• 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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• 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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• 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.

• 한국태양에너지학회 논문집
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• 제35권2호
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• pp.33-41
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• 2015

A feasibility study to estimate annual energy production of an offshore wind farm was performed using MERRA reanalysis data. Two well known commercial codes commonly used to wind farm design and power prediction were used. Three years of MERRA data were used to predict annual energy predictions of the offshore wind farm close to Copenhagen from 2011 to 2013. The availability of the wind farm was calculated from the power output data available online. It was found from the study that the MERRA reanalysis data with commercial codes could be used to fairly accurately predict the annual energy production from offshore wind farms when a meteorological mast is not available.

• 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.

• Ocean and Polar Research
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• 제41권4호
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• pp.213-232
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• 2019

This study evaluates the accuracy of four satellite-composite (OSTIA, AVHRR, G1SST, FNMONC-S) and three model-reanalysis (HYCOM, JCOPE2, FNMOC-M) daily sea surface temperature (SST) data around the Korean Peninsula (KP) using ocean buoy data from 2011-2016. The results reveal that OSTIA has the lowest root mean square error (RMSE; 0.68℃) and FNMOC-S/M has the highest correction coefficients (r = 0.993) compared with observations, while G1SST, JCOPE2, and AVHRR have relatively larger RMSEs and smaller correlations. The large RMSEs were found in the western coastal regions of the KP where water depth is shallow and tides are strong, such as Chilbaldo and Deokjeokdo, while low RMSEs were found in the East Sea and open oceans where water depth is relatively deep such as Donghae, Ulleungdo, and Marado. We found that the main sources of the large RMSEs, sometimes reaching up to 5℃, in SST data around the KP, can be attributed to rapid SST changes during events of strong tidal mixing, upwelling, and typhoon-induced mixing. The errors in the background SST fields which are used in data assimilations and satellite composites and the missing in-situ observations are also potential sources of large SST errors. These results suggest that both satellite and reanalysis SST data, which are believed to be true observation-based data, sometimes, can have significant inherent errors in specific regions around the KP and thus the use of such SST products should proceed with caution particularly when the aforementioned events occur.

• 한국지구과학회지
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• 제45권3호
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• pp.192-202
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• 2024

해양재분석 자료는 관측 자료를 수치 모델에 동화함으로, 관측 자료의 시공간적인 제약을 극복하고 해양 변수 간의 물리적 상호작용을 고려한 격자화된 고해상도 정보를 제공함으로써 해양순환 및 기후 연구에 광범위하게 사용되고 있다. 이 연구에서는 기존에 생산된 12년간(2011년부터 2022년까지)의 북서태평양 지역해양 재분석 자료를 확장하여 30년간(1993년부터 2022년까지)의 1/24° 수평해상도를 갖는 장기 재분석 자료(K-ORA22E)를 생산하고, 이를 분석하여 한반도 주변해역에서의 장기 해양기후변화를 진단하였다. K-ORA22E 데이터를 통해 한반도 주변 해역의 수온 상승 경향을 분석한 결과, 쿠로시오 확장역에서 쿠로시오의 경로가 지난 30년 동안 1년에 약 6 km 씩 북상하였으며, 쿠로시오 경로의 북쪽에서 수온 상승이 두드러졌다. 한반도 주변 해역 중에서는 동해에서 수온 상승이 가장 뚜렷했다. 특히, 동해에서는 표층보다는 중층에서 수온 상승이 두드러졌으며, 동한난류의 수온 상승률은 전 지구 평균보다 2-3배 높았다. 황해저층냉수가 출현하는 황해 중앙부에서는 장기적으로 수온이 상승하였으나, 한반도 서해안과 남해안에서는 수온이 오히려 감소하는 경향이 나타났다. 이러한 수온의 장기변화의 공간적인 차이는 쿠로시오 해류의 북상에 따른 열수송의 경로와 밀접한 관련이 있을 것으로 보인다. 이 연구에서 구축된 K-ORA22E와 같은 고해상도 지역 해양 재분석 자료는 한반도 주변 해역의 장기 변동성을 이해하고 기후 변화의 영향을 분석하는 데 중요한 기초 자료로 활용될 수 있을 것이다.

• 한국태양에너지학회 논문집
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• 제34권2호
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• pp.82-90
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• 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.

• 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.

• 한국수자원학회논문집
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• 제52권1호
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• pp.61-70
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• 2019

실제증발산 자료를 융합하기 위한 Modified Kling-Gupta efficiency Fusion (KGF)방법을 제시하였고, 인공위성 및 재분석 증발산 자료인 Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16)를 활용하여 Simple Taylor skill's Score (STS)와 비교하였다. 한반도와 중국의 세가지 land cover type(i.e., cropland, grassland, forest)을 가진 flux tower에서 비교 검증을 실시하였다. 실제증발산의 융합 방법인 STS와 KGF로 계산된 가중치의 결과를 확인하면, cropland와 grassland에서 재분석 자료(GLDAS, GLEAM)가 높은 가중치 영향을 나타내지만, forest에서 융합 방법에 따라 가중치 영향이 다르게 나타났다. 전반적으로 실제증발산 융합 방법 적용 결과의 비교에서는 cropland에서는 융합에 사용된 자료에 비하여 높은 개선이 이뤄지지 않았지만, grassland와 forest 에서는 개선이 이뤄졌다. 두 방법 중 KGF의 결과가 STS의 결과에 비하여 약간 개선되는 결과를 나타내었다.