• Journal of Environmental Health Sciences
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• v.40 no.5
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• pp.355-366
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• 2014

Objectives: This study seeks to evaluate the vulnerability assessment of the human health sector for $PM_{10}$, which is reflected in the regional characteristics and related disease mortality rates for $PM_{10}$ in Busan over the period of 2006-2010. Methods: According to the vulnerability concept suggested by the Intergovernmental Panel on Climate Change (IPCC), vulnerability to $PM_{10}$ is comprised of the categories of exposure, sensitivity, and adaptive capacity. The indexes of the exposure and sensitivity categories indicate positive effects, while the adaptive capacity index indicates a negative effect on vulnerability to $PM_{10}$. Variables of each category were standardized by the rescaling method, and each regional relative vulnerability was computed through the vulnerability index calculation formula. Results: The regions with a high exposure index are Jung-Gu (transportation region) and Saha-Gu (industrial region). Major factors determining the exposure index are the $PM_{10}$ concentration, days of $PM_{10}{\geq}50$, ${\mu}g/m^3$, and $PM_{10}$ emissions. The regions that show a high sensitivity index are urban and rural regions; these commonly have a high mortality rate for related disease and vulnerable populations. The regions that have a high adaptive capacity index are Jung-Gu, Gangseo-Gu, and Busanjin-Gu, all of which have a high level of economic/welfare/health care factors. The high-vulnerability synthesis of the exposure, sensitivity, and adaptive capacity indexes show that Dong-Gu and Seo-Gu have a risk for $PM_{10}$ potential effects and a low adaptive capacity. Conclusions: This study presents the vulnerability index to $PM_{10}$ through a relative comparison using quantitative evaluation to draw regional priorities. Therefore, it provides basic data to reflect environmental health influences in favor of an adaptive policy limiting damage to human health caused by vulnerability to $PM_{10}$.

• KCID journal
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• v.18 no.2
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• pp.33-42
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• 2011

Climate change has impacts on not only the average temperature rise but also the intensity and frequency of extreme events such as flood and drought. It is also expected that the damages on agricultural infrastructure will be increased resulting from increased rainfall intensity and frequency caused by climate change. To strengthen the climate change adaptation capacity, it is necessary to identify the vulnerability of a given society's physical infrastructures and to develop appropriate adaptation strategies with infrastructure management because generally facilities related to human settlements are vulnerable to climate changes and establishing an adaptive public infrastructure would reduce the damages and the repair cost. Therefore, development of mitigation strategies for agricultural infrastructure against climatic hazard is very important, but there are few studies on agricultural infrastructure vulnerability assessment and adaptation strategies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biological, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. In this study, for the vulnerability assessment for agricultural infrastructure, 3 categories of climate exposure, sensitivity, and adaptation capacity were defined which are composed of 16 sub-categories and 49 proxy variables. Database for each proxy variables was established based on local administrative province. Future studies are required to define the weighting factor and standardization method to calculate the vulnerability indicator for agricultural infrastructure against climate change.

• Atmosphere
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• v.21 no.1
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• pp.17-33
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• 2011

A dynamical downscaling system for seasonal forecast has been constructed based on a regional climate model, and its predictability was investigated for 10 years' wintertime (December-January-February; DJF) climatology in East Asia. Initial and lateral boundary conditions were obtained from the operational seasonal forecasting data, which are realtime output of the Global Data Assimilation and Prediction System (GDAPS) at Korea Meteorological Administration (KMA). Sea surface temperature was also obtained from the operational forecasts, i.e., KMA El-Nino and Global Sea Surface Temperature Forecast System. In order to determine the better configuration of the regional climate model for East Asian regions, two sensitivity experiments were carried out for one winter season (97/98 DJF): One is for the topography blending and the other is for the cumulus parameterization scheme. After determining the proper configuration, the predictability of the regional forecasting system was validated with respect to 850 hPa temperature and precipitation. The results showed that mean fields error and other verification statistics were generally decreased compared to GDAPS, most evident in 500 hPa geopotential heights. These improved simulation affected season prediction, and then HSS was better 36% and 11% about 850 hPa temperature and precipitation, respectively.

• Journal of Climate Change Research
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• v.1 no.1
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• pp.21-30
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• 2010

In this study, vulnerability of water resources to climate change was assessed in terms of flood, drought and water management. Criteria and indicators were employed for assessing the vulnerability. The criteria used to assess the vulnerability was sensitivity of the study area, the exposure to climate and the adaptability to climate change. These criteria were quantified and standardized using corresponding indicators. Vulnerability of water resources to climate change is assessed to be generally increasing over time. The appropriate watershed scales are the large drainage basin for national level vulnerability assessment and the small drainage basin for local one.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.188-200
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• 2014

The IPCC 5th Assessment Report (Climate Change 2013: The Physical Science Basis) was accepted at the 36th Session of the IPCC on 26 September 2013 in Stockholm, Sweden. It consists of the full scientific and technical assessment undertaken by Working Group I. This comprehensive assessment of the physical aspects of climate change puts a focus on those elements that are relevant to understand past, document current, and project future of climate change. The assessment builds on the IPCC Fourth Assessment Report and the recent Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. The assessment covers the current knowledge of various processes within, and interactions among, climate system components, which determine the sensitivity and response of the system to changes in forcing, and they quantify the link between the changes in atmospheric constituents, and hence radiative forcing, and the consequent detection and attribution of climate change. Projections of changes in all climate system components are based on model simulations forced by a new set of scenarios. The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter. The primary purpose of this Technical Summary is to provide the link between the complete assessment of the multiple lines of independent evidence presented in the main report and the highly condensed summary prepared as Policy makers Summary. The Technical Summary thus serves as a starting point for those readers who seek the full information on more specific topics covered by this assessment. Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased. Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of $CO_2$ since 1750. Human influence on the climate system is clear. This is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. The in-depth review for past, present and future of climate change is carried out on the basis of the IPCC 5th Assessment Report.

