• 한국태양에너지학회 논문집
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• 제37권2호
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• pp.1-11
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• 2017

The investigation on reliability of ERA-Interim reanalysis wind data was conducted using wind data from the five met masts measured at inland and coastal areas, Jeju island. Shinchang, Handong, Udo, Susan and Cheongsoo sites were chosen for the met mast location. ERA-Interim reanalysis data at onshore and offshore twenty points over Jeju Island were analyzed for creating Wind Statistics using WindPRO software. Reliability of ERA-Interim reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those predicted at the interest point using the Wind Statistics. The relative errors were calculated for annual average wind speed and annual energy production. In addition, the trend of the error was analyzed with distance from met mast. As a result, ERA-Interim reanalysis wind data was more suitable for offshore wind resource assessment than onshore.

• 동력기계공학회지
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• 제20권4호
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• pp.44-51
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• 2016

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.

• 대한원격탐사학회지
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• 제29권6호
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• pp.595-600
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• 2013

In order to spatially interpolate the near-surface temperature (Ta) values, satellite and reanalysis methods were used from previous studies. Accuracy of reanalysis Ta was generally better than that of satellite-based Ta, but spatial resolution of reanalysis Ta was large to use at local scale studies. Our purpose is to evaluate accuracy of reanalysis Ta and satellite-based Ta according to elevation from April 2011 to March 2012 in Northeast Asia that includes various topographic features. In this study, we used reanalysis data that is ERA-Interim produced by European Centre for Medium-Range Weather Forecasts (ECMWF), and estimated satellite-based Ta using Digital Elevation Meter (DEM), Normalized Difference Vegetation Index (NDVI), difference between brightness temperature of $11{\mu}m$ and $12{\mu}m$, and Land Surface Temperature (LST) data. The DEM data was used as auxiliary data, and observed Ta at 470 meteorological stations was used in order to evaluate accuracy. We confirmed that the accuracy of satellite-based Ta was less accurate than that of ERA-Interim Ta for total data. Results of analyzing according to elevation that was divided nine cases, ERA-Interim Ta showed higher accurate than satellite-based Ta at the low elevation (less than 500 m). However, satellite-based Ta was more accurate than ERA-Interim Ta at the higher elevation from 500 to 3500 m. Also, the width of the upper and lower quartile appeared largely from 2500 to 3500 m. It is clear from these results that ERA-Interim Ta do not consider elevation because of large spatial resolution. Therefore, satellite-based Ta was more effective than ERA-Interim Ta in the regions that is range from 500 m to 3500 m, and satellite-based Ta was recommended at a region of above 2500 m.

• 대기
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• 제26권4호
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• pp.649-663
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• 2016

This study investigates eddy transports in terms of space and time for momentum, heat, and moisture, emphasizing comparison of the results in three reanalysis data sets including ERA-Interim from the European Center for Medium-range Weather Forecasts (ECMWF), NCEP2 from the National Center for Environmental Prediction and the Department of Energy (NCEP-DOE), and JRA-55 from the Japan Meteorological Agency (JMA) during boreal winter. The magnitudes for eddy transports of momentum in ERA-Interim are represented as the strongest value in comparison of three data sets, which may be mainly come from that both zonal averaged meridional and zonal wind tend to follow the hierarchy of ERA-Interim, NCEP2, and JRA-55. Whereas in relation to heat and moisture eddy transports, those of NCEP2 are the strongest, implying that zonal averaged air temperature (specific humidity) tend to follow the raking of NCEP2, ERA-Interim, and JRA-55 (NCEP2, JRA-55, and ERA-Interim), except that transient eddy transports for heat in ERA-Interim are the strongest involving both meridional wind and air temperature. The stationary and transient eddy transports in the context of space and time correlation, and intensity of standard deviation demonstrate that the correlation (intensity of standard deviation) influence the structure (magnitude) of eddy transports. The similarity between ERA-Interim and NCEP2 (ERA-Interim and JRA-55) of space correlation (time correlation) closely resembles among three data sets. A resemblance among reanalysis data sets of space correlation is larger than that of time correlation.

• 대기
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• 제25권3호
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• pp.543-557
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• 2015

The present study examines an interaction between the eddy and mean meridional circulation (MMC) comparing the results in three reanalysis data sets including ERA-Interim, NCEP2, and JRA-55 during the boreal winter in the Northern Hemisphere. It is noteworthy that the JRA-55 tends to produce stronger MMC compared to those of others, which is mainly due to the weak eddy flux. ERA-Interim represents the ensemble averages of MMC. The MMC-eddy interaction equation was adopted to investigate the scale interaction of the eddy momentum flux (EMF), eddy heat flux (EHF), and diabatic heating (DHT) with MMC. The EMF (EHF) shows a significant correlation coefficient with streamfunction under (above) 200 hPa-level. The perturbation (time mean) part of each eddy is dominant compared to another part in the EMF (EHF). The DHT is strongly interacted with streamfunction in the region between the equator and extra-tropical latitude over whole vertical column. Thus, the dominant term in each significant region modulates interannual variability of MMC. The inverse (proportional) relationship between MMC and pressure (meridional) derivative of the momentum (heat) divergence contributions is well represented in the three reanalysis data sets. The region modulated interannual variability of MMC by both EMF and DHT (EHF) is similar in ERA-Interim and JRA-55 (ERA-Interim and NCEP2). JRA-55 shows a lack of significant region of EHF due to the high resolution, compared to other data sets.

