• Journal of the Korean earth science society
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• v.32 no.2
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• pp.190-199
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• 2011

A photovoltaic energy map that included a topography effect on the Korean peninsula was developed using the Gangneung-Wonju National University (GWNU) solar radiation model. The satellites data (MODIS, OMI and MTSAT-1R) and output data from the Regional Data Assimilation Prediction System (RDAPS) model by the Korea Meteorological Administration (KMA) were used as input data for the GWNU model. Photovoltaic energy distributions were calculated by applying high resolution Digital Elevation Model (DEM) to the topography effect. The distributions of monthly accumulated solar energy indicated that differences caused by the topography effect are more important in winter than in summer because of the dependency on the solar altitude angle. The topography effect on photovoltaic energy is two times larger with 1 km resolution than with 4 km resolution. Therefore, an accurate calculation of the solar energy on the surface requires high-resolution topological data as well as high quality input data.

• Atmosphere
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• v.22 no.2
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• pp.209-219
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• 2012

Extreme heavy snowfall episodes have been investigated in case of accumulated snowfall amount larger than 50 cm during the past ten years, in order to understand the association of low-level stability with heavy snowfall in the Yeongdong region. In general, the selected 4 events have similar synoptic setting such as the Siberian High extended to East Sea along with the Low passing by the southern Korean Peninsula, eventually inducing easterly in the Yeongdong region. Specifically moist-adiabatically neutral layer has been observed during the heavy snowfall period, which was easily identified using vertical profiles of equivalent potential temperature observed at Sokcho, whereas convective unstable layer has been formed over the East sea due to relatively warm sea surface temperature (SST) about $8{\sim}10^{\circ}C$ and lower temperature around 1~2 km above the surface, obtained from RDAPS. Difference of equivalent potential temperature between 850 hPa and surface as well as difference between air and sea temperatures altogether gradually increased before the snowfall period. Instability-induced moisture supply to the atmosphere from the East sea, being cooled and saturated by the upper cold surge, would make low-level ice cloud, and eventually move inland by the easterly flow. Heavy snowfall will be enhanced in association with low-level convergence by surface friction and upslope wind against Taebaek mountains. This study emphasizes the importance of low level stability in the Yeongdong region using the radiosonde sounding and RDAPS data, which should quantitatively be examined through numerical model as well as heat and moisture supply from the ocean.

• Atmosphere
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• v.20 no.2
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• pp.73-89
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• 2010

An updateable model output statistics (UMOS) system for daily maximum and minimum temperature ($T_M$ and $T_m$) over South Korea based on the Canadian UMOS system were developed and validated. RDAPS (regional data assimilation and prediction system) and KWRF (Korea WRF) which have quite different physics and dynamics were used for the development of UMOS system. The 20 most frequently selected potential predictors for each season, station, and forecast projection time from the 68 potential predictors of the MOS system, were used as potential predictors of the UMOS system. The UMOS equations were developed through the weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data to ensure stable equations and a smooth transition of dependency from the old model to the new model. The UMOS equations are being updated by every 7 days. The validation results of $T_M$ and $T_m$ showed that seasonal mean bias, RMSE, and correlation coefficients for the total forecast projection times are -0.41-0.17 K, 1.80-2.46 K, and 0.80-0.97, respectively. The performance is slightly better in autumn and winter than in spring and summer. Also the performance of UMOS system are clearly dependent on location, better at the coastal region than inland area. As in the MOS system, the performance of UMOS system is degraded as the forecast day increases.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.221-225
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• 2006

본 연구에서는 한계유출량(threshold runoff), 특정 유역의 토양수분 상태 및 단기 기상예보 자료 등으로부터 한강유역의 돌발홍수능(Flash Flood Guidance, FFG)을 계산할 수 있는 한국형 돌발홍수 예경보시스템을 개발하였다. 한강유역의 DEM 자료를 이용하여 미세 소유역을 구분하고 하도단면 특성을 고려한 제방 월류유량 개념을 기초로 고해상도 미세 소유역 단위의 지속시간별 한계유출량을 산정하였고, Sacramento 토양수분 모델을 통해 임의 시간의 토양수분 상태를 실시간으로 추정할 수 있는 돌발홍수 모델의 수문학적 구성요소를 개발하였다. 또한, FFG 시스템의 기상학적 구성요소로 레이더 강우 추정을 추계 동역학적 편차보정 기법을 통해 계산하였다. 상술된 수문 및 기상학적 구성요소를 바탕으로 2003년 7월 및 2004년 8월의 호우사상에 대한 유역기반의 FFG를 산정하였고, 기상청의 RDAPS(Regional Data Assimilation and Prediction System) 단기 수치예보 자료의 지속시간별 예측강수량을 활용하여 돌발홍수 발생 가능성에 대한 사례연구를 수행하였다.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.213-222
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• 2002

The 3-hour-interval prediction of ground-level temperature up to +45 hours in Seoul area is performed using dynamic linear models(DLM). Numerical outputs and observations we used as input values of DLM. According to compare DLM forecasts to RDAPS forecasts using RMSE, DLM improve the accuracy of prediction and systematic error of numerical model outputs are eliminated by DLM.

• New & Renewable Energy
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• v.7 no.1
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• pp.22-28
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• 2011

The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.74-76
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• 2010

영동지방은 서쪽으로는 태백산맥이 남북으로 위치해 있고 동쪽으로 동해와 인접해 있는 지리적인 위치로 전 계절에 걸쳐 지역 특성에 따른 국지적인 기상 현상이 많이 발생하고 있다. 특히, 대설은 영동지방의 기후 특징 중 대표적이라 할 수 있다. 대설 일수가 많고 강설량이 많은 영동지방의 강릉과 속초, 그리고 울릉도는 연 강수량에서 겨울철(12월~2월) 강수량이 각각 약 10%와 20% 이상을 차지하고 있는데 이는 우리나라 다른 지역의 5% 내외에 비하면 매우 높은 것이다. 이 지역의 강설 특징은 좁은 지리적 범위에 국한되어 나타나는 좁고 강한 강수역과 지역적으로 커다란 변화를 보이는 적설량과 강설 일수이다. 해안선으로부터 산맥의 분수계까지의 거리가 중요한 역할을 하고 있으며, 이러한 복잡한 지역에서의 강설의 발생과 강설량의 분포를 이해하기 위해서는 강설의 패턴을 분류하여 연구하는 것이 매우 중요하다. 본 연구에서는 cP 확장 시 영동지방의 강설 패턴을 하층 대류권의 바람장에 따라 산악 강설 패턴, 한기-해안 강설 패턴, 난기-해안 강설 패턴으로 분류하였다. 또한, 각 강설 패턴에 대한 종관적인 대기구조의 특성을 파악한 후 3차원 분석시스템을 이용하여, 2008년 12월 21일부터 22일까지 영동지방에 내린 대설을 한기-해안 강설 패턴으로 분류하고 분석하였다.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.69-78
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• 2010

Haines index which include the rating of atmosphere instability and dryness indicated the potential of the forest fire danger. In this study, the relationships between forest fire occurrence and Haines index were analyzed. The probability of forest fire occurrence was the highest in April and HI 5, 6 and the dryness of atmosphere was higher than the atmosphere instability. Therefore, It was proved that HI affected on the forest fire occurrence and propagation.