• Title/Summary/Keyword: Modern Era Retrospective - Analysis for Research and Applications Reanalysis Data

Search Result 10, Processing Time 0.017 seconds

Accuracy Assessment of Annual Energy Production Estimated for Seongsan Wind Farm (성산 풍력발전단지의 연간발전량 예측 정확도 평가)

  • Ju, Beom-Cheol;Shin, Dong-Heon;Ko, Kyung-Nam
    • Journal of the Korean Solar Energy Society
    • /
    • v.36 no.2
    • /
    • pp.9-17
    • /
    • 2016
  • In order to examine how accurately the wind farm design software, WindPRO and Meteodyn WT, predict annual energy production (AEP), an investigation was carried out for Seongsan wind farm of Jeju Island. The one-year wind data was measured from wind sensors on met masts of Susan and Sumang which are 2.3 km, and 18 km away from Seongsan wind farm, respectively. MERRA (Modern-Era Retrospective Analysis for Research and Applications) reanalysis data was also analyzed for the same period of time. The real AEP data came from SCADA system of Seongsan wind farm, which was compare with AEP data predicted by WindPRO and Meteodyn WT. As a result, AEP predicted by Meteodyn WT was lower than that by WindPRO. The analysis of using wind data from met masts led to the conclusion that AEP prediction by CFD software, Meteodyn WT, is not always more accurate than that by linear program software, WindPRO. However, when MERRA reanalysis data was used, Meteodyn WT predicted AEP more accurately than WindPRO.

Uncertainty Estimation of Single-Channel Temperature Estimation Algorithm for Atmospheric Conditions in the Seas around the Korean Peninsula (한반도 주변해역 대기환경에 대한 싱글채널 온도추정 알고리즘의 불확도 추정)

  • Jong Hyuk Lee;Kyung Woong Kang;Seungil Baek;Wonkook Kim
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.3
    • /
    • pp.355-361
    • /
    • 2023
  • Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

Evaluation of the Total Column Ozone in the Reanalysis Datasets over East Asia (동아시아 지역 오존 전량 재분석 자료의 검증)

  • Han, Bo-Reum;Oh, Jiyoung;Park, Sunmin;Son, Seok-Woo
    • Atmosphere
    • /
    • v.29 no.5
    • /
    • pp.659-669
    • /
    • 2019
  • This study assesses the quality of the total column ozone (TCO) data from five reanalysis datasets against nine independent observation in East Asia. The assessed datasets are the ECMWF Interim reanalysis (ERAI), Monitoring Atmosphere Composition and Climate reanalysis (MACC), Copernicus Atmosphere Monitoring Service reanalysis (CAMS), the NASA Modern-Era Retrospective analysis for Research and Applications, Version2 (MERRA2), and NCEP Climate Forecast System Reanalysis (CFSR). All datasets reasonably well capture the spatial distribution, annual cycle and interannual variability of TCO in East Asia. In particular, characteristics of TCO according to the latitude difference were similar at all points with a maximum bias of less than about 4%. Among them, CAMS and CFSR show the smallest mean bias and root-mean square error across all nine ground-based observations. This result indicates that while TCO data in modern reanalyses are reasonably good, CAMS and CFSR TCO data are the best for analysing the spatio-temporal variability and change of TCO in East Asia.

Prediction of Energy Production of China Donghai Bridge Wind Farm Using MERRA Reanalysis Data (MERRA 재해석 데이터를 이용한 중국 동하이대교 풍력단지 에너지발전량 예측)

  • Gao, Yue;Kim, Byoung-su;Lee, Joong-Hyeok;Paek, Insu;Yoo, Neung-Soo
    • Journal of the Korean Solar Energy Society
    • /
    • v.35 no.3
    • /
    • pp.1-8
    • /
    • 2015
  • The MERRA reanalysis data provided online by NASA was applied to predict the monthly energy productions of Donghai Bridge Offshore wind farms in China. WindPRO and WindSim that are commercial software for wind farm design and energy prediction were used. For topography and roughness map, the contour line data from SRTM combined with roughness information were made and used. Predictions were made for 11 months from July, 2010 to May, 2011, and the results were compared with the actual electricity energy production presented in the CDM(Clean Development Mechanism)monitoring report of the wind farm. The results from the prediction programs were close to the actual electricity energy productions and the errors were within 4%.

