• Journal of the Korean Solar Energy Society
• /
• v.30 no.4
• /
• pp.15-21
• /
• 2010

Radiation data are the best source of information for estimating average incident radiation. Lacking this or data from nearby locations of similar climate, it is possible to use empirical relation ships to estimate radiation from days of cloudiness. It is necessary to estimate the regression coefficients in order to predict the daily global radiation on a horizontal surface. There fore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account cloud cover. Particularly, the straight line regression model proposed shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of -0.26 to +0.53% and each station annual average deviation of -1.61 to +1.7% from measured values.

• International Journal of Advanced Culture Technology
• /
• v.11 no.1
• /
• pp.312-319
• /
• 2023

This study aims to enhance the engineering education for non-majors by incorporating the concept of Global Citizenship Education and addressing the need for education that responds to climate and ecological changes. The study uses robot programming as a tool to foster the development of global citizens. Non-majors often struggle with producing more than just motionless forms or solid productions, due to a lack of understanding of mechanisms and coding. The study proposes the use of the Convergence D-SteamRobot (DSR) to address this issue by blending humanities and engineering. This is achieved by presenting problems through books to increase empathy, integrating simple machine mechanisms, and creating prototypes to solve self-defined problems. Through this process, learners determine the SDGs topic they want to solve and learn about the simple mechanical mechanism involved in producing the prototype. The educational model provides a constructivist learning environment that emphasizes empathy and exploration, encourages peer-learning, and improves divergent thinking and problem-solving skills.

• Journal of Environmental Science International
• /
• v.26 no.5
• /
• pp.549-561
• /
• 2017

Recently IPCC (International Panel on Climate Change, 2007) pointed out that global warming is a certain ongoing process on the earth, due to which water resources management is becoming one of the most difficult tasks with the frequent occurrences of extreme floods and droughts. In this study we made runoff predictions for several control points in the Geum River by using the watershed runoff model, SSARR (Streamflow Synthesis and Reservoir Regulation Model), with daily RCP 4.5 and RCP 8.5 scenarios for 100 year from 1st Jan 2006 to 31st Dec 2100 at the resolution of 1 km given by Climate Change Information Center. As a result of, the Geum River Basin is predicted to be a constant flow increases, and it showed a variation in the water circulation system. Thus, it was found that the different seasonality occurred.

• Journal of Korean Society on Water Environment
• /
• v.26 no.2
• /
• pp.268-278
• /
• 2010

This study derived the effectiveness analysis results of construction of wastewater treatment plant under climate change scenarios. Canadian Global Coupled Model (CGCM3) was used and A1B and A2 of Special Report on Emission Scenario (SRES) were selected. Regional climate change data for this application were downscaled by using Statistical Downscaling Model (SDSM) and the flow and BOD concentration durations were obtained by using Hydrological Simulation Program - Fortran (HSPF). The criteria for low flow and water quality were chosen as $Q_{99}$, $Q_{95}$, $Q_{90}$ and $C_{30}$, $C_{10}$, $C_1$. The numbers of days to satisfy the instreamflow requirements and target BOD concentration were also added to the criteria for comparison. As a results, small wastewater treatment plant improved the water cycle due to the increase of low flow and the decrease of BOD concentration. But climate change affected the reduction of effectiveness significantly. Especially in case of construction of small waste water treatment plant in the upstream region, it is necessary to take climate change impact into consideration since it is usually related to the low flow and the water quality of the stream.

• The Korean Journal of Quaternary Research
• /
• v.13 no.1
• /
• pp.53-65
• /
• 1999

It is only possible by Physical based Water Balance Models such as $BROOK_{TOP}$ developed by me to estimate regional water balances caused by changes of regional ecosystem, which result in climate change, change of vegetation due to climate change, artificial landuse change, etc. This study estimates regional water balances of mid-north agricultural and forest regions in Germany using $BROOK_{TOP}$-Water Balance Model with climate change scenarios developed by PIK in Germany and GCM Scenarios developed by Praha University in Czech. Developing Water Resource Change Estimation System such as this study for global warming with considering climate, surface and underground conditions provides the basis of system development for surface-, groundwater-, cultivation-, ecosystem-, natural emergency-management, landuse and regional planing.

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

• Korean Chemical Engineering Research
• /
• v.60 no.3
• /
• pp.433-438
• /
• 2022

A carbon cycle model based method is proposed in order to evaluate the effectiveness of various policies and projects to achieve carbon neutrality. The proposed model was validated by properly reproducing the increase in the concentration of carbon dioxide in the atmosphere and the rise of the global average temperature from the data of anthropogenic carbon emissions and deforestation since the industrial revolution. As a case study, a carbon cycle impact assessment was performed for deforestation, reforestation, and afforestation. It was verified that the increase of carbon dioxide in the atmosphere is attributed not only to fossil fuel usage, but also to deforestation, and that even if deforestation is immediately followed by reforestation, it takes very long to return to the initial concentration. The proposed method is expected to be eventually applicable to simulation of potential climate control in the future, contributing to safety verification of various climate engineering techniques.

• Journal of the Korean Society of Visualization
• /
• v.5 no.2
• /
• pp.9-13
• /
• 2007

Typhoon simulation based on dynamical forecasting results is demonstrated by utilizing geodesic model GME (operational global numerical weather prediction model of German Weather Service). It is based on uniform icosahedral-hexagonal grid. The GME gridpoint approach avoids the disadvantages of spectral technique as well as the pole problem in latitude-longitude grids and provides a data structure extremely well suited to high efficiency on distributed memory parallel computers. In this study we made an attempt to simulate typhoon 'NARI' that passed over the Korean Peninsula in 2007. GME has attributes of numerical weather prediction model and its high resolution can provide details on fine scale. High resolution of GME can play key role in the study of severe weather phenomenon such as typhoons. Simulation of future typhoon that is assumed to occur under the global warming situation shows that the life time of that typhoon will last for a longer time and the intensity will be extremely stronger.

• Atmosphere
• /
• v.31 no.5
• /
• pp.511-523
• /
• 2021

This study explores the optimal ensemble size to improve the prediction performance of the Korea Meteorological Administration's operational climate prediction system, global seasonal forecast system version 5 (GloSea5). The GloSea5 produces an ensemble of hindcast data using the stochastic kinetic energy backscattering version2 (SKEB2) and timelagged ensemble. An experiment to increase the hindcast ensemble from 3 to 14 members for four initial dates was performed and the improvement and effect of the prediction performance considering Root Mean Square Error (RMSE), Anomaly Correlation Coefficient (ACC), ensemble spread, and Ratio of Predictable Components (RPC) were evaluated. As the ensemble size increased, the RMSE and ACC prediction performance improved and more significantly in the high variability area. In spread and RPC analysis, the prediction accuracy of the system improved as the ensemble size increased. The closer the initial date, the better the predictive performance. Results show that increasing the ensemble to an appropriate number considering the combination of initial times is efficient.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.5
• /
• pp.149-162
• /
• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.