• 한국환경과학회지
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• 제21권4호
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• pp.517-533
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• 2012

This study calculated wind speed at the height of 10 m using a disaster prediction model(Florida Public Hurricane Loss Model, FPHLM) that was developed and used in the United States. Using its distributions, a usable information of surface wind was produced for the purpose of disaster prevention when the typhoon attack. The advanced research version of the WRF (Weather Research and Forecasting) was used in this study, and two domains focusing on South Korea were determined through two-way nesting. A horizontal time series and vertical profile analysis were carried out to examine whether the model provided a resonable simulation, and the meteorological factors, including potential temperature, generally showed the similar distribution with observational data. We determined through comparison of observations that data taken at 700 hPa and used as input data to calculate wind speed at the height of 10 m for the actual terrain was suitable for the simulation. Using these results, the wind speed at the height of 10 m for the actual terrain was calculated and its distributions were shown. Thus, a stronger wind occurred in coastal areas compared to inland areas showing that coastal areas are more vulnerable to strong winds.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2010년도 추계학술대회 초록집
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• pp.189.1-189.1
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• 2010

The wind farm where the wind velocity condition is excellent and economical can be established to produce power with the multiple wind power turbine. The wind velocity which is suitable to Wind Power Development must be evaluated for searching the economical wind farm on planning the wind farm. In this paper, based on wind speed data at 24 locations in Korea from 1971 through 2009, the basic wind velocity which can be applied to designing wind power development is estimated using the statiscal process. The wind velocity which is measured from observation stations is revised according to wind gauge's height and Circumferential environment. The wind speeds for 200 year's return period in 24 locations are determined using the Gumbel's distribution.

• 한국환경과학회지
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• 제14권9호
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• pp.851-860
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• 2005

In order to how well predict ISCST3(lndustrial Source Complex Short Term version 3) model dispersion of air pollutant at point source, sensitivity was analysed necessary parameters change. ISCST3 model is Gaussian plume model. Model calculation was performed with change of the wind speed, atmospheric stability and mixing height while the wind direction and ambient temperature are fixed. Fixed factors are wind direction as the south wind(l80") and temperature as 298 K(25 "C). Model's sensitivity is analyzed as wind speed, atmospheric stability and mixing height change. Data of stack are input by inner diameter of 2m, stack height of 30m, emission temperature of 40 "C, outlet velocity of 10m/s. On the whole, main factor which affects in atmospheric dispersion is wind speed and atmospheric stability at ISCST3 model. However it is effect of atmospheric stability rather than effect of distance downwind. Factor that exert big influence in determining point of maximum concentration is wind speed. Meanwhile, influence of mixing height is a little or almost not.

• 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.

• 응용통계연구
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• 제24권6호
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• pp.1225-1235
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• 2011

본 논문은 수치기상모형에 의해 계산된 수치기상모의풍속($1km{\times}1km$ 해상도)의 정확도를 향상시키기 위한 통계적 보정법을 제안하였다. 이를 위해 남한전역을 $1km{\times}1km$ 격자로 나눈 지점(345,682지점)에 적합한 통계적 바람장 모형으로 부터 남한지역의 바람장을 추정하는 절차와 격자지점별/월별 보정인자를 계산하여 추정된 바람장과 수치 기상모의풍속간의 간극을 보정하는 절차로 이루어진 보정인자법을 개발하였다. 또한 75개 기상관측소지점에서 계산된 수치기상모의풍속자료에 보정인자법을 적용시켜 본 논문에서 제안된 보정법의 유용성을 보였다.

• 한국해안·해양공학회논문집
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• 제29권1호
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• pp.12-19
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• 2017

풍력 개발을 위한 해상기상탑은 초기 설치비와 유지보수비가 크기 때문에 윈드 라이다와 같은 원격관측장비를 이용하여 기상탑을 대체할 필요가 있다. 본 연구에서는 해상기상탑에서 윈드 라이다를 동시 운영하고 수집된 풍속 및 풍향의 관측결과를 상호 비교하여 윈드 라이다의 적용성을 검증하였다. 높이별 풍속 및 풍향 관측결과 두 자료간의 크기 및 경향 등의 통계적 특성 차이는 거의 없으며, 기상탑 관측자료는 구조물 차폐영향에 의한 오차가 발생하는 반면, 윈드 라이다는 오차가 없는 보다 정확한 자료를 얻을 수 있는 것을 확인하였다.

• 한국태양에너지학회 논문집
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• 제28권3호
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• pp.45-52
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• 2008

In order to clarify characteristics of variation in wind energy over a long-term period, an investigation was carried out at Seoguang site on Jeju island. The wind data for 10 years from Automatic Weather System (AWS) were analyzed for each year. The variation in the annual energy production (AEP) for the 2 MW wind turbine was estimated through statistical work. The result shows that the range of the yearly average wind speed at 15 m above ground level for 10 years was from -22.6% to +13.7%, which is wider range than that in Japan. The coefficient of variation for the AEP was 22.7%, which is about twice of that for the yearly average wind speed. Therefore, for estimating the wind energy potential accurately at a given site, the wind data should be analyzed over a long-term period based on the data from the meteorological station.