Evaluation of the Troposphere Ozone in the Reanalysis Datasets: Comparison with Pohang Ozonesonde Observation (대류권 오존 재분석 자료의 품질 검증: 포항 오존존데와 비교 검증)

  • Park, Jinkyung;Kim, Seo-Yeon;Son, Seok-Woo
    • Atmosphere
    • /
    • v.29 no.1
    • /
    • pp.53-59
    • /
    • 2019
  • The quality of troposphere ozone in three reanalysis datasets is evaluated with longterm ozonesonde measurement at Pohang, South Korea. The Monitoring Atmospheric Composition and Climate (MACC), European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERAI) and Modern Era Retrospective-Analysis for Research and Applications version 2 (MERRA2) are particularly examined in terms of the vertical ozone structure, seasonality and long-term trend in the lower troposphere. It turns out that MACC shows the smallest biases in the ozone profile, and has realistic seasonality of lower-tropospheric ozone concentration with a maximum ozone mixing ratio in spring and early summer and minimum in winter. MERRA2 also shows reasonably small biases. However, ERAI exhibits significant biases with substantially lower ozone mixing ratio in most seasons, except in mid summer, than the observation. It even fails to reproduce the seasonal cycle of lower-tropospheric ozone concentration. This result suggests that great caution is needed when analyzing tropospheric ozone using ERAI data. It is further found that, although not statistically significant, all datasets consistently show a decreasing trend of 850-hPa ozone concentration since 2003 as in the observation.

Wind Resource Assessment for Green Island - Dokdo (녹색섬 풍력자원평가 - 독도)

  • Kim, Hyun-Goo;Kim, Keon-Hoon;Kang, Young-Heaok
    • Journal of the Korean Solar Energy Society
    • /
    • v.32 no.5
    • /
    • pp.94-101
    • /
    • 2012
  • A Dokdo wind resource map has been drawn up for the Green Island Energy Master Plan according to Korea's national vision for 'Low Carbon Green Growth'. The micro-siting software WindSim v5.1,which is based on Computational Flow Analysis, is used with MERRA reanalysis data as synoptic climatology input data, and sensitivity analysis on turbulence model is accompanied. A wind resource assessment has been conducted for the Dokdo wind power dissemination plan, which consists of two 10kW wind turbines to be installed at the Dongdo dock and Dokdo guard building. It is evaluated that the capacity factors at Dongdo dock and Dokdo guard building are about 20% and 30% respectively, and annual and hourly variations of wind power generation have been analyzed, but summertime energy production is predicted to be only 40% of wintertime energy production.

Evaluation of bias and uncertainty in snow depth reanalysis data over South Korea (한반도 적설심 재분석자료의 오차 및 불확실성 평가)

  • Jeon, Hyunho;Lee, Seulchan;Lee, Yangwon;Kim, Jinsoo;Choi, Minha
    • Journal of Korea Water Resources Association
    • /
    • v.56 no.9
    • /
    • pp.543-551
    • /
    • 2023
  • Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

Prediction of Annual Energy Production of Wind Farms in Complex Terrain using MERRA Reanalysis Data (MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지 연간에너지발전량 예측)

  • Kim, Jin-Han;Kwon, Il-Han;Park, Ung-Sik;Yoo, Neungsoo;Paek, Insu
    • Journal of the Korean Solar Energy Society
    • /
    • v.34 no.2
    • /
    • pp.82-90
    • /
    • 2014
  • The MERRA reanalysis data provided online by NASA was applied to predict the annual energy productions of two largest wind farms in Korea. The two wind farms, Gangwon wind farm and Yeongyang wind farm, are located on complex terrain. For the prediction, a commercial CFD program, WindSim, was used. The annual energy productions of the two wind farms were obtained for three separate years of MERRA data from June 2007 to May 2012, and the results were compared with the measured values listed in the CDM reports of the two wind farms. As the result, the prediction errors of six comparisons were within 9 percent when the availabilities of the wind farms were assumed to be 100 percent. Although further investigations are necessary, the MERRA reanalysis data seem useful tentatively to predict adjacent wind resources when measurement data are not available.

Accuracy Evaluation of Daily-gridded ASCAT Satellite Data Around the Korean Peninsula (한반도 주변 해역에서의 ASCAT 해상풍 격자 자료의 정확성 평가)

  • Park, Jinku;Kim, Dae-Won;Jo, Young-Heon;Kim, Deoksu
    • Korean Journal of Remote Sensing
    • /
    • v.34 no.2_1
    • /
    • pp.213-225
    • /
    • 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.

The variation of aerosol optical depth over the polar stations of Korea (남북극 과학기지에서의 에어로졸 광학 깊이 변동성)

  • Koo, Ja-Ho;Choi, Taejin;Cho, Yeseul;Lee, Hana;Kim, Jaemin;Ahn, Dha Hyun;Kim, Jhoon;Lee, Yun Gon
    • Particle and aerosol research
    • /
    • v.13 no.4
    • /
    • pp.141-150
    • /
    • 2017
  • Using the NASA's Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis for aerosol optical depth (AOD) and satellite-observed carbon monoxide (CO) data, we examined the basic pattern of AOD variations over the three polar stations of Korea: Jangbogo and King Sejong stations in the Antarctica, and Dasan station in the Arctic area. AOD values at King Sejong and Dasan station show the maximum peaks in spring, which looks associated with the high amount of atmospheric CO emitted from the natural burning and the biomass burning. Jangbogo station shows the much less AOD compared to other two stations, and seems not strongly affected by the transport of airborne particles generated from mid-latitude regions. All three polar stations show the AOD increasing trend in general, indicating that the polar background air quality becomes polluted.