• Journal of Industrial Technology
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• v.35
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• pp.95-102
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• 2015

Two extreme wind speed prediction models, the EWM(Extreme wind speed model) in IEC61400-1 and the Gumbel method were compared in this study. The two models were used to predict extreme wind speeds of six different sites in Korea and the results were compared with long term wind data. The NCAR reanalysis data were used for inputs to two models. Various periods of input wind data were tried from 1 year to 50 years and the results were compared with the 50 year maximum wind speed of NCAR wind data. It was found that the EWM model underpredicted the extreme wind speed more than 5 % for two sites. Predictions from Gumbel method overpredicted the extreme wind speed or underpredicted it less than 5 % for all cases when the period of the input data is longer than 10 years. The period of the input wind data less than 3 years resulted in large prediction errors for Gumbel method. Predictions from the EWM model were not, however, much affected by the period of the input wind data.

• Journal of the Korean Solar Energy Society
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• v.32 no.1
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• pp.1-7
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• 2012

Predictions of wind speed for six different near-shore sites were made using the NCAR (National Center for Atmospheric Research) wind data. The distances between the NCAR sites and prediction sites were varied between 40km and 150km. A well-known wind energy prediction program, WindPRO, was used. The prediction results were compared with the measured data from the AWS(Automated Weather Stations). Although the NCAR wind data were located far away from the AWS sites, the prediction errors were within 9% for all the cases. In terms of sector-wise wind energy distributions, the predictions were fairly close to the measurements, and the error in predicting main wind direction was less than $30^{\circ}$. This proves that the NCAR wind data are very useful in roughly estimating wind energy in offshore or near-shore sites where offshore wind farm might be constructed in Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.319-320
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• 2008

This paper introduces remote-sensing data which can be practically applied for offshore wind resource assessment. Development of offshore wind energy is inevitable for Korea to achieve the national dissemination target of renewable energy, i.e., 5% uptil 2010. However, the only available offshore in-situ measurement, marine buoy data would not represent areal wind characteristics. Consequently, remote-sensing technology has been started to apply to offshore wind resource assessment and is actively developing. Among them, NCAR/NCEP reanalysis dataset, QuikSCAT blended dataset, and offshore wind retrieval from SAR imagery are briefly summarized in this paper.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.63-72
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• 2005

In order to understand regional wind characteristics and to estimate offshore wind resources, a wind map of the Korean Peninsula was established using remote-sensing data from the satellite, U.S. NASA Quik SCAT which has been deployed for the Sea Winds Project since 1999. According to the linear regression result between the wind map data and in-situ marine-buoy data, the correlation factor was greatly improved up to 0.87 by blending the remote-sensing data of Quik SCAT with U.S. NCEP/NCAR CDAS reanalysis data to eliminate precipitation interference and to increase temporal resolution. It is found from the established wind map that the wind speed in winter is prominent temporally and the South Sea shows spatially high energy density over the wind class 6. The reason is deduced that the north-west winds through the Yellow Sea and the north-east winds through the East Sea derived by the low pressure developed in Japan are accelerated passing through the Korea Channel and formed high wind energy region in the South Sea; the same trends are confirmed from the statistical analysis of the meteorological observation data of KMA.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.729-741
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• 2011

Wind speeds have long been estimated from C-band VV-polarized SAR data by using the CMOD algorithms such as CMOD4, CMOD5, and CMOD_IFR2. Some SAR data with HH-polarization without any observations in VV-polarization mode should be converted to VV-polarized value in order to use the previous algorithms based on VV-polarized observation. To satisfy the necessity of polarization ratio (PR) for the conversion, we retrieved the conversion parameter from full-polarized SIR-C SAR image off the east coast of Korea. The polarization ratio for SIR-C SAR data was estimated to 0.47. To assess the accuracy of the polarization ratio coefficient, pseudo VV-polarized normalized radar cross section (NRCS) values were calculated and compared with the original VV-polarized ones. As a result, the estimated psudo values showed a good agreement with the original VV-polarized data with an root mean square error by 0.99 dB. We applied the psudo NRCS to the estimation of wind speeds based on the CMOD wind models. Comparison of the retrieved wind field with the ECMWF and NCEP/NCAR reanalysis wind data showed relatively small rms errors of 1.88 and 1.91 m/s, respectively. SIR-C HH-polarized SAR wind retrievals met the requirement of the scatterometer winds in overall. However, the polarization ratio coefficient revealed dependence on NRCS value, wind speed, and incident angle.

• Journal of Industrial Technology
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• v.33 no.A
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• pp.41-48
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• 2013

A statistical downscaling methodology has been developed to investigate future daily wind speeds over South Korea. This methodology includes calibration of the statistical downscaling model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, validation of the model for the calibration period, and estimation of the future wind speed based on the general circulation model (GCM) outputs of scenario A1B of the CGCM3. Based on the scenario A1B of the CGCM3 model, the potential impacts of climate change on the daily surface wind speed is relatively small (+/- 1m/s) in South Korea.

