• 한국수자원학회논문집
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• 제49권10호
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• pp.835-849
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• 2016

최근 피해가 점차 심해지고 있는 가뭄을 경감하기 위해서는 가뭄모니터링 뿐만 아니라 정확한 가뭄전망이 수행되어야 한다. 본 연구에서는 국내 기존 MSWSI의 한계점을 개선하였으며, 개선된 MSWSI를 이용하여 앙상블기반 확률론적 가뭄전망을 수행하였다. 우선 금강유역 내 존재하는 모든 수문기상인자를 조사하여 각 유역별로 기존 MSWSI에서 적용한 4개 인자(하천유량, 지하수, 강수, 댐유입량)와 적합한 인자(댐저수위, 댐방류량)를 추가 선정하였다. 두 번째로 기존에는 정규분포만을 적용하였으나 본 연구에서는 각 수문기상인자들에 적합한 확률분포를 추정하였다. 강수와 하천은 대부분 Gumbel 분포, 댐유입량, 방류량, 저수위는 2 매개변수 대수정규분포, 지하수는 3 매개변수 대수정규분포를 따르는 것으로 나타났다. 개선된 MSWSI를 과거 실측강수, 하천유량 등을 이용하여 검증한 결과 기존 MSWSI보다 개선된 MSWSI가 과거 발생한 가뭄현상을 더 잘 나타내어 개선된 MSWSI가 효용성이 있음을 확인하였다. 마지막으로 개선된 MSWSI를 이용하여 앙상블기반 확률론적 가뭄전망을 극심한 가뭄이 발생한 2006년과 2014년을 대상으로 수행하고 검증하였으며, 기존보다 개선된 MSWSI를 이용한 가뭄전망이 우수한 결과를 나타냈다. 또한 대부분의 소유역에서 실제 가뭄의 가뭄지수가 개선된 MSWSI를 이용한 가뭄전망 범위에 속하는 것으로 나타났다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권11호
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• pp.493-504
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• 2023

대한민국은 지진 판의 경계로부터 멀리 떨어진 지역에 있으며, 이러한 지역에서 발생하는 판 내부 지진은 판 경계부 지진과 비교하면 일반적으로 규모가 작고 발생빈도도 낮다. 그럼에도 불구하고 과거 2년부터 1904년 사이 한반도에서 발생했던 지진과 최근 한반도 지진을 관측한 이래에 발생한 지진을 조사 및 분석한 결과 진도 규모 9까지 이르는 것으로 나타났다. 본 논문에서는 한반도에서 발생한 지진과 통계적 자기 유사성과의 관계를 분석하기 위해서 국립기상연구소에서 발표한 「한반도 역사지진 기록 (2년~1904년)」을 이용한다. 또한 본 논문을 통해서 해결한 문제는 한반도에서 발생한 지진데이터와 통계적 자기 유사성과 시각화의 관계 연구를 처음으로 규명하였으며, 그 결과 한반도 지진의 자기 유사성 정도를 판단하는 3가지 정량적인 추정방법으로 측정한 결과 자기 유사성 파라메터 H 값(0.5 < H < 1)이 0.8이상으로 자기 유사성 정도가 높은 것으로 나타났다. 그리고 그래프의 시각화를 통해 지진이 어느 지역에서 많이 발생했는지를 쉽게 파악할 수 있고, 향후 지진 발생시 피해를 예측하고 재산과 인명 피해를 최소화할 수 있는 예측 시스템 개발과 지진 데이터 분석 및 모델링 연구에 활용될 수 있을 것으로 보인다. 뿐만아니라 본 연구결과를 토대로 자기 유사성 프로세스는 지진활동의 패턴과 통계적 특성을 이해하고, 유사한 지진 사건을 그룹화하고 분류하는데 도움을 줄 수 있으며, 지진 활동에 대한 예측, 지진 위험 평가 및 지진 공학 관련 연구에 활용될 것으로 예상된다.

