• New & Renewable Energy
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• v.1 no.1 s.1
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• pp.44-53
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• 2005

To understand general status of the national wind environment and to distinguish potential areas to be developed as a largescale wind farm, a synoptic wind map of the Korean Peninsula is established by processing remote sensing data of the satellite, NASA QuikSCAT which Is deployed for the SeaWinds Project since 1999. According to the validation results obtained by comparing with the measurement data of marine buoys of KMA(Korea Meteorological Administration), the cross-correlation factor Is greatly Improved up to 0.87 by blending the sea-surface dat3 of QuikSCAT with NCEP/NCAR CDAS data. It is found from the established synoptic wind map that the wind speed in winter is prominent temporally and the South Sea shows high energy density up to the wind class 6 spatially. The reason is deduced that the northwest winds through the yellow Sea and the northeast 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 by the statistical analysis of meteorological observation data of KMA.

• Atmosphere
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• v.26 no.3
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• pp.387-400
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• 2016

In this study, the atmospheric $CO_2$ concentrations estimated by CT2013B, a recent version of CarbonTracker, are compared with $CO_2$ measurements from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project during 2010-2011. CarbonTracker is an inversion system that estimates surface $CO_2$ fluxes using atmospheric $CO_2$ concentrations. Overall, the model results represented the atmospheric $CO_2$ concentrations well with a slight overestimation compared to observations. In the case of horizontal distribution, variations in the model and observation difference were large in northern Eurasia because most of the model and data mismatch were located in the stratosphere where the model could not represent $CO_2$ variations well enough due to low model resolution at high altitude and existing phase shift from the troposphere. In addition, the model and observation difference became larger in boreal summer. Despite relatively large differences at high latitudes and in boreal summer, overall, the modeled $CO_2$ concentrations fitted well to observations. Vertical profiles of modeled and observed $CO_2$ concentrations showed that the model overestimates the observations at all altitudes, showing nearly constant differences, which implies that the surface $CO_2$ concentration is transported well vertically in the transport model. At Narita, overall differences were small, although the correlation between modeled and observed $CO_2$ concentrations decreased at higher altitude, showing relatively large differences above 225 hPa. The vertical profiles at Moscow and Delhi located on land and at Hawaii on the ocean showed that the model is less accurate on land than on the ocean due to various effects (e.g., biospheric effect) on land compared to the homogeneous ocean surface.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.1
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• pp.33-41
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• 2015

Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.149-163
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• 2004

Evapotranspiration (ET) is a critical component of the hydrologic cycle which influences economic activities as well as the natural ecosystem. While there have been numerous studies on ET estimation for homogeneous areas using point measurements of meteorological variables, monitoring of spatial ET has not been possible at landscape - or watershed - scales. We propose a site-specific application of the land surface model, which is enabled by spatially interpolated input data at the desired resolution. Gyunggi Province of South Korea was divided into a regular grid of 10 million cells with 30m spacing and hourly temperature, humidity, wind, precipitation and solar irradiance were estimated for each grid cell by spatial interpolation of synoptic weather data. Topoclimatology models were used to accommodate effects of topography in a spatial interpolation procedure, including cold air drainage on nocturnal temperature and solar irradiance on daytime temperature. Satellite remote sensing data were used to classify the vegetation type of each grid cell, and corresponding spatial attributes including soil texture, canopy structure, and phenological features were identified. All data were fed into a standalone version of SiB2(Simple Biosphere Model 2) to simulate latent heat flux at each grid cell. A computer program was written for data management in the cell - based SiB2 operation such as extracting input data for SiB2 from grid matrices and recombining the output data back to the grid format. ET estimates at selected grid cells were validated against the actual measurement of latent heat fluxes by eddy covariance measurement. We applied this system to obtain the spatial ET of the study area on a continuous basis for the 2001-2003 period. The results showed a strong feasibility of using spatial - data driven land surface models for operational monitoring of regional ET.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.3
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• pp.285-296
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• 2003

The measurement of the radiation energy, trunk temperature, leaf area index (LAI), air temperature, vapor pres-sure, and precipitation has been conducted under a mixed forest at Kwangneung Arboretum during the period of 2001. Characteristics of the diurnal and seasonal variation of the radiative energy were investigated. The aerodynamic roughness length was determined as about 1.6 m and the mean albedo was about 0.1 The downward short-wave radiation was linearly correlated with the net radiation and its correlation coefficient was about 0.96. From this linear relation, the heating coefficient was calculated and its annual mean value was about 0.21 The albedo and heating coefficient was varied with season, surface characteristics, and meteorological conditions. The diurnal and seasonal variations of radiation energy were discussed in terms of the surface characteristics and meteorological conditions. In the daytime, during clear skies, net radiation was dominated by the shortwave radiation. In presence of clouds and fog, the radiation energy was diminished. At night, the net radiation was entirely dominated due to the net longwave radiation. There was no distinct diurnal variation in net radiation flux during the overcast or rainy days. The net radiation was strongest in spring and weakest in winter. The seasonal development in leaf area was also reflected in a strong seasonal pattern of the radiation energy balance. The timing, duration, and maximum leaf area and trunk temperature were found to be an important control on radiation energy budget. The trunk temperature was either equal or warmer than air temperature during most of the growing season because the canopy could absorb a substantial amount of sunlight. After autumn (after the middle of October), the trunk temperature was consistently cooler than air temperature.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.549-560
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• 2019

