• Atmosphere
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• v.30 no.3
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• pp.257-276
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• 2020

Faithful evaluation of the meteorological input is a prerequisite for a better understanding of air quality model performance. Despite the importance, the preliminary meteorological assessment has rarely been concerned. In this study, we aim to evaluate the performance of the Weather Research and Forecasting (WRF) model conducting a year-long high-resolution meteorological simulation in 2016 over the Seoul metropolitan area. The WRF model was configured based on a series of sensitivity simulations of initial/boundary meteorological conditions, land use mapping data, reanalysis grid nudging method, domain nesting method, and urban canopy model. The simulated results of winds, air temperature, and specific humidity in the atmospheric boundary layer (ABL) were evaluated following statistical evaluation guidance using the surface and upper meteorological measurements. The statistical evaluation results are presented. The model performance was interpreted acceptable for air quality modeling within the statistical criteria of complex conditions, showing consistent overestimation in wind speeds. Further statistical analysis showed that the meteorological model biases were highly systematic with systematic bias fractions (f_SB) of 20~50%. This study suggests that both the momentum exchange process of the surface layer and the ABL entrainment process should be investigated for further improvement of the model performance.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.482-491
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• 2012

Because the satellite imagery can detect the radiative heat from the surface using the thermal IR (TIR) channel, there have been many efforts to verify the relationship between the land surface temperature (LST) and urban heat island. However, the relationship between geomorphological characteristics like surface aspects and LST is relatively less studied. Therefore, the geomorphological elements, for example, surface aspects and surface slopes, are considered to evaluate their effects on the change of the surface temperature distribution using the Landsat 7 ETM+ TIR channel and the possibility of the image to detect anthropogenic heat from the surface. We found that the surface aspect is ignorable but the surface slope with the sun elevation influences on the surface temperature distribution. Also, the radiative heat from the surface to the atmosphere could not be accurately recorded by the satellite image due to the surface slope but the slope correction process used in this study could correct the surface temperature under slope condition and the slope correction, in fact, was not influenced on the average temperature of the surface. The possibility of the anthropogenic heat detection from the surface from the satellite imagery was verified as well.

• Atmosphere
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• v.16 no.2
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• pp.85-96
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• 2006

The six-year (2000~2005) record of aerosol optical thickness (AOT or $\tau$) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) was analyzed over the Northeast Asia. The MODIS AOT standard products (MOD04_L2) over both ocean and land were collected to evaluate the spatial and temporal variability of the atmospheric aerosols over the study region ($32^{\circ}N{\sim}42^{\circ}N$ and $115^{\circ}E{\sim}133^{\circ}E$). The monthly averaged AOT result revealed slight changes(${\pm}0.002{\tau}/month$), which was almost unchangeable, over Korea. In contrast, the large AOT values (> 0.6) and a significant AOT increase (> 0.004 ${\tau}/month$) over East China were observed. For the analysis of spatio-temporal variability of AOT values, study area was divided by six sectors (I: North-East China, II: East China, III: Yellow Sea, IV: Korea Peninsular, V: East Sea, and VI: South Sea and Western part of Japan). The considerable result showed that particularly high AOT contribution was observed over sector I (32.5%) and II (25.5%) where some major urban and industrialized areas and agricultural fields are located and other cases were observed 13.2%, 14.6%, 7.1%, 7.0% over sector III, IV, V, and VI, respectively. In addition, yearly AOT changes based on seasons are observed differently at each sector but increasing trends reveal in summer and fall over all sectors.

• Corrosion Science and Technology
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• v.10 no.2
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• pp.52-59
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• 2011

Corrosion of metallic materials occurs by the reaction with corrosive environment such as atmosphere, marine, soil, urban, high temperature etc. In general, reduction of thickness and cracking and degradation are resulted from corrosion. Corrosion in all industrial facilities and infrastructure causes large economic losses as well as a large number of accidents. Economic loss by corrosion has been reported to be nearly 1-6% of GNP or GDP. In order to reduce corrosion damage of industrial facilities, corrosion map as well as a systematic investigation of the loss of corrosion in each industrial sector is needed. The Corrosion Science Society of Korea in collaboration with 15 universities and institutes has started to survey on the cost of corrosion and corrosion map of Korea since 2005. This work presents the results of the survey on cost of corrosion by Uhlig, Hoar, and input-output methods, and the evaluation of atmospheric corrosion rate of carbon steel, weathering steel, galvanized steel, copper, and aluminum in Korea. The total corrosion cost was estimated in terms of the percentage of the GDP of industry sectors and the total GDP of Korea. According to the result of Input/output method, corrosion cost of Korea was calculated as 2.9% to GDP (2005). Time of wetness was shown to be categories 3 to 4 in all exposure areas. A definite seasonal difference was observed in Korea. In summer and fall, time of wetness was higher than in other seasons. Because of short exposure period (12 months), significant corrosion trends depending upon materials and exposure corrosion environments were not revealed even though increased mass loss and decreased corrosion rate by exposure time.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1229-1234
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• 2021

GOCI-II, which succeeded the mission of GOCI, was successfully launched in February 2020 and is in operation. GOCI-II is expected to be highly useful in a wide range of fields, including detailed changes in the coastal seawater environment using improved spatial and spectral resolution, increased number of observation and full disk observation mode. This special issue introduces the assessment of the current GOCI-II data quality and the studies on the accuracy improvement and applications at this time of one year after launch and data disclosure. We expect that this issue can be an opportunity for GOCI-II data to be actively utilized not only in the ocean but also in various fields of land and atmosphere.

