn.

• Atmosphere
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• v.33 no.5
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• pp.477-492
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• 2023

Based on the new climate normals (1991~2020), annual mean, maximum and minimum temperature is 12.5℃, 18.2℃, and 7.7℃, respectively while annual precipitation is 1,331.7 mm, the annual mean wind speed is 2.0 m s^-1, and the relative humidity is 67.8% in the Republic of Korea. Compared to 1981~2010 normal, annual mean temperature increased by 0.2℃, maximum and minimum temperatures increased by 0.3℃, while the amount of precipitation (0.7%) and relative humidity (1.1%) decreased. There was no distinct change in annual mean wind speed. The spatial range of the annual mean temperature in the new normals is large from 7.1 to 16.9℃. Annual precipitation showed a high regional variability, ranging from 787.3 to 2,030.0 mm. The annual mean relative humidity decreased at most weather stations due to the rise in temperature, and the annual mean wind speed did not show any distinct difference between the new and old normals. With the addition of a warmer decade (2011~2020), temperatures all increased consistently and in particular, the increase in the maximum temperature, which had not significantly changed in previous decades, was evident. The increasing trend of annual and summer precipitation by the 2010s has disappeared in the new normals. Among extreme climate indices, MxT30 (Daily maximum temperature ≥ 33℃ days), MnT25 (Daily minimum temperature ≥ 25℃ days), and PH30 (1 hour maximum precipitation ≥ 30 mm days) increased while MnT-10 (Daily minimum temperature < -10℃ days) and W13.9 (Daily maximum wind speed ≥ 13.9 m/s days) decreased at a statistically significant level. It is thought that a detailed study on the different trends of climate elements and extreme climate indices by region should be conducted in the future.

• Atmosphere
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• v.19 no.3
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• pp.227-235
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• 2009

Global climate warming induced by long-lived greenhouse gases is expected to cause increases in wildfire frequencies and intensity in boreal forest regions of mid- and high-latitudes in the future. Siberian forest fires are one of important sources for air pollutants such as ozone and aerosols over East Asia. Thus an accurate quantification of forest fire influences on air quality is crucial, in particular considering its higher occurrences expected under the future warming climate conditions. We here use the 3-D global chemical transport model (GEOS-Chem) with the satellite constrained fire emissions to quantify Siberian fire effects on ozone concentrations in East Asia. Our focus is mainly on spring 2003 when the largest fires occurred over Siberia in the past decade. We first evaluated the model by comparing to the EANET observations. The model reproduced observed ozone concentrations in spring 2003 with the high $R^2$ of 0.77 but slightly underestimated by 20%. Enhancements in seasonal mean ozone concentrations were estimated from the difference in simulations with and without Siberian fires and amounted up to 24 ppbv over Siberia. Effects of Siberian fires also resulted in 3-10 ppbv incresases in Korea and Japan. These increases account for about 5-15% of the ozone air quality standard of 60 ppbv in Korea, indicating a significant effect of Siberian fires on ozone concentrations. We found however that possible changes in regional meteorology due to Siberian fires may also affect air quality. Further study on the interaction between regional air quality and meteorology is necessary in the future.

• Journal of Korean Society of Rural Planning
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• v.23 no.2
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• pp.75-86
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• 2017

IPCC Guidelines have been updated after the first official announcement to get more precise estimation of GHG emissions. The goal of this study is to evaluate the implications of the IPCC Guidelines improvements including equations of country-specific parameter values for estimating GHG emissions for rice cultivation on the agricultural sector. In addition, we analyze the effects of emission factors associated with organic amendment applications. The results of this study are as follows; (1) the total GHG emissions of rice cultivation based on 1996 IPCC GL are 28% lower than those estimated by 2006 IPCC GL with the same year data; (2) GHGs can be reduced up to 60% through the assumption of organic fertilizer applications; (3) Jeonnam and Chungnam are the worst regions for GHG emissions on rice cultivation and Chungbuk shows the highest reduction rate of GHG emissions, about 40%.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.51-58
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• 2017

This study proposes an appropriate level of insulation standards by region through annual heating energy requirements according to regional climate. The reference buildings out of non-residential buildings approved by the energy saving design standard for buildings were derived in the previous study, in which the annual heating energy requirements for each building were as follows when the insulation standard for building members in four regions (Pyeongchang, Seoul, Gwang-ju, and Jeju) suggested by the energy saving design standard for buildings: $29.8kWh/m^2$ in Pyeongchang, $17.5kWh/m^2$ in Seoul, $14.4kWh/m^2$ in Gwangju, and $16.7kWh/m^2$ in Jeju. To satisfy the passive level of insulation standards for these buildings, in case that roof/floor of buildings in Pyeongchang and Seoul was $0.2W/m^2K$, the minimum window thermal transmittance should satisfy $0.9W/m^2K$ and the minimum wall thermal transmittance should satisfy $0.1W/m^2K$ in the case of Pyeongchang. On the other hand, the minimum window thermal transmittance should satisfy $1.5W/m^2K$ and the minimum wall thermal transmittance should satisfy $0.14W/m^2K$ in the case of Seoul. For Jeju regions, the minimum wall thermal transmittance should satisfy $0.34W/m^2K$ to meet the passive level of buildings. Based on the above results, the thermal transmittance of each member by region should take the outdoor climate condition of the region into consideration to satisfy the passive level of buildings.