• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1784-1788
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• 2010

APEC 기후센터(APEC Climate Center, APCC)에서 제공하는 다중모형앙상블(Multi-model Ensemble, MME) 형태의 계절예측정보를 이용하여 3개월 가뭄전망을 수행하였다. APCC MME는 기후예측모형이 가지는 불확실성을 최소화하기 위한 방법으로, 아시아 태평양 지역 내 9개 회원국 16개 기관 21개 기후모형의 계절예측정보를 활용하여, 개별 모형이 가지는 계통오차(Systematic error)를 앙상블 기법을 통하여 상쇄함으로써 최적의 예측자료를 도출한다. 또한, 기후예측 모형이 예측한 대기순환장은 관측 지점변수와 경험적 통계적 관련성을 가지므로, 이를 바탕으로 상세지역의 이상기후에 대한 정보를 도출할 수 있다. 본 연구에서는 가뭄 관리 및 전망을 위한 입력 자료로서, 기상전문 기관인 APEC 기후센터 (APEC Climate Center, APCC)에서 제공하는 전구 규모의 기온 및 강수 전망자료를 기상청 산하 59개 지점의 전망자료로 통계적 규모 축소화 기법을 통해 3개월 예보를 실시하였다. APCC 계절예측자료를 가뭄모니터링시스템의 자료입력 포맷에 따라 적절히 가공한 뒤, 가뭄 관리 및 전망을 위하여 SPI(Standard Precipitation Index) 및 PDSI(Palmer Drought Severity Index)지수의 입력자료로 사용하여 SPI 및 PDSI 지수를 산정하였다. 또한 분위사상법(Quantile Mapping)을 이용하여 총 59개 지점의 과거 월평균 관측값과 최근 2009년에 대한 모의값의 누적확률분포값을 계산하고 모의값의 확률분포를 관측값의 확률분포에 사상시켜 가뭄 전망을 위한 기상변수의 오차를 보정하고자 하였다. 이러한 계절예측정보를 이용하여 가뭄 전망에 대한 신뢰도가 높아진다면, 사전예방 및 피해완화로 가뭄상황에 대한 신속한 대처 및 피해의 경감이 이루어질 수 있을 것이다.

• Journal of the Korean earth science society
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• v.38 no.3
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• pp.194-208
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• 2017

This study analyzed the correlation between tropical cyclone (TC) frequency and the western North Pacific monsoon index (WNPMI), which have both been influential in East China Sea during the summer season over the past 37 years (1977-2013). A high positive correlation was found between these two variables, but it did not change even if El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) years were excluded. To determine the cause of this positive correlation, the highest (positive WNPMI phase) and lowest WNPMIs (negative WNPMI phase) during an eleven-year period were selected to analyze the mean difference between them, excluding ENSO years. In the positive WNPMI phase, TCs were mainly generated in the eastern seas of the tropical and subtropical western North Pacific, passing through the East China Sea and moving northward toward Korea and Japan. In the negative phase, TCs were mainly generated in the western seas of the tropical and subtropical western North Pacific, passing through the South China Sea and moving westward toward China's southern regions. Therefore, TC intensity in the positive phase was stronger due to the acquisition of sufficient energy from the sea while moving a long distance up to East Asia's mid-latitude. Additionally, TCs occurred more in the positive phase. Regarding the difference in 850 hPa and 500 hPa stream flows between the two phases, anomalous cyclones were strengthened in the tropical and subtropical western North Pacific, whereas anomalous anticyclones were strengthened in East Asia's mid-latitude regions. Due to these two anomalous pressure systems, anomalous southeasterlies developed in East China Sea, which played a role in the anomalous steering flows that moved TCs into this region. Furthermore, due to the anomalous cyclones that developed in the tropical and subtropical western North Pacific, more TCs could be generated in the positive phase.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.264-264
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• 2023