• Ecology and Resilient Infrastructure
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• 제10권4호
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• pp.116-124
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• 2023

극한호우 발생빈도 증가로 소하천 홍수 피해가 증가하고 있어 소하천 리스크 관리를 위해 유량 계측 요구가 증가하고 있다. 이에 행정안전부 (MOIS) 소속 국립재난안전연구원 (NDMI)은 CCTV 기반 자동유량계측기술 (CCTV based Automatic Discharge Measurement Technology, CADMT)을 개발하고 성능 검증과 재난 리스크 관리기술 개발을 위해 시범소하천을 운영하고 있다. 본 연구는 CADMT가 설치된 능막천과 중선필천 2개 소하천을 선정하고 소하천에 가장 가까운 기상청 Automatic Weather System 강우량 자료와 유량 계측자료를 이용해 4-Parameter Logistic 방법으로 Nomograph를 개발한다. 개발한 Nomograph를 검증하기 위하여 본 연구는 각 소하천에서 홍수량을 예측하고 그 결과를 계측 유량과 비교한다. 검증 결과 예측치는 계측치를 잘 재현하는 것으로 나타나 향후, 보다 정확도 높은 계측자료가 수집되고 이에 기반한 Nomograph가 개발된다면 정확도 높은 홍수 예·경보가 가능할 것으로 판단된다.

• 대기
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• 제25권1호
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• Journal of Korean Society for Atmospheric Environment
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• 제24권E2호
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• pp.63-73
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• 2008

In this study, neural network models (NNMs) were examined as alternatives to dispersion models in predicting the short-term $SO_2$ concentrations in a coastal area because the performances of dispersion models in coastal areas have been found to be unsatisfactory. The NNMs were constructed for various combinations of averaging time and prediction time in advance by using the historical data of meteorological parameters and $SO_2$ concentrations in 2002 in the coastal area of Boryeung, Korea. The NNMs were able to make much more accurate predictions of 1 hr $SO_2$ concentrations at ground level in the morning in coastal area than the atmospheric dispersion models such as fumigation models, ADMS3 and ISCST3 for identical conditions of atmospheric stability, area, and weather. Even when predictions of 24-h $SO_2$ concentrations were made 24 hours in advance, the predictions and measurements were in good accordance(correlation coefficient=0.65 for n=216). This accordance level could be improved by appropriate expansion of training parameters. Thus it may be concluded that the NNMs can be successfully used to predict short-term ground level concentrations averaged over time less than 24 hours even in complex terrain. The prediction performance of ANN models tends to improve as the prediction lagging time approaches the concentration averaging time, but to become worse as the lagging time departs from the averaging time.

• 대기
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• 제20권4호
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• pp.483-494
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• 2010

The vertical profiles of the extinction coefficient, the backscatter coefficient, and the lidar ratio (i.e., extinction-to-backscattering ratio) for Asian dust and pollution aerosols are determined from Raman (inelastic) and elastic backscatter signals. The values of lidar ratios during two polluted days is found between 52 and 82 sr (July 22, 2009) and 40~60 sr (July 31, 2009) at 52 nm, with relatively low value of particle depolarization ratio (<5%) and high value of sun photometer-derived Angstrom exponent (> 1.2). However, lidar ratios between 25 and 40 sr are found during two Asian dust periods (October 20, 2009 and March 15, 2010), with 10~20% of particle depolarization ratio and the relatively low value of sun photometer-derived Angstrom exponent (< 0.39). The lidar ratio, particle depolarization ratio and color ratio are useful optical parameter to distinguish non-spherical coarse dust and spherical fine pollution aerosols. The comparison of aerosol extinction profiles determined from inelastic-backscatter signals by the Raman method and from elastic-backscatter signals by using the Fernald method with constant value of lidar ratio (50 sr) have shown that reliable aerosol extinction coefficients cannot be determined from elastic-backscatter signals alone, because the lidar ratio varies with aerosol types. A combined Raman and elastic backscatter lidar system can provide reliable information about the aerosol extinction profile and the aerosol lidar ratio.

