• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.83-100
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• 2020

This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.

• Atmosphere
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• v.29 no.1
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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.

• Journal of Environmental Science International
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• v.22 no.10
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1611-1623
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• 2021

Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R² were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R² were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.5
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• pp.414-422
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• 2004

To infer phylogenetic relationships among Epinephelus species inhabiting coastal regions of Korean peninsula, mitochondrial cytochrome b genes from 9 species belonging to the subfamily Epinephelinae were PCR-amplified, cloned and sequenced. Aligned cytochrome b sequences of 10 species containing one additional sequence from GenBank were 1,140 base pairs in length, including 439 variable and 330 parsimony informative sites. The cytochrome b genes of 10 species, as other vertebrates studied to date, exhibit unequal base compositions: an entirely low G content ($15.2{\pm}0.3{\%}$on average) and almost equal T, C and A contents ($29.3{\pm}0.8{\%},\;30.7{\pm}1.0{\%},\;and\;24.8{\pm}0.5{\%}$ on average, respectively).In third codon positions, transitional substitutions especially between Epinephelus species and outgroup species are almost certainly saturated or near saturation. Phylogenetic analyses were performed with sequence data from 8 Epinephelus species and 2 outgroup species (Cephalopholis urodela and Vaviola louti) by using distance-based (neighbor-joining and minimum evolution) and parsimony-based (maximum parsimony) methods. The results showed that the monophyly of the genus Epinephelus was supported by relatively high bootstrap values. However, phylogenetic relationships among E. areolatus, E. moara, E. septemfasciatus, and Epinephelus sp were poorly resolved. Within the genus Epinephelus, three resolved monophyletic groups were found: clade 1 included E. akaara and E. awoara;, clade 2 included E. fasciatus and E. merra; and clade 3 included E. akaara, E. awoara, E. fasciatus, E. merra, E. areolatus, E. moara, E. septemfasciatus and Epinephelus Sp.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.69-69
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• 2023

격자 기반의 지면모형을 구동하기에 앞서 사용자의 목적에 따른 모델의 정확도와 모델의 구동 시간의 적절한 균형을 이루는 지면 모델의 격자 크기의 설정은 중요하다. 특히, 격자 크기에 따라 화재 모의 결과 영향이 매우 클 수 있지만, 이에 관한 연구들을 거의 이루어지지 않았다. 화재 모의는 탄소 순환뿐만 아니라 물 순환에도 직접적인 영향을 미치기 때문에 이를 위한 적절한 격자 크기 설정은 중요하다. 본 연구에서는 지면모형인 NCAR Community Land Model version 5(CLM 5)-biogeochemistry (BGC) 모형과 2000년부터 2019년의 The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) 기상자료 이용하여서 지면 모델 격자 크기(1.9°×2.5°, 0.47°×0.63°, 0.25°×0.25°)에 따른 전 지구 규모의 화재 시뮬레이션 결과들을 분석하였다. 연평균 화재면적은 격자 크기가 제일 큰 1.9°×2.5° 격자의 시뮬레이션에서 연평균 450M ha로 가장 작게 나타났으며 격자의 크기가 작아질수록 화재의 크기는 증가하는 것으로 나타났다. 지면 모델의 격자가 작아짐에 따라 토양 입자의 분포가 세분화되고 이에 따라 투수 계수값이 증가하며 높은 토양수분의 분포들을 줄어들고 낮은 토양수분의 분포는 증가함을 확인하였다. 토양수분이 줄어듦에 따라 화재 연소성 정도를 나타내는 변수의 값이 증가하고 이에 따라 화재 발생빈도 및 화재 확산이 증가하여 지면 모델의 화재면적을 더 증가시키는 요인이 됨을 확인하였다. 이 연구를 바탕으로 하여 화재 모의의 불확실성 요소를 이해하고, 격자 크기에 따라 화재 모의 관련 매개변수의 수정이 필요할 것으로 판단된다.

• Atmosphere
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• v.29 no.5
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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.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.3
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• pp.169-179
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• 2014

Monthly mean surface heat fluxes in the southeastern Yellow Sea are calculated using directly observed airsea variables from an ocean buoy station including short- and longwave radiations, and COARE 3.0 bulk flux algorithm. The calculated monthly mean heat fluxes are then compared with previous estimates of climatological monthly mean surface heat fluxes near the buoy location. Sea surface receives heat through net shortwave radiation ($Q_i$) and loses heat as net longwave radiation ($Q_b$), sensible heat flux ($Q_h$), and latent heat flux ($Q_e$). $Q_e$ is the largest contribution to the total heat loss of about 51 %, and $Q_b$ and $Q_h$ account for 34% and 15% of the total heat loss, respectively. Net heat flux ($Q_n$) shows maximum in May ($191.4W/m^2$) when $Q_i$ shows its annual maximum, and minimum in December ($-264.9W/m^2$) when the heat loss terms show their annual minimum values. Annual mean $Q_n$ is estimated to be $1.9W/m^2$, which is negligibly small considering instrument errors (maximum of ${\pm}19.7W/m^2$). In the previous estimates, summertime incoming radiations ($Q_i$) are underestimated by about $10{\sim}40W/m^2$, and wintertime heat losses due to $Q_e$ and $Q_h$ are overestimated by about $50W/m^2$ and $30{\sim}70W/m^2$, respectively. Consequently, as compared to $Q_n$ from the present study, the amount of net heat gain during the period of net oceanic heat gain between April and August is underestimated, while the ocean's net heat loss in winter is overestimated in other studies. The difference in $Q_n$ is as large as $70{\sim}130W/m^2$ in December and January. Analysis of long-term reanalysis product (MERRA) indicates that the difference in the monthly mean heat fluxes between the present and previous studies is not due to the temporal variability of fluxes but due to inaccurate data used for the calculation of the heat fluxes. This study suggests that caution should be exercised in using the climatological monthly mean surface heat fluxes documented previously for various research and numerical modeling purposes.

• Atmosphere
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• v.25 no.2
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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.