물순환 과정에서의 증발산은 장기적인 관점에서의 수자원 계획 수립 시 중요한 요소이다. 증발산은 기온, 상대습도, 일사량 등 기상학적 인자뿐만 아니라 증발표면, 식생분포 등 다양한 인자의 복합작용에 의해 일어나므로, 유역 단위에서 발생한 실제증발산(Actual evapotranspiration, AET)을 측정하기에는 기술적인 한계가 존재한다. 그러나 증발산 보완관계(Complementary relationship of evapotranspiration, CRE) 가설을 활용하면, 수문요소의 상호작용을 고려한 모델링을 거치지 않고도, 비교적 간단하게 AET를 추정할 수 있다. 본 연구는 증발산 관측자료를 기반으로 유역 단위에서의 CRE를 검증하고자 하며, 플럭스 타워 등 다양한 관측장비가 설치되어 있는 용담댐 시험유역을 대상유역으로 선정하였다. 용담댐 유역 내 산지에 위치한 덕유산 플럭스 타워에서 측정된 증발산을 AET로 보았으며, 유역 인근에 위치한 전주 기상관측소에서 측정되는 팬 증발량(E_pan)을 잠재증발산량(Potential evapotranspiration, PET)으로 보았다. E_pan 계측시, 증발팬의 가열 등 주변환경 변화로 인해 과다하게 추정되는 값을 보완하기 위해 FAO Penman-Monteith 식을 활용해 팬 증발량 보정계수(Coefficient of pan evaporation, k_p)를 산정하여 적용하였다. 습윤증발산량(Wet evapotranspiration, WET)은 대기가 완전히 포화되었을 때 발생하는 증발산량으로, 댐 수표면에서 계측되는 수면증발량을 WET로 보았다. CRE 검증을 위해 AET와 PET를 각각 WET로 나누어 AET+와 PET+로 무차원화하였으며, 습윤지수(Moisture Index, MI)는 AET를 PET로 나누어 산정하였다. CRE 가설은 MI에 따른 AET+와 PET+가 서로 보완관계를 갖는다는 것인데, 용담댐 유역의 관측자료를 활용하여 CRE를 검증한 결과 AET+와 PET+ 간의 비대칭계수(b)가 1.23인 것으로 나타났다. 이 때의 평균제곱오차(MSE)는 0.599, 결정계수(R₂)는 0.631로 나타나 CRE의 b가 적합하게 추정된 것으로 판단된다. 본 연구결과와 같이 검증된 CRE를 통해 증발산 관측지점이 없거나, 조밀하지 않은 유역의 AET를 간접추정할 수 있으며, 이를 활용해 보다 정확한 댐의 장기유출 모의와 용수공급계획 수립에 도움을 줄 수 있을 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.474-474
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• 2021

물순환 과정에서의 증발산량은 필수적으로 고려해야 하는 요소이며, 증발산은 기상학적 인자뿐만 아니라 증발 표면 특성 등 복합적인 요인에 의해서 발생한다. 이러한 이유로 실제증발산의 절대량을 추정하는 것은 쉽지 않으며, 특히 수문학적 관점에서 유역단위의 증발산량을 산정하는 데에는 기술적인 한계가 존재한다. 반면 잠재증발산량과 실제증발산량의 보완관계가설을 활용하면 복잡한 수문모델링을 거치지 않고 팬증발량으로부터 유역의 실제증발산을 산정할 수 있다. 본 연구에서는 관측자료를 기반으로 하여 용담댐 유역의 증발산 보완관계를 검증하고자 한다. 실제증발산량(ETA)은 용담댐 내 덕유산 플럭스 타워의 관측자료를 활용하였으며, 잠재증발산량(ETP)으로는 기상관측소에서 관측한 팬 증발량 자료를 활용하였고 습윤증발산량(ETW)은 Priestley-Taylor 공식을 통해 산정하였다. ETW는 수분이 무제한 공급되는 상황에서의 증발산량으로 정의되며, 동시에 ETA 및 ETP와의 상대적 비율로 스케일화하여 보완관계설정에 활용하였다. 대기의 습윤지수(Moisture Index, MI)는 ETA와 ETP간의 상대적 비율로 정의하였다. 이 때 팬 증발량은 기상 및 주변 환경 조건의 영향을 받아 증발량이 과대추정 되는 경향이 있으므로 보정계수를 적용하여 보정한 값을 활용하였다. 보정계수는 FAO Penman-Monteith 식을 활용한 기준증발산량과 팬 증발량의 기울기로 산정하며, 본 연구에서는 보정계수로 0.77을 사용하였다. 또한 ETW 산정 시 적용되는 Priestley-Talyor 계수(α)는 널리 알려진 값인 1.26 대신 유역의 기상조건을 고려하여 0.99를 적용하였다. α 값의 조정을 통해 증발산 보완관계에 대한 E+의 평균 제곱근 오차(RMSE)가 0.685에서 0.075, Ep+의 경우 0.437에서 0.315로 개선되어 용담댐 유역의 증발산 보완관계가 만족할 만한 수준으로 확인되었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1151-1159
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• 2014

