• 한국해양환경ㆍ에너지학회지
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• 제13권3호
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• pp.127-134
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• 2010

본 연구는 2007년의 태풍 Manyi와 Usagi 기간 동안에 대기모델에 의해 예측된 한반도 주변의 해면기압의 정확도를 비교하였다. 중규모 지역 모델인 RDAPS, KWRF와 본 연구에서 개발된 9 km, 3 km 수평해상도의 고해상도 WRF 모델 결과가 활용되었다. 모델로 예측된 해면기압은 한반도 주변의 AWS와 해양기상 부이 등 연안지역에 총35개 지점 관측자료와 비교하였다. 비록 4개의 모델이 태풍 기간 동안 해면기압을 잘 모의하였지만 3 km WRF가가장 좋은 예측 결과를 보였으며 지역 모델인 RDAPS와 KWRF와 비교하여 최대 69%와 60% 정확도 향상을 보였다.

• Structural Engineering and Mechanics
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• 제62권2호
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• pp.171-178
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• 2017

Nonlinear vibrations of an Euler-Bernoulli beam resting on a nonlinear elastic foundation are discussed. In search of approximate analytical solutions, the classical multiple scales (MS) and the multiple scales Lindstedt Poincare (MSLP) methods are used. The case of primary resonance is investigated. Amplitude and phase modulation equations are obtained. Steady state solutions are considered. Frequency response curves obtained by both methods are contrasted with each other with respect to the effect of various physical parameters. For weakly nonlinear systems, MS and MSLP solutions are in good agreement. For strong hardening nonlinearities, MSLP solutions exhibit the usual jump phenomena whereas MS solutions are not reliable producing backward curves which are unphysical.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.249-249
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• 2023

Spring drought forecasting in South Korea is essential due to the sknewness of rainfall which could lead to water shortage especially in spring when managed without prediction. Therefore, drought forecasting over South Korea was performed in the current study by thoroughly searching appropriate predictors from the lagged global climate variable, mean sea level pressure(MSLP), specifically in winter season for forecasting time lag. The target predictand defined as accumulated spring precipitation(ASP) was driven by the median of 93 weather stations in South Korea. Then, it was found that a number of points of the MSLP data were significantly cross-correlated with the ASP, and the points with high correlation were regionally grouped. The grouped variables with three regions: the Arctic Ocean (R1), South Pacific (R2), and South Africa (R3) were determined. The generalized linear model(GLM) was further applied for skewed marginal distribution in drought prediction. It was shown that the applied GLM presents reasonable performance in forecasting ASP. The results concluded that the presented regionalization of the climate variable, MSLP can be a good alternative in forecasting spring drought.

• Ocean and Polar Research
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• 제31권4호
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• pp.297-304
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• 2009

We investigated the response of the westerly winds over the Southern Ocean (SO) to glacial boundary conditions for the Last Glacial Maximum using the CCM3 atmospheric general circulation model. In response to glacial boundary conditions, the zonally averaged maximum SO westerly winds weakened 20-35% and were displaced toward the equator by 3-4 degrees. This weakening of the SO westerly winds arose from a substantial increase in mean sea level pressure (MSLP) in the southern part of the SO around Antarctica relative to the northern part. The increase in MSLP around Antarctica is associated with a marked temperature reduction caused by an increase in sea ice cover and ice albedo feedback during the glacial time. The weakened westerly winds in the SO and their equator-ward displacement might play a role in reducing the atmospheric $CO_2$ concentration by reducing upwelling of the carbon rich deep water during the glacial time.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.47-47
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• 2023

Drought occurs due to lack of water resources over an extended period and its intensity has been magnified globally by climate change. In recent years, drought over South Korea has also been intensed, and the prediction was inevitable for the water resource management and water industry. Therefore, drought forecasting over South Korea was performed in the current study with the following procedure. First, accumulated spring precipitation(ASP) driven by the 93 weather stations in South Korea was taken with their median. Then, correlation analysis was followed between ASP and Df4m, the differences of two pair of the global winter MSLP. The 37 Df4m variables with high correlations over 0.55 was chosen and sorted into three regions. The selected Df4m variables in the same region showed high similarity, leading the multicollinearity problem. To avoid this problem, a model that performs variable selection and model fitting at once, least absolute shrinkage and selection operator(LASSO) was applied. The LASSO model selected 5 variables which showed a good agreement of the predicted with the observed value, R²=0.72. Other models such as multiple linear regression model and ElasticNet were also performed, but did not present a performance as good as LASSO. Therefore, LASSO model can be an appropriate model to forecast spring drought over South Korea and can be used to mange water resources efficiently.