• 한국지구과학회지
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• 제31권5호
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• pp.475-487
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• 2010

Sea surface wind field was retrieved from high-resolution SIR-C SAR data by using CMOD algorithms off the east coast of Korea. In order to extract wind direction information from SAR data, a two-dimensional spectral analysis method was applied to the normalized radar cross section of the image. An $180^{\circ}$-ambiguity problem in the determination of wind direction was solved by selecting a direction nearest to the wind vector of the ECMWF reanalysis data. Comparison of the wind retrieval patterns with the ECMWF and NCEP/NCAR dataset showed RMS errors in the range of 1.30 to $1.72\;ms^{-1}$. In contrast, comparison of wind directions revealed large errors of greater than $60^{\circ}$, which is enormously higher than the permitted limit of about $20^{\circ}$ for satellite scatterometer winds. Compared with wind speed results from different algorithms, wind vectors based on commonly-used CMOD4 algorithm showed good agreement with those derived by other algorithms such as CMOD_IFR2 and CMOD5, particularly at medium winds from 4 to $8\;ms^{-1}$. However, apparent discrepancy appeared at low winds (< $4\;ms^{-1}$). This study also addressed an importance of accurate wind direction data to improve the accuracy of wind speed retrieval and discussed potential causes of wind retrieval errors from SAR data.

• 한국환경과학회지
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• 제16권10호
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• pp.1127-1137
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• 2007

We focused on effects on data assimilation of simulated wind fields by using upper-air observations (wind profiler and sonde data). Local Analysis Prediction System (LAPS), a type of data assimilation system, was used for wind field modeling. Five cases of simulation experiments for sensitivity analysis were performed: which are EXP0) non data assimilation, EXP1) surface data, EXP2) surface data and sonde data, EXP3) surface data and wind profiler data, EXP4) surface data, sonde data and wind profiler data. These were compared with observation data. The result showed that the effects of data assimilation with wind profiler data were found to be greater than sonde data. The delicate wind fields in complex coastal area were simulated well in EXP3. EXP3 and EXP4 using wind profiler data with vertically high resolution represented well sophisticated differences of wind speed compared with EXP1 and EXP2, this is because the effects of wind profiler data assimilation were sensitively adjusted to first guess field than those of sonde observations.

• Journal of the Korean Data and Information Science Society
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• 제28권4호
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• pp.797-810
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• 2017

한반도는 매년 태풍의 위험에 노출되어 있다. 태풍은 강풍과 강우가 동반되는 열대성 저기압으로 사회 경제적으로 막대한 피해를 유발한다. 현재의 자연재해 경고 시스템은 풍속과 강우를 구분하여 위험을 감지토록 설계되어 강풍과 폭우를 동반한 태풍의 위험을 경고하는데 한계점이 존재한다. 코플라모형은 확률변수들 사이의 복잡한 의존성 구조를 파악하기 위해 단변량분포의 집합을 다변량분포로 연결하는 모형으로 강우, 홍수, 가뭄 등의 분야에서 활발하게 연구되고 있다. 본 연구에서는 한반도에서 태풍에 가장 많이 노출된 도시인 부산과 제주도의 기상 관측소 (ASOS)에서 수집된 1904년 4월 9일부터 2015년 12월 31일까지 일강수량 (precipitation), 일최대풍속 (maximum wind speed) 자료를 이용하였다. 각 변수의 주변부확률을 추정하기 위해 두꺼운 꼬리 분포인 로그정규분포, 감마분포, 와이블분포를 고려하였다. 주변부 확률분포의 적합성검정은 Kolmogorov-Smirnov와 Cramervon-Mises, Anderson-Darling 검정통계량을 이용하였다. 코플라모형을 위해 순위를 기반으로 한 유사자료 (pseudo observation)를 생성하여 두 변수 간 의존성을 추정하였다. 강풍과 폭우의 의존성을 설명하기 위한 코플라모형으로 타원형, 나선형, 극단치 코플라모형이 고려되었다. 코플라모형의 적합성은 Cramer-von-Mises로 검정하였고, 교차검증을 통해 최적모형을 선택하였다. 연구결과 일강우량과 풍속의 주변부 확률분포로 대부분 로그정규분포가 적합하였다. 부산의 일평균풍속에 따른 일강우량은 t 코플라, 일최대풍속에 따른 일강우량은 Clayton 코플라가 최적모형으로 선정되었다. 제주도의 일최대풍속에 따른 일강우량은 정규코플라, 일강우량에 따른 일평균풍속은 Frank 코플라, 일강우량에 따른 일최대풍속은 Husler-Reiss 코플라가 최적모형으로 선택되었다.