• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.1-10
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• 2013

This study has purpose to minimize the impact of climate change of Siheung. Vulnerability assessment was carried out for establishing the Siheung Climate Change Master Plan. Climate change vulnerability assessment analyzed using climate exposure, sensitivity and adaptive capacity indicators. A proxy variable is selected from each indicator. Meteorological data uses the RCP scenarios provided by the Meteorological Administration, and this study assumes that the same trend will continues in the future. Siheung are vulnerable to heavy rains in the flooded roads and farmland. Also, it is necessary to be careful heat wave in summer. The size and scale of the damage depends on the city's ability to respond to the impacts of climate change. It is necessary to make a adaptation plan for climate change impact assessment and vulnerability analysis. This study will be used to make Siheung Climate Change Master Plan and to determine the priority of the policy as guideline. It is expected that this study is helpful to pursue climate change vulnerability assessment of other local governments.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.79-91
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• 2011

In order to study interactions between climate change and air quality, a modeling system including the downscaling scheme has been developed in the integrated manner. This research focuses on the development of a downscaling method to utilize CCSM3 outputs as the initial and boundary conditions for the regional climate model, MM5. Horizontal/vertical interpolation was performed to convert from the latitude/longitude and hybrid-vertical coordinate for the CCSM3 model to the Lambert-Conformal Arakawa-B and sigma-vertical coordinate for the MM5 model. A variable diagnosis was made to link between different variables and their units of CCSM and MM5. To evaluate the dynamic downscaling performance of this study, spatial distributions were compared between outputs of CCSM/MM5 and NRA/MM5 and statistic analysis was conducted. Temperature and precipitation patterns of CCSM/MM5 in summer and winter showed a similar pattern with those of observation data in East Asia and the Korean Peninsula. In addition, statistical analysis presented that the agreement index (AI) is more than 0.9 and correlation coefficient about 0.9. Those results indicate that the dynamic downscaling system built in this study can be used for the research of interaction between climate change and air quality.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.601-614
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• 2012

This paper is aimed to analyze the determinants and their relative importance that affect regional competitiveness in the era of globalization and climate change. The panel model was set by a balanced panel data for 7 metropolitan areas & 9 provinces and for the period of 2001~2010. Gross regional income per capita is used as the dependent variable and competitiveness-based factors, economic production factors, and climate change adaptation factors are selected as the explanatory variables. In this study, Model 1(typical regional competitiveness model) and Model 2 (added adaptation to climate change adaptation factors) were compared. The important findings can be summarized as follows. The most influential determinants on regional competitiveness are the ratio of knowledge-based industries and human capital and energy inefficiencies decrease the regional competitiveness. Compared to Model 1, Model 2 showed that the effects of the regional openness and the technology innovation capital are relatively more influential in Model 2. The results of this empirical study provide policy implications to strengthen the regional competitiveness in the future of the era of globalization and climate change.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.67-74
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• 2017

This paper analyzes the causal relationship from climate to international grain prices. Although climate is an important factor affecting the grain markets, it has been restrictively considered in previous studies analyzing the causal relationship of international grain prices. In this paper, monthly data from May 1987 to 2013 is used for the causal analysis in which the sea surface temperature (SST), a representative global climate variable, and the international prices of wheat, corn, and soybean, the world's three major crops, are considered. The test method is the parametric version of the nonparametric test for causality in high-order moments suggested by Nishiyama et al. (2011). The results show that the climate causes in the first moment the prices of all the three grains and causes in the second moment the prices of corn and soybean, but does not cause in the third moment any of the three grain prices.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.277-297
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• 2016

This study is to analyze the effects of changing pattern of climate vaariables on total factor productivity of Korea manufacture industry. Changes in temperature, rainfalls and humidity which are the representative climate variables are used as main factors. Not only average values of the variables but those highest values are used as independent variables in the model, in order to consider the characteristic pattern of recent climate change, the high volatilities. The OLS results are unlike to previous literature that temperature and humidity had no significant impact on manufacturing productivity. An increase in the amount of precipitation was analyzed that impact negatively impacted. The analysis of panel data showed that temperatures and precipitation all that does not significantly affect the manufacturing. While the increase of the average humidity is shown to increase the total productivity of manufacture industry. In Korea, adaptation capability is important in determining the effects of climate change on productivity of manufacture industry.

