• Atmosphere
• /
• v.31 no.2
• /
• pp.185-198
• /
• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.188-202
• /
• 2011

Due to emissions of greenhouse gases caused by increased use of fossil fuels, the climate change has been detected and this phenomenon would affect even larger changes in temperature and precipitation of South Korea. Especially, the increase of temperature by climate change can affect the amount and pattern of snowfall. Accordingly, we tried to predict future snowfall and the snowfall pattern changes by using the downscaled GCM (general circulation model) scenarios. Causes of snow varies greatly, but the information provided by GCM are maximum / minimum temperature, rainfall, solar radiation. In this study, the possibility of snow was focused on correlation between minimum temperatures and future precipitation. First, we collected the newest fresh snow depth offered by KMA (Korea meteorological administration), then we estimate the temperature of snow falling conditions. These estimated temperature conditions were distributed spatially and regionally by IDW (Inverse Distance Weight) interpolation. Finally, the distributed temperature conditions (or boundaries) were applied to GCM, and the future snowfall was predicted. The results showed a wide range of variation for each scenario. Our models predict that snowfall will decrease in the study region. This may be caused by global warming. Temperature rise caused by global warming highlights the effectiveness of these mechanisms that concerned with the temporal and spatial changes in snow, and would affect the spring water resources.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.13 no.1
• /
• pp.28-34
• /
• 2011

This study was carried out to estimate monthly mean of daily maximum and minimum temperature across North Korea at a 30 m grid spacing for a climatological normal year (1971-2000) and the 4 decadal averages (1971-1980, 1981-1990, 1991-2000, and 2001-2010). A geospatial climate interpolation method, which has been successfully used to produce the so-called 'High-Definition Digital Climate Maps' (HD-DCM), was used in conjunction with the 27 North Korean and 17 South Korean synoptic data. Correction modules including local effects of cold air drainage, thermal belt, ocean, solar irradiance and urban heat island were applied to adjust the synoptic temperature data in addition to the lapse rate correction. According to the final temperature estimates for a normal year, North Korean winter is expected colder than South Korean winter by $7^{\circ}C$ in average, while the spatial mean summer temperature is lower by $3^{\circ}C$ than that for South Korea. Warming trend in North Korea for the recent 40 years (1971-2010) was most remarkable in spring and fall, showing a 7.4% increase in the land area with 15 or higher daily maximum temperature for April.

• Journal of the Korean association of regional geographers
• /
• v.17 no.4
• /
• pp.432-442
• /
• 2011

Climatic variables such as temperature and precipitation tend to vary both in space and in time simultaneously. Thus, it is necessary to include space-time autocorrelation into conventional spatial interpolation methods for reliable time-series mapping. This paper introduces and applies space-time variogram modeling and space-time kriging to generate time-series temperature maps using hourly Automatic Weather System(AWS) temperature observation data for a one-month period. First, temperature observation data are decomposed into deterministic trend and stochastic residual components. For trend component modeling, elevation data which have reasonable correlation with temperature are used as secondary information to generate trend component with topographic effects. Then, space-time variograms of residual components are estimated and modelled by using a product-sum space-time variogram model to account for not only autocorrelation both in space and in time, but also their interactions. From a case study, space-time kriging outperforms both conventional space only ordinary kriging and regression-kriging, which indicates the importance of using space-time autocorrelation information as well as elevation data. It is expected that space-time kriging would be a useful tool when a space-poor but time-rich dataset is analyzed.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.1
• /
• pp.55-63
• /
• 2016

Temperature lapse rate within the planetary boundary layer shows a diurnal cycle with a substantial variation. The widely-used lapse rate value for the standard atmosphere may result in unaffordable errors if used in interpolating hourly temperature in complex terrain. We propose a simple method for estimating hourly lapse rate and evaluate whether this scheme is better than the conventional method using the standard lapse rate. A standard curve for lapse rate based on the diurnal course of temperature was drawn using upper air temperature for 1000hPa and 925hPa standard pressure levels. It was modulated by the hourly sky condition (amount of clouds). In order to test the reliability of this method, hourly lapse rates for the 500-600m layer over Daegwallyeong site were estimated by this method and compared with the measured values by an ultrasonic temperature profiler. Results showed the mean error $-0.0001^{\circ}C/m$ and the root mean square error $0.0024^{\circ}C/m$ for this vertical profile experiment. An additional experiment was carried out to test if this method is applicable for the mountain slope lapse rate. Hourly lapse rates for the 313-401m slope range in a complex watershed ('Hadong Watermark 2') were estimated by this method and compared with the observations. We found this method useful in describing diurnal cycle and variation of the mountain slope lapse rate over a complex terrain despite larger error compared with the vertical profile experiment.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.12
• /
• pp.1690-1696
• /
• 2014