• 대기
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• 제26권4호
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• pp.697-709
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• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

• 대기
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• 제27권4호
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• pp.483-498
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• 2017

Sky view factor can quantify the influence of complex obstructions. This study aims to evaluate the best available SVF method that represents an urban thermal condition with land cover in complex city of Korea and also to quantify a correlation between SVF and mean air temperature; the results are as follows. First, three SVF methods comparison result shows that urban thermal study should consider forest canopy induced effects because the forest canopy test (on/off) on SVF reveals significant difference range (0.8, between maximum value and minimum value) in comparison with the range (0.1~0.3) of SVFs (Fisheye, SOLWEIG and 3DPC) difference. The significance is bigger as a forest cover proportion become larger. Second, R-square between SVF methods and urban local mean air temperature seems more reliable at night than a day. And as the value of SVF increased, it showed a positive slope in summer day and a negative slope in winter night. In the SVF calculation method, Fisheye SVF, which is the observed value, is close to the 3DPC SVF, but the grid-based SWG SVF is higher in correlation with the temperature. However, both urban climate monitoring and model/analysis study need more development because of the different between SVF and mean air temperature correlation results in the summer night period, which imply other major factors such as cooling air by the forest canopy, warming air by anthropogenic heat emitted from fuel oil combustion and so forth.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.752-755
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• 2006

Evaportranspiration is an important factor in hydrology cycle. Traditionally, it is measured by using basin or empirical formula with meteorology data, while it does not represent the evaportranspiration over a regional area. With the advent of improved remote sensing technology, it becomes a surface parameter of research interest in the field of remote sensing. Airborne and satellite imagery are utilized in this study. The high resolution airborne images include visible, near infrared, and thermal infrared bands and the satellite images are acquired by MODIS. Surface heat fluxes such as latent heat flux and sensible heat flux are estimate by using airborne and satellite images with surface meteorological measurements. We develop a new method to estimate the evaportranspiration over the rice paddy. The surface heat fluxes are initialized with a surface energy balance concept and iterated for convergent solution with atmospheric correct functions associated with aerodynamic resistance of heat transport. Furthermore, we redistribute the total net energy into sensible heat and latent heat fluxes. The result reveals that radiation and evaporation controlled extremes can be properly decided with both airborne and satellite images. The correlation coefficient of latent heat flux and sensible heat flux with corresponding in situ observations are 0.66 and 0.76, respectively. The relative root mean squared errors (RMSEs) for latent heat flux and sensible heat flux are 97.81 $(W/m^2)$ and 124.33 $(W/m^2)$, respectively. It is also shown that the newly developed retrieval scheme performs well when it is tested by using MODIS date.

• 한국태양에너지학회 논문집
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• 제36권4호
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• pp.11-20
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• 2016

For accurate wind resource assessment and wind turbine performance test, it is essential to secure wind data covering a rotor plane of wind turbine including a hub height. In general, we can depict wind speed profile by extrapolating or interpolating the wind speed data measured from a meteorological tower where multiple anemometers are mounted at different heights using a power-law of wind speed profile. The most important parameter of a power-law equation is a vertical wind profile exponent which represents local characteristics of terrain and land cover. In this study, we calculated diurnal vertical wind profile exponents of 8 locations in Jeju Island who possesses excellent wind resource according to the GUM (Guide to the Expression of Uncertainty in Measurement) to evaluate its uncertainty. Expanded uncertainty is calculated by combined standard uncertainty, which is the result of composing type A standard uncertainty with type B standard uncertainty. Although pooled standard deviation should be considered to derive type A uncertainty, we used the standard deviation of vertical wind profile exponent of each day avoiding the difficult of uncertainty evaluation of diurnal wind profile variation. It is anticipated that the evaluated uncertainties of diurnal vertical wind profile exponents at 8 locations in Jeju Island are to be registered as a national standard reference data and widely used in the relevant areas.