• Atmosphere
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• v.29 no.2
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• pp.183-196
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• 2019

High-quality and high-resolution meteorological information is essential to reduce damages due to disastrous weather phenomena such as flash flood, strong wind, and heat/cold waves. There are many meteorological observation stations operated by Korea Meteorological Administration (KMA) in Seoul Metropolitan Area (SMA). Nonetheless, they are still not enough to represent small-scale weather phenomena like convective storm cells due to its poor resolution, especially over urban areas with high-rise buildings and complex land use. In this study, feasibilities to use additional pre-existing networks (e.g., operated by local government and private company) are tested by investigating the effects of network density on the gridded horizontal distribution of two meteorological variables (temperature and precipitation). Two heat wave event days and two precipitation events are chosen, respectively. And the automatic weather station (AWS) networks operated by KMA, local-government, and SKTechX in Incheon area are used. It is found that as network density increases, correlation coefficients between the interpolated values with a horizontal resolution of 350 m and observed data also become large. The range of correlation coefficients with respect to the network density shows large in nighttime rather than in daytime for temperature. While, the range does not depend on the time of day, but on the precipitation type and horizontal distribution of convection cells. This study suggests that temperature and precipitation sensors should be added at points with large horizontal inhomogeneity of land use or topography to represent the horizontal features with a resolution higher than 350 m.

• Journal of the Korean Applied Science and Technology
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• v.36 no.3
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• pp.905-914
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• 2019

In this study, The PMF model was used to identify pollutant sources and their contribution to pollution sources of $PM_{2.5}$. The contribution of A city to each source was 19.8% for Secondary Sulfate, followed by Mobile 19.5%, Industry 16.0%, Biomass Buring 14.1%, Secondary Nitrate 14.1%, Oil Combustion 11.6%, Aged Sea Salt 2.6%, Soil 2.5% and so on. Sulfate and Ammonium concentrations were the highest contributing sources in the source profile, which was analyzed to be Secondary Aerosols produced by Photochemical Reactions of gaseous precursors (SOx and ammonia gas) in the atmosphere.

• Atmosphere
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• v.30 no.4
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• pp.361-376
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• 2020

This study evaluates multiple Regional Climate Models (RCMs) in simulating temperature and precipitation over the Far East Asia (FEA) and estimates the portions of the total uncertainty originating in the RCMs and the driving Global Climate Models (GCMs) using nine present-day (1981~2000) climate data obtained from combinations of three GCMs and three RCMs in the CORDEX-EA phase2. Downscaling using the RCMs generally improves the present temperature and precipitation simulated in the GCMs. The mean temperature climate in the RCM simulations is similar to that in the GCMs; however, RCMs yield notably better spatial variability than the GCMs. In particular, the RCMs generally yield positive added values to the variability of the summer temperature and the winter precipitation. Evaluating the uncertainties by the GCMs (VARGCM) and the RCMs (VARRCM) on the basis of two-way ANOVA shows that VARRCM is greater than VARGCM in contrast to previous studies which showed VARGCM is larger. In particular, in the winter temperature, the ocean has a very large VARRCM of up to 30%. Precipitation shows that VARRCM is greater than VARGCM in all seasons, but the difference is insignificant. In the following study, we will analyze how the uncertainty of the climate model in the present-day period affects future climate change prospects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.723-728
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• 2022

The vitality of the city's commercial district, which in the base of city life and provides vitality and diversity of life, has a great impact on the vitality of the entire city and the revitalization of the local economy. The revitalization of the commercial street is related to the activation of walking, and walking is closely related to the quality of life because it involves a wide range of interactions with the surrounding environment beyond simple movement. This quality of life leads to 'Livability'. In order to revitalize pedestrians on the commercial street, the liberty factor was derived and the importance of what was the most important and effective for the activation of the commercial street was analyzed. As a result, it was found that the items representing the atmosphere and purpose, which are detailed indicators of placeness, had a high priority, and it was found that the detailed indicators belonging to accessibility came out with a lower priority. In order to increase the livability of the commercial street, the priority is to increase the spatiality of the space, and if pedestrians are activated as the number of visits and stay time of visitors increases, it can be extended to the vitality of the entire area.