• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.23-27
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• 2008

The new conjunctive surface-subsurface flow model at a large scale was developed by using a 1-D Diffusion Wave (DW) model for surface flow interacting with the 3-D Volume Averaged Soil-moisture Transport (VAST) model for subsurface flow for the comprehensive terrestrial water and energy predictions in Land Surface Models (LSMs). A selection of numerical implementation schemes is employed for each flow component. The 3-D VAST model is implemented using a time splitting scheme applying an explicit method for lateral flow after a fully implicit method for vertical flow. The 1-D DW model is then solved by MacCormack finite difference scheme. This new conjunctive flow model is substituted for the existing 1-D hydrologic scheme in Common Land Model (CLM), one of the state-of-the-art LSMs. The new conjunctive flow model coupled to CLM is tested for a study domain around the Ohio Valley. The simulation results show that the interaction between surface flow and subsurface flow associated with the flow routing scheme matches the runoff prediction with the observations more closely in the new coupled CLM simulations. This improved terrestrial hydrologic module will be coupled to the Climate extension of the next-generation Weather Research and Forecasting (CWRF) model for advanced regional, continental, and global hydroclimatological studies and the prevention of disasters caused by climate changes.

• Atmosphere
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• v.15 no.1
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• pp.1-16
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• 2005

Land-surface and soil processes significantly affect mesoscale local weather systems as well as global/regional climate. In this study, characteristics of land-surface models (LSMs) and soil models (SMs) that are frequently coupled into mesoscale meteorological models are investigated. In addition, detailed analyses on three LSMs, employed by the PSU/NCAR MM5, are provided. Some impacts of LSMs on heavy rainfall prediction are also discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.159-172
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• 2006

In this study, the series of Landsat TM/ETM+ images was acquired to extract land surface temperature for wide-area and executed geometric correction and radiometric correction. And the land surface temperature was extracted using NASA Model, and achieved the first correction by performing land coverage category for study area and applied characteristic emission rate. Land surface temperature which was acquired by the first correction was analyzed in correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two data using establishing correction formula. As a result, land surface temperature acquired by 1st and 2st correction could be corrected in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, I could acquire land surface temperature about study area by higher accuracy by applying to other Landsat images for re-verification of study results.

• Atmosphere
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• v.22 no.3
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• pp.357-365
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• 2012

High spatio-temporal resolution hydrologic components can give important information to monitor natural disaster. The objective of this study is to create high spatial-temporal resolution gridded hydrologic components using TOPLATS distributed land surface model and evaluate their accuracy. For this, Andong dam basin is selected as study area and TOPLATS model is constructed to create hourly simulated values in every $1{\times}1km^2$ cell size. The observed inflow at Andong dam and soil moisture at Andong AWS site are collected to directly evaluate the simulated one. RMSEs of monthly simulated flow for calibration (2003~2006) and verification (2007~2009) periods show 36.87 mm and 32.41 mm, respectively. The hourly simulated soil moisture in the cell located Andong observation site for 2009 is well fitted with observed one at -50 cm. From this results, the cell based hydrologic components using TOPLATS distributed land surface model show to reasonably represent the real hydrologic condition in the field. Therefore the model driven hydrologic information can be used to analyze local water balance and monitor natural disaster caused by the severe weather.

• Atmosphere
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• v.20 no.3
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• pp.319-332
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• 2010

Sensitivity experiments of WRF model using different planetary boundary layer (PBL) and land surface model (LSM) parameterizations are evaluated for prediction of wind fields within the surface layer. The experiments were performed with three PBL schemes (YSU, Pleim, MYJ) in combination with three land surface models (Noah, RUC, Pleim). The WRF model was conducted on a nested grid from 27-km to 1-km horizontal resolution. The simulations validated wind speed and direction at 10 m and 80 m above ground level at a 1-km spatial resolution over the South Korea. Statistical verification results indicate that Pleim and YSU PBL schemes are in good agreement with observations at 10 m above ground level, while the MYJ scheme produced predictions similar to the observed wind speed at 80 m above ground level. LSM comparisons indicate that the RUC model performs best in predicting 10-m and 80-m wind speed. It is found that MYJ (PBL) - RUC (LSM) simulations yielded the best results for wind field in the surface layer. The choice of PBL and LSM parameterization will contribute to more accurate wind predictions for air quality studies and wind power using WRF.

