• 대기
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• 제18권1호
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• pp.1-14
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• 2008

The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.

• 대기
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• 제18권1호
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• pp.71-81
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• 2008

In this study, in order to estimate high resolution precipitation with monthly time scales, Parameter-elevation Regressions on Independent Slopes Model (PRISM) was modified and configured for Korean precipitation based on elevation, distance, topographic facet, and coastal proximity. Applying this statistical downscaling model to Korean precipitation for 5 years from 2001 to 2005, we have compiled monthly grid data with a horizontal resolution of 5-km and evaluated the model using bias, root mean square error (RMSE), and correlation coefficient between the observed and the estimated. Results show that bias, RMSE, and correlation coefficient of the estimated value have a range from 0.2% to 1.0%, 19.6% (June) to 43.9% (January), and 0.73 to 0.84, respectively, indicating that the modified Korean PRISM (K-PRISM) is reasonably worked by weighting factors, i.e., topographic effect and rain shadow effect.

• 한국대기환경학회지
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• 제22권6호
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• pp.791-798
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• 2006

In order to investigate the NVOC (Natural Volatile Organic Compound) emissions from White Oak, the emission rates of isoprene were measured according to season, weather conditions, and the age of the tree. The analysis of seasonal emission rates showed that the emission rates were the highest during summer followed by spring and fall. The emission rates during summer were found to be nearly 8 times greater than those during fall. In addition, it was observed that the emission rates of isoprene depends on PAR and temperature. Moreover, the effect of age on the emission rates was studied, and the White Oak in the age range of $21{\sim}30$ had higher emission rates than that in the range of $41{\sim}50$. Accordingly, the current result indicates that the isoprene emissions are affected by both meteorological parameter and the age of a tree.

• 한국콘텐츠학회논문지
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• 제6권5호
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• pp.42-55
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• 2006

대부분의 멀티미디어 시스템들의 환경은 수동적인 배경으로 이루어진다. 그러나 가상환경에서 실세계 시뮬레이션에 있어서 지형은 바람이나 비, 구름과 같은 많은 이벤트에 영향을 미친다. 그러므로 지형과 기상 현상 모델링은 현실적인 가상환경을 시뮬레이션 하기 위하여 필요하다. 이러한 모델링에서는 높이와 지역정보 뿐만 아니라 온도와 습도와 같은 환경적 요소도 중요하다. 하나의 이벤트는 전제조건, 절차, 결과로 이루어지며, 이벤트의 결과가 다른 이벤트의 전제조건을 만족하는 형식의 인과관계를 통하여 여러 가지 이벤트들이 발생하게 된다. 본 논문에서는 등고선을 이용하여 자연현상 시뮬레이션에서 환경이 되는 개체들의 범위와 속성들을 표현하고 이를 통해 자연현상 이벤트를 표현하는 방법을 제시한다.

• 한국수산과학회지
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• 제27권5호
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• pp.572-582
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• 1994

To investigate water mass structure and DO(Dissolved Oxygen) distribution in Chinhae Bay, temperature, salinity and DO were observed in the bay in summer and winter from 1990 to 1993, and two-dimensional tidal current and parameter log($H/U^3$) were computed. Shallow water fronts in the bay were formed in summer in Kaduk channel and the central part of the bay having log($H/U^3$) values of $2.0{\sim}2.5$. Oxygen deficiency at the bottom layer in summer occurred in the western and northern part of the bay with weak tidal current, where the value of log($H/U^3$) was more than about 3.5 and $M_2$ tidal current was less than about 20 cm/s. DO concentration at the bottom layer of Kaduk channel and the central channel of the bay having the strong tidal current was more than about 3.5 mg/l. The isolines of DO concentration were nearly parallel to the isovelocity, and the concentrations correlated with the frontal location. The frontal location and DO distribution were influenced by tidal range, river inflow and meteorological conditions, and also correlated with bottom slope characteristics.

• Communications for Statistical Applications and Methods
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• 제25권1호
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• pp.15-27
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• 2018

Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.

• 대기
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• 제29권2호
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• pp.227-239
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• 2019

This paper reviews various bulk-type cloud microphysics parameterizations (BCMPs). BCMP, predicting the moments of size distribution of hydrometeors, parameterizes the grid-resolved cloud and precipitation processes in atmospheric models. The generalized gamma distribution is mainly applied to represent the hydrometeors size distribution in BCMPs. BCMP can be divided in three different methods such as single-moment, double-moment, and triple-moment approaches depending on the number of prognostic variables. Single-moment approach only predicts the hydrometeors mixing ratio. Double-moment approach predicts not only the hydrometeors mixing ratio but also the hydrometeors number concentration. Triple-moment approach predicts the dispersion parameter of hydrometeors size distribution through the prognostic reflectivity, together with the number concentrations and mixing ratios of hydrometeors. Triple-moment approach is the most time expensive method because it has the most number of prognostic variables. However, this approach can allow more flexibility in representing hydrometeors size distribution relative to single-moment and double-moment approaches. At the early stage of the development of BMCPs, warm rain processes were only included. Ice-phase categories such as cloud ice, snow, graupel, and hail were included in BCMPs with prescribed properties for densities and sedimentation velocities of ice-phase hydrometeors since 1980s. Recently, to avoid fixed properties for ice-phase hydrometeors and ad-hoc category conversion, the new approach was proposed in which rimed ice and deposition ice mixing ratios are predicted with total ice number concentration and volume.

• Wind and Structures
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• 제33권6호
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• 대한토목학회논문집
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• 제28권6B호
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• pp.675-681
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• 2008

기상자료가 부족하거나 결측인 지역의 기준 증발산량 산정을 위해서는 Hargreaves 공식의 매개변수 추정을 수행할 필요가 있다. 본 연구에서는 우리나라 전역에 걸쳐 1997년-2006년 기상자료를 바탕으로 Hargreaves 공식을 이용하여 기준 증발산량(이하 ETo)을 산정하였다. 각 지점별로 PM공식에 의해 산정한 값을 증발산량의 정해로 가정하여 Hargreaves 매개변수를 지점별로 추정하였다. 최소의 오차가 발생하도록 Hargreaves 계수를 조정한 후 Root Mean Square Error와 Nash Sutcilffe Coefficient of Efficiency분석을 통하여 추정효율이 크게 향상되는 것을 알 수 있었다. 또한 추정된 매개변수를 바탕으로 기온 자료만의 의한 Hargreaves 증발산량을 추정할 수 있도록 일반화된 하나의 회귀직선을 도출하여 보았다. 온도-Hargreaves 계수의 선형 상관관계를 이용한 Hargreaves 계수의 일반화에서는 개선의 여지가 있지만 만족스러운 결과를 보여주는 것으로 나타났다. 이 연구결과는 우리나라의 수자원, 관개분야 및 환경 운용에 많은 도움이 될 것으로 판단된다.