• Journal of the Korean earth science society
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• v.32 no.2
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• pp.239-247
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• 2011

The United Nations Framework Convention on Climate Change and the corresponding national low-carbon policy should be grounded on the scientific understanding of climate sensitivity to the increase in CO2 concentration. This is, however, precluded by the fact that current estimates of the climate sensitivity highly vary. To understand the scientific background, limitations, and prospects of the climate sensitivity study, this paper reviews, as objectively as possible, the most recent results on the sensitivity issue. Theoretically, the climate sensitivity hinges on climate feedbacks from various atmospheric and surface physical processes. Especially cloud and sea-ice processes associated with shortwave radiation are known to have largest uncertainty, resulting in an inaccurate estimation of climate sensitivity. For this reason, recent observational studies using satellite data suggest sensitivity lower than or similar to those estimated by climate models (2-5 K per doubled CO2).

• 한국해양학회지
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• v.20 no.2
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• pp.1-9
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• 1985

A simple analytic model of the sea surface temperature(SST) is developed in order to understand the effects of the Asian monsoon and the Kuroshio on the annual variations of SST by the Asian monsoon is almost in phase with the incoming radiation whereas that by the Kuroshio is out of phase with the incoming radiation. In the Yellow Sea, due to the heat advection by the Asian monsoon, the yearly mean SST is low and the annual range of SST exceeds 20$^{\circ}C$. The annual range of SST in the northwestern Japan Sea is large because of the combined effects of the Asian monsoon and the cold water advection. In the Kuroshio and in the Tsushima Current regions, the annual range of SST is small and the mean SST is high due to the heat advection by warm currents.

• Journal of Satellite, Information and Communications
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• v.1 no.2
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• pp.1-7
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• 2006

GOCi (Geostationary Ocean Color Imager) is one of the COMS payloads that KARI is currently developing and scheduled to be in operation from around 2008. Its primary objective is to monitor the Korean coastal water environmental condition. We report the current progress in development of the integrated optical model as one of the key analysis tools for the GOCI in-orbit performance verification. The model includes the Sun as the emitting light source. The curved Earth surface section of 2500 km x 2500 km includingthe Korean peninsular os defined as a Lambertian scattering surface consisted of land and sea surface. From its geostationary orbit, the GOCI optical system observes the reflected light from the surfaces with varying reflectance representing the changes in its environmental conditions. The optical ray tracing technique was used to demonstrate the GOCI in-orbit performances such as red tide detection. The computational concept, simulation results and its implications to the on-going development of GOCI are presented.

• Journal of Bio-Environment Control
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• v.9 no.4
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• pp.201-206
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• 2000

A certain system to overcome high temperature should be introduced for the stable year-round cultivation in greenhouses. There are efficient methods to overcome high temperature such as ventilation system with shading screen, fan and pad system with screen, and fog system with screen. This study was carried out to find a means to determine the capacity of such system. Heat balance equations for each system were established and verified by experimental results. The calculated ventilation rates from heat balance equations showed a good agreement with the measured ones. The evapotranspiration coefficient was the most important parameter affecting the ventilation requirement among input parameter affecting the ventilation requirement among input parameters except weather data. When the evaportanspiration coefficient increased 1%, the ventilation requirement decreased 1.3%. Therefore the data of evapotranspiration coefficient should be accumulated by various experiments, and then design standards and selection guidelines should be provided. The simulation results for same design conditions shown that air exchanges requirement and evaporating water of fan and pad system were 5.1∼7.7% and 6.8∼9.3% larger than those of fog system, respectively.

• Journal of the Society of Disaster Information
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• v.8 no.4
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• pp.419-431
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• 2012

This paper takes precautions proposals against prospective disasters from the space weather maximum in 2013. A geomagnetic space storm sparked by a solar maximum like the one that flared toward earth is bound to strike again and could wreak havoc across the modern world. The purpose of the study is that the disaster reduction and safety service implementation study on the ultimate space weather systems by the information systems of the space weather. The process methods of the study are that an implementation of preparation for the smart IT and GIS based disaster management systems of the solar maximum deal with analysis on the flare, solar proton event, and geomagnetic storm from space blasters, These approach and methods for the solar maximin display national policy implementation of the pattern of the radio wave disasters from the protection and preparation methods. This research can provide affective methods for the saving lives and property protections that implementation of the disaster prediction and disaster prevention systems adapts the smart IT systems and converged decision making support systems using uGIS methodology.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.100-100
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• 2019