Network RTK generates spatial corrections by using differenced measurements from reference stations in the network, and the corrections are then provided to a rover. The rover, generally, uses linear interpolation, which assumes that the corrections at each reference station are spatially correlated, to obtain a precise correction of its location. However, an irregularity of the tropospheric delay is a real-world factor that violates this assumption. Tropospheric delay is a result of weather conditions, such as humidity, temperature and pressure, and it can cause spatial decorrelation when there are changes in the local climate. In this paper, we have defined the non-linear characteristics of the tropospheric delay between reference stations or user within a region as the "irregularity of tropospheric delay". Such an irregularity can negatively impact the network RTK performance. Therefore, we analyze the influence of the irregularity of tropospheric delay in network RTK based on meteorological data.

• Journal of Power Electronics
• /
• v.3 no.1
• /
• pp.62-67
• /
• 2003

Recently, photovoltaic system has been studied widely as a renewable energy system, because it does not produce environmental pollution and it has infinity energy source from the sun. A study on photovoltaic system has a lot of problems like as reappearance and repetition of some situation in the laboratory experiment for development of MPPT algorithm and islanding detection algorithm. because output characteristics of solar cell are varied by irradiation and surface temperature of solar cell. Therefore, the assistant equipment which emulates the solar cell characteristics which can be controlled arbitrarily by researcher is require to the researchers for reliable experimental data. In this paper, the virtual implement of solar cell (VISC) system is proposed to solve these problems and to achieve reliable experimental result on photovoltaic system. VISC system emulates the solar cell output characteristics, and this system can substitute solar cell in laboratory experiment system. To realize the VISC, mathematical model of solar cell is studied for driving converter and the DC/DC converters are compared in viewpoint of tracking error using computer simulation. Output dynamic characteristic of PV array is varied by irradiation and PWM converter performance is studied using PSIM simulator.

• Journal of the Korean Solar Energy Society
• /
• v.38 no.1
• /
• pp.1-11
• /
• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• Journal of Mechanical Science and Technology
• /
• v.20 no.10
• /
• pp.1741-1752
• /
• 2006

A combined Streamline Upwind Petrov-Galerkin method (SUPG) and segregated finite element algorithm for solving conjugate heat transfer problems where heat conduction in a solid is coupled with heat convection in viscous fluid flow is presented. The Streamline Upwind Petrov-Galerkin method is used for the analysis of viscous thermal flow in the fluid region, while the analysis of heat conduction in solid region is performed by the Galerkin method. The method uses the three-node triangular element with equal-order interpolation functions for all the variables of the velocity components, the pressure and the temperature. The main advantage of the presented method is to consistently couple heat transfer along the fluid-solid interface. Four test cases, which are the conjugate Couette flow problem in parallel plate channel, the counter-flow in heat exchanger, the conjugate natural convection in a square cavity with a conducting wall, and the conjugate natural convection and conduction from heated cylinder in square cavity, are selected to evaluate efficiency of the presented method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2005.05a
• /
• pp.43-46
• /
• 2005

Micro molding technology is a promising mass production technology for polymer based microstructures. Mass production technologies such as the micro injection/compression molding, hot embossing, and micro reaction molding are already in use. In the present study, we have developed a numerical analysis system to simulate three-dimensional non-isothermal cavity filling for hot embossing, with a special emphasis on the free surface capturing. Precise free surface capturing has been successfully accomplished with the level set method, which is solved by means of the Runge-Kutta discontinuous Galerkin (RKDG) method. The RKDG method turns out to be excellent from the viewpoint of both numerical stability and accuracy of volume conservation. The Stokes equations are solved by the stabilized finite element method using the equal order tri-linear interpolation function. To prevent possible numerical oscillation in temperature Held we employ the streamline upwind Petrov-Galerkin (SUPG) method. With the developed code we investigated the detailed change of free surface shape in time during the mold filling. In the filling simulation of a simple rectangular cavity with repeating protruded parts, we find out that filling patterns are significantly influenced by the geometric characteristics such as the thickness of base plate and the aspect ratio and pitch of repeating microstructures. The numerical analysis system enables us to understand the basic flow and material deformation taking place during the cavity filling stage in microstructure fabrications.