• Atmosphere
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• v.21 no.4
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• pp.373-389
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• 2011

This research focuses on the sensitivity of the WRF(Weather Research and Forecasting) Model according to three different land cover data(USGS(United States Geological Survey), MODIS(Moderate Resolution Imaging Spectroradiometer)30s+USGS, and KLC (Korea Land Cover)) for an event of sea breeze, occurred over the Gangwon Yeongdong region on 13 May 2009. Based on the observation, the easterly into Gangneung, due to the sea-breeze circulation, was identified between 1000 LST and 1640 LST. It did not reach beyond the Taebaek Mountain Range and thus the easterly was not observed near Daegwallyeong. On the other hand, the numerical simulations utilizing land cover data of USGS, MODIS30s+USGS, and KLC showed easterlies beyond the Taebaek Mountain Range up to Daegwallyeong. In addition, rather different penetration distances of each easterly, and different timings of beginning and ending of sea breeze were identified among the simulations. The Bias, MAE(Mean Absolute Error) and RMSE(Root Mean Square Error) of the wind from WRF simulation using MODIS30s+USGS land cover data were the least among the simulations particularly over Gangwon Yeongdong coastal area(Sokcho, Gangneung and Donghae), while those of the wind over the Gangwon Mountain area(Daegwallyeong and Jinbu) from the simulation using KLC land cover data were the least among them. The wind field over Gangwon Yeongdong coastal area from the simulation using USGS land cover data was rather poor among them.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Wind and Structures
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• v.20 no.1
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• pp.59-74
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• 2015

A coupled model system for Wind Resource Assessment (WRA) was studied. Using a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, global-scale data were downscaled to the inner nested grid scale (typically a few kilometers), and then through the coupling Computational Fluid Dynamics (CFD) mode, FLUENT. High-resolution results (50 m in the horizontal direction; 10 m in the vertical direction below 150 m) of the wind speed distribution data and ultimately refined wind farm information, were obtained. The refined WRF/FLUENT system was then applied to assess the wind resource over complex terrain in the northern Poyang Lake region. The results showed that the approach is viable for the assessment of wind energy.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.173-183
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• 2015

The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, $R^2$ is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, $R^2$ 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, $R^2$ 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, $R^2$ 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.27-37
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• 2010

A system coupled the prognostic WRF mesoscale model and CALMET diagnostic model has been employed for predicting high-resolution wind field over complex coastal area. WRF has three nested grids down to from during two days from 24 August 2007 to 26 August 2007. CALMET simulation is performed using both initial meteorological field from WRF coarsest results and surface boundary condition that is Shuttle Radar Topography Mission (SRTM) 90m topography and Environmental Geographic Information System (EGIS) 30m landuse during same periods above. Four Automatic Weather System (AWS) and a Sonic Detection And Ranging (SODAR) are used to verify modeled wind fields. Horizontal wind fields in CM_100m is not only more complex but better simulated than WRF_1km results at Backwoon and Geumho in which there are shown stagnation, blocking effects and orographically driven winds. Being increased in horizontal grid spacing, CM_100m is well matched with vertically wind profile compared SODAR. This also mentions the importance of high-resolution surface boundary conditions when horizontal grid spacing is increased to produce detailed wind fields over complex terrain features.

• Journal of KIISE
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• v.42 no.3
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• pp.281-288
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• 2015

A volcano disaster damage prediction system supports decision making for counteracting volcanic disasters by simulating meteorological condition and volcanic eruptions. In this system, a program called Fall3D generates predicted results for the diffusion of ash after a volcanic eruption on the basis of meteorological information. The relevant meteorological information is generated by a weather numerical prediction model known as Weather Research & Forecasting (WRF). In order to reduce the entire processing time without modifying these two simulation programs, pipelining can be used by partly executing Fall3D whenever the hourly (partial) results of WRF are generated. To reduce the processing time, successor programs such as Fall3D require that certain features be suspended until the part of the results that is based on prior calculation is generated by a predecessor. Even though Fall3D does not have a suspend or resume feature, pipelining effect can be produced by using the program's restart feature, which resumes simulation from the previous session. In this study, we suggest a workflow that can control the execution type.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.729-739
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• 2017