In this study, two global simple indices are used to investigate climate variability and change in observations. Land-Ocean Contrast (LOC) is an index of area-averaged surface temperature contrast between land and ocean. Meridional Temperature Gradient (MTG) is defined as the mean meridional temperature gradient in the Northern Hemisphere from mid to high latitude and sub-tropical zonal bands. These indices have direct or indirect effects on changing in atmospheric circulations and atmospheric moisture transport from north-south or east-west into East Asia (EA). In addition, warm season hydrometeorology in EA is highly associated with water supplies for coupled human and natural systems including drinking water, irrigation, hydropower generation as well as fisheries. Therefore, in this study, we developed an empirical separation approach for summer rainfall from typhoon and monsoon. An exploratory analysis was also conducted to identify the regional patterns of summer monsoon precipitation over the Korean peninsula within the context of changes in different types of temperature gradients. The results show significant and consistent changes in summer monsoon rainfall during the summer season (June-September) in South Korea.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.588-595
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• 2020

Prediction and control of nitrogen oxides (NO_x) emission is of great interest in industry due to stricter environmental regulations. Herein, we propose an artificial intelligence (AI)-based framework for prediction of NO_x emission. The framework includes pre-processing of data for training of neural networks and evaluation of the AI-based models. In this work, Long-Short-Term Memory (LSTM), one of the recurrent neural networks, was adopted to reflect the time series characteristics of NO_x emissions. A decision tree was used to determine a time window of LSTM prior to training of the network. The neural network was trained with operational data from a heating furnace. The optimal model was obtained by optimizing hyper-parameters. The LSTM model provided a reliable prediction of NO_x emission for both training and test data, showing an accuracy of 93% or more. The application of the proposed AI-based framework will provide new opportunities for predicting the emission of various air pollutants with time series characteristics.

• Journal of the Korean earth science society
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• v.29 no.1
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• pp.45-59
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• 2008

This study aims to analyze the interdecadal variation of relationship between Indian Ocean sea surface temperature (SST) and East Asian summer monsoon (EASM) during the period of 1948-2005. In the pre-period, which is from 1948 to 1975, the relationship between Indian Ocean SST and East Asian summer rainfall anomaly (EASRA) is very weak. However, in the post-period, which is trom 1980 to 2005, Indian Ocean SST is significantly positively correlated with EASRA. The equatorial Indian Ocean SST has a significantly positive correlation with EASM in spring, while Indian Ocean SST near the bay of Bengal has a positive relationship in summer for the post-period. Also the interdecadal variation of the correlation between Indian Ocean SST and EASRA is significant, but that between EASRA and the El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) is not. Atmospheric general circulation model (AGCM) test results show the pattern of increased precipitation in the zonal belt region including South Korea and Japan and the pattern of decreased precipitation in the northeastern part of Asia, which are similar to the real climate. The increase of the precipitation in August from the model run is also similar to the real climate variation. Model results indicate that the Indian Ocean SST warming could intensify the convection over the vicinity of the Philippines and the Bay of Bengal, which forces to move northward the convection center. This warming strengthens the EASM and weakens the WNPM.