• Proceedings of the KSRS Conference
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• v.1
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• pp.446-449
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• 2006

It is backscattering of solar radiation by water body that makes ocean color observable from above, either by airplanes or satellites. Given the very low direct contribution to backscattering by phytoplankton cells, it is curious why the retrieval of phytoplankton concentration from remotely observed ocean color is evidently successful. From semianalytical bio-optical models, a dataset is created of spectral absorption, scattering and backscattering coefficients as a function of chlorophyll concentration. Four scenarios are considered, 1) only molecular and no particle scattering, 2) random particle backscattering uncorrelated with chlorophyll concentration, 3) constrained random particle scattering with known backscattering ratio, and 4) constrained random scattering with random backscattering ratio. Scenario 1 only introduces moderate errors of -20% - 90%. And for scenarios 3 and 4, the errors are largely within 30% and 100%. Scenario 2 introduces the largest errors, with the retrieved chlorophyll concentration virtually uncorrelated with the true values, implying the backscattering must somehow be related to the trophic state. The results of the study suggested These 3 cases confirmed that while it is the absorption by phytoplankton that in large part decides the accuracy of chlorophyll concentration retrieval, for the success of monitoring of global ocean primary productivity we have to improve our knowledge on particle backscattering.

• KIEAE Journal
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• v.7 no.4
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• pp.57-62
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• 2007

At the moment, the reduction of building energy consumption is a unavoidable task of mankind for conserving global environment. Decreasing overall U-value of building envelope and air infiltration, especially in Korean climate condition with clear four seasons, are the obvious solutions for the objective. Thus low glazing ratio with small window openings are required for heating and cooling load reduction in buildings. Using larger window openings could provide better natural ventilation but it also increases the direct solar radiation penetration into indoor space, heat gain in summer and heat loss in winter. On the other hand, the ventilation rates decreasing problem with smaller window openings could be occurred. As a solution for it, the use of casement window can cause increasing natural ventilation rates by wing wall effect. This paper focuses on deduce the most efficient opening type of casement window in Korean climate. To estimate ventilation performance of each opening types, CFD simulation was used. The best performance of opening type in every wind direction is opening both windows to the center and the most appropriate opening type for Korean climate is also opening both windows to center.

• Journal of Environmental Science International
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• v.26 no.12
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• pp.1363-1374
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• 2017

Global climate change caused by industrialization has caused abnormal weather conditions such as urban temperatures and tropical nights, urban heat waves, heat waves, and heavy rains. Therefore, the study tried to analyze climate conditions and weather conditions in the streets and analyze climate factors and meteorological factors that lead to inconvenience to citizens. In the case of trees, the overall temperature, surface temperature, solar irradiance, and net radiation were measured low, and the temperature was lower in the Pedestrian road than in roads. The dry bulb temperature, the black bulb temperature, and the wet bulb temperature for the thermal evaluation showed the same tendency. In the case of thermal evaluation, there was a similar tendency to temperature in WBGT, MRT, and UTCI, and varied differences between types. Although the correlation between the meteorological environment and the thermal environment showed a statistically significant significance, the difference between the measured items was not significant. The study found that the trees were generally pleasant to weather and thermal climate in the form of trees, and the differences were mostly documented.

• Journal of Korea Water Resources Association
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• v.34 no.4
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• pp.391-401
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• 2001

Several curvature parameters, solar radiation parameter and topographic flow generation parameters have been summarized and calculated to predict the spatial distribution of soil moisture content. The spatial distribution of soil moisture data can be obtained using Global Positioning System(GPS) and portable soil moisture monitoring equipment, Theta-Probe. Correlation analysis has been performed between the parameters of soil moisture prediction and measured data of soil moisture. Multiple regression analysis of soil moisture prediction shows the potential capability and limitations of existing methods of digital terrain analysis.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.789-794
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• 2006

The potential impacts of climate change on heating and cooling energy demand were investigated by means of transient building energy simulations and hourly weather data scenarios for Inchon. Future trends for the 21 st century was assessed based oil climate change scenarios with 7 global climate models(GCMs), We constructed hourly weather data from monthly temperatures and total incident solar radiation ($W/m^2$) and then simulated heating and cooling load by Trnsys 16 for Inchon. For 2004-2080, the selected scenarios made by IPCC foresaw a $3.7-5.8^{\circ}C$rise in mean annual air temperature. In 2004-2080, the annual cooling load for a apartment with internal heat gains increased by 75-165% while the heating load fell by 52-71%. Our analysis showed widely varying shifts in future energy demand depending on the season. Heating costs will significantly decrease whereas more expensive electrical energy will be needed of air conditioning during the summer.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.41-49
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• 2021

The causes of climate change are natural and artificial. Natural causes include changes in temperature and sunspot activities caused by changes in solar radiation due to large-scale volcanic activities, while artificial causes include increased greenhouse gas concentrations and land use changes. Studies have shown that excessive carbon use among artificial causes has accelerated global warming. Climate change is rapidly under way because of this. Due to climate change, the frequency and cycle of infectious disease viruses are greater and faster than before. Currently, the world is suffering greatly from coronavirus infection-19 (COVID-19). Korea is no exception. The first confirmed case occurred on January 20, 2020, and the number of infected people has steadily increased due to several waves since then, and many confirmed cases are occurring in 2021. In this study, we conduct a study on climate change before and after COVID-19 using weather data from Korea to determine whether climate change affects infectious disease viruses through logistic regression analysis. Based on this, we want to classify before and after COVID-19 through a logistic regression model to see how much classification rate we have. In addition, we compare monthly classification rates to see if there are seasonal classification differences.