• Journal of the Korean earth science society
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• v.31 no.5
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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.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.213-225
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• 2018

In order to access the accuracy of the gridded daily Advanced Scatterometer (hereafter DASCAT) ocean surface wind data in the surrounding of Korea, the DASCAT was compared with the wind data from buoys. In addition, the reanalysis data for wind at 10 m provided by European Centre for Medium-Range Weather Forecasts (ECMWF, hereafter ECMWF), National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR, hereafter NCEP), Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2, hereafter MERRA) were compared and analyzed. As a result, the RMSE of DASCAT for the actual wind speed is about 3 m/s. The zonal components of wind of buoys and the DASCAT have strong correlation more than 0.8 and the meridional components of wind them have lower correlation than that of zonal wind and are the lowest in the Yellow Sea (r=0.7). When the actual wind speed is below 10 m/s, the EMCWF has the highest accuracy, followed by DASCAT, MERRA, and NCEP. However, under the wind speed more than 10 m/s, DASCAT shows the highest accuracy. In the nature of error according to the wind direction, when the zonal wind is strong, all dataset has the error of more than $70^{\circ}$ on the average. On the other hand, the RMSE of wind direction was recorded $50^{\circ}$ under the strong meridional winds. ECMWF shows the highest accuracy in these results. The RMSE of the wind speed according to the wind direction varied depending on the actual wind direction. Especially, MERRA has the highest RMSE under the westerly and southerly wind condition, while the NCEP has the highest RMSE under the easterly and northerly wind condition.

• Atmosphere
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• v.22 no.1
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• pp.57-71
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• 2012

Influences of orographic and ocean effect, which depend on the detailed geographic characteristics, upon winter time (December-February) precipitation in the Yeongdong region are investigated. Most of precipitation events in the Yeongdong region during the wintertime are associated with moist northeasterly (coming from the northeast direction) winds and also the spatial distribution of precipitation shows a great difference between Mountain area (Daegwallyeong) and Coastal area (Gangneung). The linear correlation coefficient between the meteorological variables obtained from NCEP/NCAR Reanalysis Data and precipitation amount for each precipitation type is calculated. Mountain type precipitation is dominated by northeasterly wind speed of the low level (1000 hPa and 925 hPa) and characterized with more precipitation in mountain area than coastal area. However, Coastal type precipitation is affected by temperature difference between ocean and atmosphere, and characterized with more precipitation in coastal area than mountain area. The results are summarized as follows; In the case of mountain type precipitation, the correlation coefficient between wind speed at 1000 hPa (925 hPa) and precipitation amount at Daegwallyeong is 0.60 (0.61). The correlation is statistical significant at 1% level. In the case of coastal type precipitation, the correlation coefficient of temperature difference between ocean and 925 hPa (850 hPa) over the East sea area and precipitation amount at Gangneung is 0.33 (0.34). As for the mountain type precipitation, a detailed analysis was conducted in order to verify the relationship between precipitation amount at Daegwallyeong and low level wind speed data from wind profiler in Gangneung and Buoy in the East Sea. The results also show the similar behavior. This result indicates that mountain type precipitation in the Yeongdong region is closely related with easterly wind speed. Thus, the statistical analysis of the few selected meteorological variables can be a good indicator to estimate the precipitation totals in the Yeongdong region in winter time.

• Proceedings of the Korean Quaternary Association Conference
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• 2004.06a
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• pp.24-25
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• 2004

It is well known that there is an inverse relationship between the strength of Indian summer monsoon Rainfall (ISMR) and extent of Eurasian snow cover/depth in the preceding season. Tibetan snow cover/depth also affects the Asian monsoon rainy season largely. The positive correlation between Tibetan sensible heat flux and southeast Asian rainfall suggest an inverse relationship between Tibetan snow cover and southeast Asian rainfall. Developments in Regional Climate Models suggest that the effect of Tibetan snow on the ISMR can be well studied by Limited Area Models (LAMs). LAMs are used for regional climate studies and operational weather forecast of several hours to 3 days in future. The Eta model developed by the National Center for Environmental Prediction (NCEP), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Regional Climate Model (RegCM) have been used for weather prediction as well as for the study of present-day climate and variability over different parts of the world. Regional Climate Model (RegCM3) has been widely . used for various mesoscale studies. However, it has not been tested to study the characteristics of circulation features and associated rainfall over India so far. In the present study, Regional Climate Model (RegCM-3) has been integrated from 1 st April to 30th September for the years 1993-1996 and monthly mean monsoon circulation features and rainfall simulated by the model at 55km resolution have been studied for the Indian summer monsoon season. Characteristics of wind at 850hPa and 200hPa, temperature at 500hPa, surface pressure and rainfall simulated by the model have been examined for two convective schemes such as Kuo and Grell with Arakawa-Schubert as the closure scheme, Model simulated monsoon circulation features have been compared with those of NCEP/NCAR reanalyzed fields and the rainfall with those of India Meteorological Department (IMD) observational rainfall datasets, Comparisons of wind and temperature fields show that Grell scheme is closer to the NCEP/NCAR reanalysis, The influence of Tibetan snowdepth in spring season on the summer monsoon circulation features and subsequent rainfall over India have been examined. For such sensitivity experiment, NIMBUS-7 SMMR snowdepth data have been used as a boundary condition in the RegCM3, Model simulation indicates that ISMR is reduced by 30% when 10cm of snow has been introduced over Tibetan region in the month of previous April. The existence of Tibetan snow in RegCM3 also indicates weak lower level monsoon westerlies and upper level easterlies.