최근 대기 중 미세먼지의 농도가 높은 일수가 급증하면서, 미세먼지를 저감하고자 하는 연구가 활발히 이루어지고 있다. 미세먼지는 주로 자동차 혹은 공장 등 인간 활동에 의한 오염물질 배출에 의해 발생하는 것으로 알려져 있으며, 태양복사에너지, 토양수분, 강우, 풍속 등의 수문기상학적 인자에 의해 발생, 이동, 소멸의 과정을 거친다. 현재 우리나라에서는 미세먼지 농도를 관측하기 위해 지점 기반의 관측소를 운영하고 있으며, 관측소가 위치하지 않은 지역의 미세먼지 농도는 선형 보간법 등을 활용한 내삽 기법을 통해 제공하고 있다. 그러나 미세먼지 농도는 다양한 수문기상인자들의 영향에 의한 차이가 크게 나타나기 때문에 지점 기반의 자료로는 해당 지역의 미세먼지 농도를 추정하는 데 어려움이 많다. 본 연구에서는 미세먼지의 공간적인 분포를 추정하고자 MODerate resolution Imaging Spectroradiometer (MODIS) 에어로졸 자료와 Global Land Data Assimilation System (GLDAS) 수문기상인자를 활용하여 미세먼지 농도에 영향을 주는 것으로 판단되는 다양한 수문기상인자들과의 상관성을 분석하였다. 미세먼지와 각 인자간의 상관성을 분석하여 높은 상관성을 갖는 수문기상인자들을 도출하고 최적의 선형회귀분석 모델을 구축하기 위해 베이지안 모델 평균(Bayesian Model Averaging, BMA)을 사용하였으며, 지점 데이터와의 비교를 통해 활용성을 검증하였다. 전체적으로 수문기상인자를 사용한 선형회귀분석 결과에서는 미세먼지농도 변화의 경향을 반영하고 있는 것을 확인할 수 있었으나, 계절별, 지역별 등 대기 특성을 고려하지 않아 각 기간의 급격한 농도 변화를 감지하기에 어려움이 있었다. 이러한 연구를 바탕으로 수문기상인자와 미세먼지 농도의 패턴이 더욱 정확히 분석된다면, 미세먼지 농도 모니터링과 정확한 예보 시스템의 구축에 효과적으로 활용 될 것으로 기대된다.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Journal of the Korean earth science society
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• v.36 no.3
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• pp.210-221
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• 2015

The terrain features and surface characteristics are the most important elements not only in meteorological modeling but also in air quality modeling. The diurnal evolution of local climate over complex terrain may be significantly controlled by the ground irregularities. Such topographic features can affect a thermally driven flow, either directly by causing changes in the wind direction or indirectly, by inducing significant variations in the ground temperature. Over a complex terrain, these variations are due to the nonuniform distribution of solar radiation, which is highly determined by the ground geometrical characteristics, i.e. slope and orientation. Therefore, the accuracy of prediction of regional scale circulation is strong associated with the accuracy of land-use and topographic information in meso-scale circulation assessment. The objective of this work is a numerical simulation using MM5-A2C model with the detailed topography and land-use information as the surface boundary conditions of the air flow field in mountain regions. Meteorological conditions estimated by MM5-A2C command a great influence on the dispersion of mountain areas with the reasonable feature of topography where there is an important difference in orographic forcing.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.603-616
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• 2016

In this study, the effects of differential heating by land-use types on flow and air temperature at an Seoul Automated Synoptic Observing Systems (ASOS) located at Songwol-dong, Jongno-gu, Seoul was analyzed. For this, a computation fluid dynamics (CFD) model was coupled to the local data assimilation and prediction system (LDAPS) for reflecting the local meteorological characteristics at the boundaries of the CFD model domain. Time variation of temperatures on solid surfaces was calculated using observation data at El-Oued, Algeria of which latitude is similar to that of the target area. Considering land-use type and shadow, surface temperatures were prescribed in the LDAPS-CFD coupled model. The LDAPS overestimated wind speeds and underestimated air temperature compared to the observations. However, a coupled LDAPS-CFD model relatively well reproduced the observed wind speeds and air temperature, considering complicated flows and surface temperatures in the urban area. In the morning when the easterly was dominant around the target area, both the LDAPS and coupled LDAPS-CFD model underestimated the observed temperatures at the Seoul ASOS. This is because the Kyunghee Palace located at the upwind region was composed of green area and its surface temperature was relatively low. However, in the afternoon when the southeasterly was dominant, the LDAPS still underestimated, on the while, the coupled LDAPS-CFD model well reproduced the observed temperatures at the Seoul ASOS by considering the building-surface heating.