• Atmosphere
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• v.21 no.4
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• pp.429-438
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• 2011

The climatology of surface UV radiation for Seoul, presented in Cho et al. (1998; 2001), has been updated using measurement of surface erythemal ultraviolet (EUV) and total ultraviolet (TUV) irradiance (wavelength 286.5~363.0 nm) by a Brewer Spectrophotometer (MK-IV) for the period 2004~2010. The analysis was also carried out together with the broadband total (global) solar irradiance (TR ; 305~2800 nm) and cloud amount to compare with the UV variations, measured by Seoul meteorological station of Korean Meteorological Agency located near the present study site. Under all-sky conditions, the day-to-day variability of EUV exhibits annual mean of 98% in increase and 31% in decrease. It has been also shown that the EUV variability is 17 times as high as the total ozone in positive change, whereas this is 6 times higher in negative change. Thus, the day to day variability is dominantly caused rather by the daily synoptic situations than by the ozone variability. Annual mean value of daily EUV and TUV shows $1.62kJm^{-2}$ and $0.63MJm^{-2}$ respectively, whereas mean value of TR is $12.4MJm^{-2}$ ($143.1Wm^{-2}$). The yearly maximum in noon-time UV Index (UVI) varies between 9 and 11 depending on time of year. The highest UVI shows 11 on 20 July, 2008 during the period 2004~2010, but for the period 1994~2000, the index of 12 was recorded on 13 July, 1994 (Cho et al., 2001). A 40% of daily maximum UVI belongs to "low (UVI < 2)", whereas the UVI less than 5% of the maximum show "very high (8 < UVI < 10)". On average, the maximum UVI exceeded 8 on 9 days per year. The values of Tropospheric Emission Monitoring Internet Service (TEMIS) EUV and UVI under cloud-free conditions are 1.8 times and 1.5 times, respectively, higher than the all-sky measurements by the Brewer. The trend analysis in fractional deviation of monthly UV from the reference value shows a decrease of -0.83% and -0.90% $decade^{-1}$ in the EUV and TUV, respectively, whereas the TR trend is near zero (+0.11% $decade^{-1}$). The trend is statistically significant except for TR trend (p = 0.279). It is possible that the recent UV decrease is mainly associated with increase in total ozone, but the trend in TR can be attributed to the other parameters such as clouds except the ozone. Certainly, the cloud effects suggest that the reason for the differences between UV and TR trends can be explained. In order to estimate cloud effects, the EUV, TUV and TR irradiances have been also evaluated for clear skies (cloud cover < 25%) and cloudy skies (cloud cover ${\geq}$ 75%). Annual mean values show that EUV, TUV and TR are $2.15kJm^{-2}$, $0.83MJm^{-2}$, and $17.9MJm^{-2}$ for clear skies, and $1.24kJm^{-2}$, $0.46MJm^{-2}$, and $7.2MJm^{-2}$ for cloudy skies, respectively. As results, the transmission of radiation through clouds under cloudy-sky conditions is observed to be 58%, 55% and 40% for EUV, TUV and TR, respectively. Consequently, it is clear that the cloud effects on EUV and TUV are 18% and 15%, respectively lower than the effects on TR under cloudy-sky conditions. Clouds under all-sky conditions (average of cloud cover is 5 tenths) reduced the EUV and TUV to about 25% of the clear-sky (cloud cover < 25%) values, whereas for TR, this was 31%. As a result, it is noted that the UV radiation is attenuated less than TR by clouds under all weather conditions.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

• Journal of Power Electronics
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• v.17 no.2
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.11
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• pp.421-427
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• 2016

The indoor temperature of a building increases during the day due to solar radiation. This behavior is significant in school buildings that are finished with high thermal capacity materials. Moreover, in school buildings, windows cannot be opened until the class has finished owing to the security policy of schools. Consequently, classrooms maintain a high temperature throughout the morning. It is thus important to remove the indoor heat before the commencement of classes in order to reduce the cooling energy needed. The Energy Recovery Ventilator (ERV) system is currently being installed in school buildings for ventilating the classrooms. Night-purge control using ERV can be a good strategy to cool the classroom in advance of the operation of the cooling system. However, the optimal operation method of the ERV for night-purge control has not yet been reported. In this study, the effect of night-purge control with ERV in school buildings is analyzed by simulation method. The results of this study showed that the energy saving effect of night-purge control with ERV is most effective in the case of 2 hours operation prior to the commencement of the first lass and when enthalpy based outdoor air cooling is used.