• 대기
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• 제22권3호
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• pp.287-298
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• 2012

The predictability of heavy precipitation over the Korean Peninsula is studied using THORPEX Interactive Grand Global Ensemble (TIGGE) data. The performance of the six ensemble models is compared through the inconsistency (or jumpiness) and Root Mean Square Error (RMSE) for MSLP, T850 and H500. Grand Ensemble (GE) of the three best ensemble models (ECMWF, UKMO and CMA) with equal weight and without bias correction is consisted. The jumpiness calculated in this study indicates that the GE is more consistent than each single ensemble model. Brier Score (BS) of precipitation also shows that the GE outperforms. The GE is used for a case study of a heavy rainfall event in Korean Peninsula on 9 July 2009. The probability forecast of precipitation using 90 members of the GE and the percentage of 90 members exceeding 90 percentile in climatological Probability Density Function (PDF) of observed precipitation are calculated. As the GE is excellent in possibility of potential detection of heavy rainfall, GE is more skillful than the single ensemble model and can lead to a heavy rainfall warning in medium-range. If the performance of each single ensemble model is also improved, GE can provide better performance.

• 대기
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• 제29권4호
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.

• 한국해안·해양공학회논문집
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• 제24권3호
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• pp.217-227
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• 2012

2007년 3월 31일에 영광을 비롯한 한반도 서해안에 발생한 이상파랑의 발생 원인을 관측자료와 수치모델을 이용하여 분석하였다. 사용된 자료는 조위 관측소에서 관측된 조위 자료와 AWS의 해면기압 자료로서 모두 1분 간격의 시계열 자료이다. 이러한 시계열 자료를 시간과 주기에 대한 에너지 성분으로 변환시켜줄 수 있는 웨이블렛 변환을 이용하여 이상파랑과 같이 단기적으로 불규칙하게 발생하는 변화를 분석하였다. 분석 결과를 이용하여 이상파랑의 도달시간과 진행방향을 도출하였고, 생성원인을 분석하기 위해 AWS 자료를 통해 기압 점프의 크기와 주기 및 진행방향에 대해 조사하였다. 3시간 간격의 분석일기도에 제시된 기압 분포를 이용하여 서해상에서 기압 점프의 이동 패턴을 유추하였다. 분석된 결과의 타당성을 검증하기 위해 2차원 수치모형을 이용하여 이상파랑에 대한 모의를 수행하였다. 기압 점프의 진행에 따라 발생된 해수면의 변동은 공진작용에 의해 수위가 증가하는 것으로 나타났다. 산정된 수위는 관측값과 비교할 때 과소 산정되는 것으로 나타났으나, 웨이블릿 변환을 통해 분석한 도달순서와 유사하게 수위 관측지역에 도달하는 것으로 산정되었다.

• 대한원격탐사학회지
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• 제11권2호
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• pp.17-27
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• 1995

현재 전세계적으로 널리 사용되고 있는 드보라크 방법에 의한 태풍강도 분석법을 1991년 우리나라에 영향을 준 6개 태풍사례에 대해 실제 적용하여 강도분석을 하였다. 또한 분석된 태풍 강도를 이용하여 태풍의 중심기압과 최대풍속을 산출하는 상관 관계식을 계산하여 제시하였다. ORCHID 태풍에 이 관계식을 실제 적용하여 관측값과 비교하여 그 정확도를 평가하였다. 그 결 과 중심기압(MSLP : Minimum Sea Level Pressure)과 최대풍속(MWS : Maximum Wind Speed)이 관측값보다 약간 낮은 값을 보였지만 전체적인 패턴은 비슷하게 나타났다. 그러나 미국 국립 해양 대기청(NOAA) 및 일본 기상청(NAA)에 의해 작성된 상관 관계표로 산출된 값은 관측 값과는 많은 차이를 보여 주었다. One of the world widely used methods in determining the intensity of a typhoon is Dvorak's technique. By applying the Dvorak's method to the typhoons which affected our country in various degress and extents without regard to their individual severity, we estimated their intensity for six different cases of typhoons. We have derived a regression equation of estimating the central pressures and maximum wind speeds for the six selected typhoons. Their intensity was estimated from the Dvork's method using GMS satellite image data. The derived equation has tested to typhoon ORCHID and the computed values have been compared with the direct observations in its central pressure and maximum wind speed. The computed values in the Dvork's method are smaller in their magnitudes than the observed corresponding values. But their relative magnitudes do not change so much at each different time step. But our results are significantly different from those of NOAA and JMA. The cause of differences are not investigated in depth in this analysis.