• 대기
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• 제28권4호
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• pp.415-425
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• 2018

The roles of atmospheric heating formation and distribution on the global circulation are of utmost importance, and those are directly related to not only spatial but also temporal characteristics of monsoon system. In this study, before we clarify the characteristics of apparent heat source <$Q_1$> and moisture sink <$Q_2$>, comparisons of three reanalysis datasets (NCEP2, ERA-Interim, and JRA-55) in its global or regional patterns are performed to clearly evaluate differences among datasets. Considering inter-hemispheric difference of global monsoon regions, seasonal means of June-July-August and December-January-February, which is summer (winter) and winter (summer) in the Northern (Southern) Hemisphere are employed respectively. Here we show the characteristics of eight different regional monsoon regions and find contributions of <$Q_2$> to <$Q_1$> for the regional monsoon regions. Each term in apparent heat source and moisture sink is shown to come from the ERA-Interim dataset, since the ERA-Interim could be representative of three datasets. The NCEP2 data has a different characteristic in the ratio of <$Q_2$> and <$Q_1$> because it overestimates <$Q_1$> compared to the other two different datasets. The Australia monsoon has been performing better over time, while some regional monsoons (South America, North America, and North Africa) have been showing increasing data inconsistency. In addition, the three reanalysis datasets are getting different marching with time, in particular since the early 2000s over South America, North America, and North Africa monsoon regions. The recent inconsistency among the three datasets that may be associated with the global warming hiatus remains unexplored.

• 대기
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• 제29권5호
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• pp.659-669
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• 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.

• 대기
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• 제25권2호
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• pp.235-248
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• 2015

In this study, we analyzed the three dimensional variations (latitude, longitude, and height of Jet core) and wind speed of upper Jet stream in the East Asian region using recent 35 years (1979~2013) of four reanalysis data (NCEP-R2, MERRA, ERA-Interim. and JRA-55). Most of Jet core is located in $30.0{\sim}37.5^{\circ}N$ and $13.0{\sim}157.5^{\circ}E$ although there are slight differences among the four reanalysis data. The wind speed differences among reanalysis are about $3m\;s^{-1}$ regardless of seasons, the weakest in NCEP-R2 and the strongest in JRA-55. Although significance level is not high, most of reanalysis showed that the Jet core has a tendency of southward moving during spring and winter, but moving northward during summer and fall. This amplified seasonal variation of Jet core suggests that seasonal variations of weather/climate can be increased in the East Asian region. The longitude of Jet core has a tendency of systematically westward moving and decreasing of zonal variations regardless of averaging methods and reanalysis data. In general, the Jet core shows a tendency of moving south-west-ward and upward, getting intensified during spring and winter regardless of the reanalysis data. However, the Jet core shows a tendency of moving westward and downward, and getting weakened during summer. In fall, there were no distinctive trends not only in wind speed but also three dimensional locations compared to other seasons. Although the significance levels are not high and variation patterns are slightly different according to the reanalysis data, our findings are more or less different from the previous results. So, more works are needed to clarify the three dimensional variation patterns of Jet core over the East Asian region as a result of global warming.

• 대기
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• 제29권1호
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• pp.53-59
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• 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.

• 대한원격탐사학회지
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• 제34권6_2호
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• pp.1261-1272
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• 2018

북극 지역의 대기 온도는 바다 및 해빙, 대기 사이의 에너지 교환에 큰 역할을 하므로 북극 대기 온도를 정확하게 파악하는 것은 중요하다. 하지만 현장 관측 자료들은 북극 대기 온도의 공간적인 분포를 나타내는 데에 한계가 있다. 따라서 본 연구에서는 부이(buoy) 자료와 Advanced Microwave Scanning Radiometer 2(AMSR2) 위성자료를 이용하여 기계학습 기반 여름철 대기 온도 추정 모델을 구축하였다. 기계학습으로는 random forest(RF) 및 support vector machine(SVM)을 사용하였으며, AMSR2 관측 시간에 따라 하루 두 번의 대기 온도를 추정하였다. 또한 추정된 대기 온도를 유럽 중기예보센터(European Centre for Medium-Range Weather Forecasts, ECMWF)의 ERA-Interim 재분석자료의 대기 온도와 공간 분포를 비교하였다. 교차 검증 결과 두 가지 기계학습 기법 모두 0.84-0.88의 $R^2$ 및 $1.31-1.53^{\circ}C$의 RMSE를 보였다. 공간적인 분포에서 IABP 부이 관측 자료가 존재하지 않는 바렌츠해(Barents Sea), 카라해(Kara Sea) 및 배핀만(Baffin bay) 지역에서는 기계학습 모델이 ERA-Interim 대기 온도에 비하여 과소 추정하는 경향을 보였다. 본 연구는 경험적인 북극 대기 온도 추정의 가능성과 한계점을 서술하였다.