The Weather Research and Forecasting (WRF) model and Vegetation Photosynthesis and Respiration Model (VPRM) were coupled to simulate atmospheric $CO_2$ concentrations. The performance of the WRF-VPRM to simulate regional scale $CO_2$ concentration was estimated over coastal basin areas. Either Hestia 2011(HST) or Vulcan 2002(VUL) anthropogenic $CO_2$ emission data were used in two numerical experiments for the study regions. Simulated meteorological variables were validated with ground and background $CO_2$ measurement data, and the results show that the model captured temporal variations of $CO_2$ concentration on a daily basis. $CO_2$ directional analysis revealed that the dominant $CO_2$ emission sources are located S and SW. The simulated Net Ecosystem Exchange (NEE) agreed relatively well with measured $CO_2$ fluxes at each vegetation class site, showing approximately 40% at max improvement at shrub areas.

• Journal of Environmental Science International
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• v.26 no.4
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• pp.493-507
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• 2017

Since the late 20th century, the urbanization in Korea has been rapidly increasing, especially in major cities like Seoul, as a result of industrialization. One of the aspects of urbanization is coating the surfaces with impervious concrete or asphalt that water cannot penetrate. In addition, various urban, such as urban heat islands, which also have a great impact on the urban environment, occur within the cities. Therefore, the urban environment is gradually becoming hot and dry, and the need for more urban parks to compensate for these negative impacts is growing. Thus, several numerical studies have been conducted to assess these problems using coupled Numerical Weather Prediction (NWP) and Computational Fluid Dynamics (CFD). In this study, an experiment was conducted to determine the accuracy of the area of the input field using Weather Research and Forecasting (WRF) model, and applying the more accurate input field to a numerical simulation using ENVI-met, in order to investigate the effect of urban parks on the thermal comfort. The results showed that an input field with a larger area is more accurate than that with a smaller area, because the surrounding terrain and cities are considered in details in the experiment with the larger area. Subsequently, the more accurate input field was used in ENVI-met, and the results of this simulation showed that the presence of the urban park increased the thermal comfort and improved the humidity conditions.

• Atmosphere
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• v.26 no.2
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• pp.277-288
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• 2016

Polar lows are intense mesoscale cyclones that mainly occur over the sea in polar regions. Owing to their small spatial scale of a diameter less than 1000 km, simulating polar lows is a challenging task. At King Sejong station in West Antartica, polar lows are often observed. Despite the recent significant climatic changes observed over West Antarctica, adequate validation of regional simulations of extreme weather events such as polar lows are rare for this region. To address this gap, simulation results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering Antartic Peninsula at a high horizontal resolution of 3 km are validated against near-surface meteorological observations. We selected a case of high wind speed event on 7 January 2013 recorded at Automatic Meteorological Observation Station (AMOS) in King Sejong station, Antarctica. It is revealed by in situ observations, numerical weather prediction, and reanalysis fields that the synoptic and mesoscale environment of the strong wind event was due to the passage of a strong mesoscale polar low of center pressure 950 hPa. Verifying model results from 3 km grid resolution simulation against AMOS observation showed that high skill in simulating wind speed and surface pressure with a bias of $-1.1m\;s^{-1}$ and -1.2 hPa, respectively. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation of Antartic weather systems and the near-surface meteorological instruments installed in King Sejong station can provide invaluable data for polar low studies over West Antartica.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.2
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• pp.119-130
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• 2012

Heat island phenomena in Chuncheon (Korea) were investigated using air temperature measured by automatic weather stations and temperature dataloggers located at rural and urban sites. Numerical simulation of the phenomena was performed using Weather Research and Forecasting Urban Canopy Model (WRF-UCM) and results were compared with the observation. The model was initialized with NCEP/FNL data. The horizontal resolution of the fine domain is 0.33 km. The results of observational analyses show that the intensity of heat island was significantly higher during the nighttime than during the daytime. The highest measured temperature difference between rural and urban site is $3.49^{\circ}C$ and average temperature difference varies between 1.4 and $1.9^{\circ}C$. Good agreement was found between the simulated and observed temperatures. However, significantly overestimated wind speed was found at the urban sites. The linear regression analysis between observed and simulated temperature shows high correlation coefficient 0.96 for urban and 0.94 for rural sites while for wind speed, a very low correlation coefficient was found, 0.30 and 0.55 respectively.