The effects of the coal-fired power plant emissions, as the biggest point source of air pollutants, on spatiotemporal surface air pollution over the remote area are investigated in this study, based on a set of date selection and statistical technique to consider meteorological and geographical effects in the emission-concentration (source-receptor) relationship. We here proposed the sophisticated technique of data processing to separate and quantify the effects. The data technique comprises a set of data selection and statistical analysis procedure that include data selection criteria depending on meteorological conditions and statistical methods such as Kolmogorov-Zurbenko filter (K-Z filter) and empirical orthogonal function (EOF) analysis. The data selection procedure is important for filtering measurement data to consider the meteorological and geographical effects on the emission-concentration relationship. Together with meteorological data from the new high resolution ECMWF reanalysis 5 (ERA5) and the Korea Meteorological Administration automated surface observing system, air pollutant emission data from the telemonitoring system (TMS) of Dangjin and Taean power plants as well as spatio-temporal air pollutant concentrations from the air quality monitoring system are used for 4 years period of 2014-2017. Since all the data used in this study have the temporal resolution of 1 hour, the first EOF mode of spatio-temporal changes in air pollutant concentrations over the Seoul metropolitan area (SMA) due to power plant emission have been analyzed to explain over 97% of total variability under favorable meteorological conditions. It is concluded that SO₂, NO₂, and PM₁₀ concentrations over the SMA would be decreased by 0.468, 1.050 ppb, and 2.045 ㎍ m^-3 respectively if SO₂, NO₂, and TSP emissions from Dangjin power plant were reduced by 10%. In the same way, the 10% emission reduction in Taean power plant emissions would cause SO₂, NO₂, and PM₁₀ decreased by 0.284, 0.842 ppb, and 1.230 ㎍ m^-3 over the SMA respectively. Emissions from Dangjin power plant affect air pollution over the SMA in higher amount, but with lower R value, than those of Taean under the same meteorological condition.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.150-156
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• 2017

A frozen road surface increases traffic accidents during the winter season. Hence, information on easily-frozen road sections and their specificities are required to prevent traffic accidents. Frozen road surfaces are determined by equipment measuring road surface temperatures. However, there are limitations in investigating the entire road network. Therefore, it is imperative to develop new methods that effectively determine road surface freezing risks. Meteorologically, road surfaces are frozen when the actual temperature cools down to the dew point temperature. Under this condition, there is likely to be frost if relative humidity reaches 100% and frozen road surfaces as the temperature gets lower. Meteorological characteristics give us an alternative to a direct measurement road surface temperature to estimate risks of road surface freezing. Based on the clues, the relationship between severity of traffic accidents and temperature changes is empirically investigated using Paju weather data. The results reveal that as the temperature gets lower and changes in current temperature are relatively small, the severity of traffic accidents become higher. In addition, the same is true when the difference between current temperature and the dew point temperature is relatively small, as it increases possibilities of road surface freezing. Future studies must investigate how current temperature and the dew point temperature affect road surface freezing and thereby establish a time-space scope to estimate possible road surface freezing sections using only weather and road material type data. This would provide invaluable information for predicting and preventing frozen road accidents based on weather patterns.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.47-53
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• 2021

The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.481-494
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• 2018

The accurate radiative transfer model simulation is essential for an accurate ozone profile retrieval using optimal estimation from backscattered ultraviolet (BUV) measurement. The input parameters of the radiative transfer model are the main factors that determine the model accuracy. In particular, meteorological parameters such as temperature and surface pressure have a direct effect on simulating radiation spectrum as a component for calculating ozone absorption cross section and Rayleigh scattering. Hence, a sensitivity of UV ozone profile retrievals to these parameters has been investigated using radiative transfer model. The surface pressure shows an average error within 100 hPa in the daily / monthly climatological data based on the numerical weather prediction model, and the calculated ozone retrieval error is less than 0.2 DU for each layer. On the other hand, the temperature shows an error of 1-7K depending on the observation station and altitude for the same daily / monthly climatological data, and the calculated ozone retrieval error is about 4 DU for each layer. These results can help to understand the obtained vertical ozone information from satellite. In addition, they are expected to be used effectively in selecting the meteorological input data and establishing the system design direction in the process of applying the algorithm to satellite operation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.107-116
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• 2020

In this data paper, we share the dataset obtained during 2019 from the test-bed to develop soil moisture estimation technology for upland fields, which was built in Seosan and Taean, South Korea on May 3. T his dataset includes various eco-hydro-meteorological variables such as soil moisture, evapotranspiration, precipitation, radiation, temperature, humidity, and vegetation indices from the test-bed nearby the Automated Agricultural Observing System (AAOS) in Seosan operated by the Korea Meteorological Administration. T here are three remarkable points of the dataset: (1) It can be utilized to develop and evaluate spatial scaling technology of soil moisture because the areal measurement with wide spatial representativeness using a COSMIC-ray neutron sensor as well as the point measurement using frequency/time domain reflectometry (FDR/TDR) sensors were conducted simultaneously, (2) it can be used to enhance understanding of how soil moisture and crop growth interact with each other because crop growth was also monitored using the Smart Surface Sensing System (4S), and (3) it is possible to evaluate the surface water balance by measuring evapotranspiration using an eddy covariance system.