• Atmosphere
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• v.32 no.4
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• pp.367-379
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• 2022

In this paper, the evaluation of the performance of Korea Meteorological Administratio (KMA) Global Seasonal forecasting system version 6 (GloSea6) is presented by assessing the effects of larger ensemble size and carrying out the test using different initial conditions for hindcast in sub-seasonal to seasonal scales. The number of ensemble members increases from 3 to 7. The Ratio of Predictable Components (RPC) approaches the appropriate signal magnitude with increase of ensemble size. The improvement of annual variability is shown for all basic variables mainly in mid-high latitude. Over the East Asia region, there are enhancements especially in 500 hPa geopotential height and 850 hPa wind fields. It reveals possibility to improve the performance of East Asian monsoon. Also, the reliability tends to become better as the ensemble size increases in summer than winter. To assess the effects of using different initial conditions, the area-mean values of normalized bias and correlation coefficients are compared for each basic variable for hindcast according to the four initial dates. The results have better performance when the initial date closest to the forecasting time is used in summer. On the seasonal scale, it is better to use four initial dates, where the maximum size of the ensemble increases to 672, mainly in winter. As the use of larger ensemble size, therefore, it is most efficient to use two initial dates for 60-days prediction and four initial dates for 6-months prediction, similar to the current Time-Lagged ensemble method.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.9-19
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• 2015

Internal air temperature of greenhouse is an important variable that can be influenced by the complex interaction between outside weather and greenhouse inside climate. This paper focuses on a data-based model approach to predict internal air temperature of the greenhouse. External air temperature, solar radiation, wind speed and wind direction were measured next to an experimental greenhouse supported by the Electronics and Telecommunications Research Institute and used as input variables for the model. Internal air temperature was measured at the center of three sections of the greenhouse and used as an output variable. The proposed model consisted of a transfer function including the four input variables and tested the prediction accuracy according to the sampling interval of the input variables, the orders of model polynomials and the time delay variable. As a result, a second-order model was suitable to predict the internal air temperature having the predictable time of 20-30 minutes and average errors of less than ${\pm}1K$. Afterwards mechanistic interpretation was conducted based on the energy balance equation, and it was found that the resulting model was considered physically acceptable and satisfied the physical reality of the heat transfer phenomena in a greenhouse. The proposed data-based model approach is applicable to any input variables and is expected to be useful for predicting complex greenhouse microclimate involving environmental control systems.

• Korean Journal of Ecology and Environment
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• v.51 no.3
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• pp.221-233
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• 2018

This study was carried out to predict the current and future potential distribution and to identify the factors affecting potential distribution of 7 plants(Lamium amplexicaule L., Trigonotis peduncularis(Trevir.) Benth. ex Hemsl, Capsella bursa-pastoris (L.) L. W. Medicus, Taraxacum officinale Weber, Veronica persica Poir., Conyza sumatrensis E. Walker, Hypochaeris radicata L.) selected as indicators for climate change in agricultural ecosystem. We collected presence/absence data of 7 indicator plants at 108 sites in South Korea and applied the Maxent model. According to future climate scenario, the distribution area of C. bursa-pastoris(L.) L. W. Medicus, T. officinale Weber, and V. persica Poir. was expected to be reduced, but the distribution range was to be maintained. The distribution areas and range of the C. sumatrensis E. Walker and H. radicata L. were expected to be increased. The distribution area and range of T. peduncularis (Trevir.) Benth. Ex Hemsl. and L. amplexicalue L. were rapidly decreased. Non-climatic factors such as land cover and altitude were the most important environmental variable for T. officinale Weber, C. bursa-pastoris(L.) L.W.Medicus, V. persica Poir., T. peduncularis (Trevir.) Benth. Ex Hemsl., and L. amplexicalue L.. Climatic factors were the most important environmental variable for C. sumatrensis E. Walker and H. radicata L.. It is expected that the future potential distribution of 7 indicator plants response to climate change will be used to monitor and to establish the management plan.

• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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• pp.83-90
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• 2019

Most of the variable shading devices are installed outdoors, so they are greatly affected by structural safety due to external climate change, wind, rain, and snow. Especially, due to strong wind such as typhoons, safety problems may occur due to the dropout of the device. Therefore, it is necessary to secure the structural safety against the wind. Therefore, it is necessary to analyze the structural behavior of the windshield to evaluate the structural safety of the variable sunshade device. In this study, we analyze the wind pressure applied to the shading material according to the change of the length of the variable shading device, and apply it to the calculation of the wind load for the structural design of the variable shading device. The CFD (Computational Fluid Dynamic) analysis of the structure of the sample was used to analyze wind pressure magnitude and distribution. In order to estimate the wind pressure, the maximum wind loads of the static and negative pressures acting on the structure were analyzed from numerical simulation results.