• Journal of Urban Science
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• v.9 no.1
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• pp.17-31
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• 2020

This study aims to analyze the relations among greenbelt, urban land surface temperature empirically in order to assess the environmental effects of the greenbelt in the Seoul metropolitan area, objectively. For this purpose, this study conducts an empirical analysis of impacts of greenbelt on urban land surface temperature using a multiple-regression model. The main data employed in the analysis include real-time air pollution data, Landsat 8-OLI Landsat imagery data, KLIS data and Jip-gye-gu data. The major findings are summarized as follows. NDVI has a negative (-) correlation with the land surface temperature, and the urban temperature is high in areas with poor vegetation. The land surface temperature is low in residential or commercial areas, while the temperature is high in industrial areas. The temperature is low in green fields, open spaces, and river areas. it is found that the urban land surface temperature is low in the greenbelt zone. In the greenbelt zone, there is an effect that reduces the land surface temperature by 1% on average, as compared to that at the center of the Seoul metropolitan area. Especially, the center of the Seoul metropolitan area, in a range from 0.6% to 1.9% of the average temperature, the temperature gets lower up to approximately 3km from the greenbelt boundary.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.58-61
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• 2003

A land surface parameterization has been used to simulate influences of the terrestrial surface on the atmosphere. A simple biosphere model (SiB2), one of land surface parameterization, calculates exchange of radiation, sensible heat, latent heat, and momentum between the surface and the atmosphere (Sellers, et al., 1996).(omitted)

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.1-15
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• 2017

Eutrophication of surface waters is of concern worldwide, because it can result in many undesirable water-quality and ecological problems, such as hypoxic 'dead' zones and harmful algal blooms, both associated with considerable economic costs. In this study, we used LSM (Land Surface Model) to simulate nitrogen in five major rivers in the Southern Korean Peninsula. The main objective of this research was to enhance nitrogen data for input of LM3V model in South Korea. Input data for nitrogen fluxes were categorized into three sections including agriculture fertilizer, livestock manure, atmosphere deposition, biological fixation, and sewage pollutants were used as the nitrogen input. For using LM3V model, the nitrogen input data were regenerated by considering states of agriculture and industry in South Korea at a $1/8^{\circ}$ resolution. Then, we simulated stream/river flows and N loads throughout the entire drainage networks in South Korea at a $1/8^{\circ}$ resolution. By using the same parameters for the entire country ($100,210km^2$), composed of 5 river basins with varying climate and land use, the model simulates spatial (11 sites) and temporal (1999~2010) patterns of flows and nitrate-N loads are resonable by comparing observed flow and nitrate-N loads. The r (Pearson's linear correlation) for water temperature, flow and nitrate-N at river were 080~0.93, 0.62~0.92 and 0.5~0.9 respectively. Based on enhanced N input data and model results, we find that LM3V model as land surface model can be applied in South Korea with interaction of atmosphere and land conditions.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.795-806
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• 1998

Soil moisture is affected by regional climate, soil characteristics and land surface condition, etc,. Especially, the changes in land surface condition is more than other factors, which is mainly due to rapid urbanization and industrialization. This study is to evaluate how the change of land surface condition impacts on soil moisture field evolution using a simple model of soil moisture dynamics. For the quantification of soil moisture field, the first half of the paper is spared for the statistical characterization based on the first- and second-order statistics of Washita '92 and Monsoon '90 data. The second half is for evaluating the impact of land cover changes through simulation study using a model for soil moisture dynamics. The model parameters, the loss rate and the diffusion coefficient, have been estimated using the observed data statistics, where the changes of surface conditions are considered into the model by applying various parameter sets with different second-order statistics. This study is concentrated on evaluating the impact due to the changes of land surface condition variability. It is because we could easily quantify the impact of the changes of its areal mean based on the linear reservoir concept. As a result of the study, we found; (1)as the variability of land surface condition, increases, the soil moisture field dries up more easily, (2)as the variabilit y of the soil moisture field is the highest at the beginning of rainfall and decreases as time goes on to show the variability of land surface condition, (3)the diffusion effect due to surface runoff or water flow through the top soil layer is limited to a period of surface runoff and its overall impact is small compared to that of the loss rate field.

• Asian Journal of Atmospheric Environment
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• v.10 no.1
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• pp.42-50
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• 2016

This study presents a performance evaluation of four different land surface models (LSM) available in Weather Forecast Research (WRF). The research site was located in Haean Basin in South Korea. The basin is very unique by its geomorphology and topography. For a better representation of the complex terrain in the mesoscale model were used a high resolution topography data with a spatial resolution of 30 meters. Additionally, land-use layer was corrected by ground mapping data-sets. The observation equipments used in the study were an ultrasonic anemometer with a gas analyzer, an automatic weather station and a tethered balloon sonde. The model simulation covers a four-day period during autumn. The result shows significant impact of LSM on meteorological simulation. The best agreement between observation and simulation was found in the case of WRF with Noah LSM (WRF-Noah). The WRF with Rapid Update Cycle LSM (WRF-RUC) has a very good agreement with temperature profiles due to successfully predicted fog which appeared during measurements and affected the radiation budget at the basin floor. The WRF with Pleim and Xiu LSM (WRF-PX) and WRF with Thermal Diffusion LSM (WRF-TD) performed insufficiently for simulation of heat fluxes. Both overestimated the sensible and underestimated the latent heat fluxes during the daytime.