• Journal of the Korean Geographical Society
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• v.49 no.4
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• pp.489-508
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• 2014

The purpose of this study is to clarify the spatio-temporal patterns of changes in seasonal extreme temperature events in the Republic of Korea based on daily maximum and minimum temperature data sets observed at 61 weather stations for the recent 40 year period (1973~2012). According to analysis of regional average data, in spring increases of warm days are most distinct, while in summer reductions of cool nights and increases of warm nights are most noticeable. The similar patterns to those in summer are observed in fall, while in winter reductions of cool days and nights are notable. Regardless of the magnitude of urbanization, changes in nighttime extreme temperature events prevail in transitional periods between seasons, while those in daytime extreme temperature events do so only in particular months. In contrast, cool days in spring and summer, warm days in summer and warm nights in winter do not show any statistically-significant changes at most of stations. The sensitivity of seasonal extreme temperature events to increases of seasonal average extreme temperature is greatest in the case of warm days ($+6.3days/^{\circ}C$) and cool nights ($-6.2days/^{\circ}C$) in spring, warm nights ($+10.4days/^{\circ}C$) and days ($+9.5days/^{\circ}C$) in summer, warm days ($+7.7days/^{\circ}C$) in fall, and cool nights ($-4.7/^{\circ}C$) in winter, respectively. These results indicate that changes in seasonal extreme temperature events and their sensitivity to changes in seasonal climate means under a warmer climate are occurring with seasonally and diurnally asymmetric magnitudes in Korea due to complex climate feedbacks.

• Journal of the Korean association of regional geographers
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• v.19 no.4
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• pp.615-626
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• 2013

In this study, spatial patterns of the urban flood vulnerability index in Seoul are examined by considering climate exposure, sensitivity, and adaptability associated with floodings for recent 5 year (2006~2010) period by the smallest administrative unit called Dong. According to the results of correlation analyses based on the IPCC(Intergovernmental Panel on Climate Change)'s vulnerability model, among many variables associated with urban flooding, rainwater tank capacity, 1-day maximum precipitation and flood pumping station capacity have statistically-significant, and relatively-high correlations with the number of flood damage in Seoul. The flood vulnerability map demonstrates that the extensive areas along Anyang and Joongnang streams show relatively high flood vulnerability in Seoul due to high sensitivity. Especially in case of Joongnang stream areas, climatic factors also contribute to the increase of flood vulnerability. At local scales, several Dong areas in Gangdong-gu and Songpa-gu also show high flood vulnerability due to low adaptability, while those in Gangnam-gu do due to high sensibility and climate factor such as extreme rainfall events. These results derived from the flood vulnerability map by Dong unit can be utilized as primary data in establishing the adaptation, management and proactive policies for flooding prevention within the urban areas in more detail.

• Ocean and Polar Research
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• v.26 no.1
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• pp.33-42
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• 2004

Effect of freshwater discharge on the long-term salt balance in the Northern and Central Indian River Lagoon (IRL) is successfully simulated by a new analytical solution to a water balance-based one-dimensional salt conservation equation. Sensitivity tests show that the salinity levels drop abruptly even during the dry season (November to May) due to the high surface runoff discharge caused by tropical storms, depressions, and passage of cold fronts. Increasing surface runoff and direct precipitation has risen by ten times, lowering the salinity level down to 12psu in the Northern Central zone, and to 17 psu in the Northern zone. However, the salinity level in the Southern Central zone has decreased to 25 psu. High sensitivity of the Northern Central zone to freshwater discharge can be partially explained by a rapid urbanization in this zone. During the dry season, less sensitivity of the Southern Central zone to the increased surface runoff is attributed to the proximity of the zone to the Sebastian Inlet and a strong diffusion condition possibly resulting from the seawater intrusion to the surficial aquifer at the Vero Beach. During the wet season, however, the whole study area is highly sensitive to freshwater discharge due to the weak diffusion conditions. High sensitivity of the IRL to the given diffusion conditions guarantees that the fresh-water release occurs during strong wind conditions, achieving both flood control in the drainage basin and a proper salinity regime in the IRL.

• Water Engineering Research
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• v.6 no.2
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• pp.73-89
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• 2005

Two kinds of high resolution GCMs with the same spatial resolutions but with different schemes run by domestic and foreign agencies are used to clarify the usefulness and sensitivity of GCM for water resources applications for Korea. One is AMIP-II (Atmospheric Model Intercomparison Project-II) type GCM simulation results done by ECMWF (European Centre for Medium-Range Weather Forecasts) and the other one is AMIP-I type GCM simulation results done by METRI (Korean Meteorological Research Institute). Observed mean areal precipitation, temperature, and discharge values on 7 major river basins were used for target variables. Monte Carlo simulation was used to establish the significance of the estimator values. Sensitivity analyses were done in accordance with the proposed ways. Through the various tests, discrimination condition is sensitive for the distribution of the data. Window size is sensitive for the data variation and the area of the basins. Discrimination abilities of each nodal value affects on the correct association. In addition to theses sensitivity analyses results, we also noticed some characteristics of each GCM. For Korean water resources, monthly and small window setting analyses are recommended using GCMs.