• Atmosphere
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• v.21 no.4
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• pp.439-446
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• 2011

NCEP reanalysis data were analyzed in order to provide distribution of global wind resource and wind speed in the surface layer for the years 2000-2009. Wind speed at 10 m above ground level (AGL) was converted to wind speed at 80 m above the ground level using the power law. The global average 80 m wind speed shows a maximum value of $13ms^{-1}$ at the storm track region. High wind speed over the land exists in Tibet, Mongolia, Central North America, South Africa, Australia, and Argentina. Wind speed over the ocean increased with a large value in the South China Sea, Southeast Asia, East Sea of the Korea. Sea surface wind in Western Europe and Scandinavia are suitable for wind farm with a value of $7-8ms^{-1}$. Areas with great potential for wind farm are also found in Eastern and Western coastal region of North America. Sea surface wind in Southern Hemisphere shows larger values in the high latitude of South America, South Africa and Australia. The distribution of low-resolution reanalysis data represents general potential areas for wind power and can be used to provide information for high-resolution wind resource mapping.

• Atmosphere
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• v.29 no.4
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• pp.355-365
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• 2019

Based on in-situ monitoring data produced by National Institute of Meteorological Sciences, we evaluated the performance of Joint UK Land Environment Simulator (JULES) on the surface energy balance for rice-paddy and cropland in Korea with the operational ancillary data used for Unified Model (UM) Local Data Assimilation and Prediction System (LDAPS) (CTL) and the high-resolution ancillary data from external sources (EXP). For these experiments, we employed the one-year (March 2015~February 2016) observations of eddy-covariance fluxes and soil moisture contents from a double-cropping rice-paddy in BoSeong and a cropland in AnDong. On the rice-paddy site the model performed better in the CTL experiment except for the sensible heat flux, and the latent heat flux was underestimated in both of experiments which can be inferred that the model represents flood-irrigated surface poorly. On the cropland site the model performance of the EXP experiment was worse than that of CTL experiment related to unrealistic surface type fractions. The pattern of the modeled soil moisture was similar to the observation but more variable in time. Our results shed a light on that 1) the improvement of land scheme for the flood-irrigated rice-paddy and 2) the construction of appropriate high-resolution ancillary data should be considered in the future research.

• Atmosphere
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• v.17 no.3
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• pp.255-268
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• 2007

This study generated and evaluated the high resolution (5 km) gridded data of monthly mean, maximum and minimum temperature from 2002 to 2005 over South Korea using a modified PRISM(Parameter-elevation Regressions on Independent Slopes Model: K-PRISM) developed by Daly et al. (2003). The performance of K-PRISM was evaluated by qualitative and quantitative ways using the observations and gridded data derived by inverse distance weighting (IDW) and hypsometric methods (HYPS). For the generation of high resolution gridded data, geographic informations over South Korea, such as the digital elevation, topographic facet and coastal proximity, are derived from the 1 km digital elevation data. The spatial patterns of temperature derived by K-PRISM were more closely linked to topography and coastal proximity than those by IDW. The K-PRISM performed much better than IDW for all months and temperatures, but it was equal to or slightly better than the HYPS. And the performances of K-PRISM were better in the minimum and mean temperature (winter) than the in maximum temperature (summer).

• Journal of Environmental Science International
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• v.23 no.3
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• pp.503-510
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• 2014

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.63-70
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• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• Atmosphere
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• v.31 no.3
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• pp.251-265
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• 2021

This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.1
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• pp.1-14
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• 2015

This study investigates the impact of enhanced regional meteorological fields on improvement of wind energy forecasting accuracy in the southwestern coast of the Korean Peninsula. To clarify the effect of detailed surface boundary data and application of analysis nudging technique on simulated meteorological fields, several WRF simulations were carried out. Case_LT, which is a simulation with high resolution terrain height and land use data, shows the most remarkable accuracy improvement along the shoreline mainly due to modified surface characteristics such as albedo, roughness length and thermal inertia. Case_RS with high resolution SST data shows accurate SST distributions compared to observation data, and they led to change in land and sea breeze circulation. Case_GN, grid nudging applied simulation, also shows changed temperature and wind fields. Especially, the application of grid nudging dominantly influences on the change of horizontal wind components in comparison with vertical wind component.

• Atmosphere
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• v.32 no.2
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• pp.103-118
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• 2022

This study evaluates the simulated meteorological fields with a particular focus on the low-level wind, which plays an important role in air pollutants dispersion, under the varying synoptic environment. Additionally, the effects of subgrid-scale orography parameterization and improved topography/land-use data on the simulated low-level wind is investigated. The WRF model version 4.1.3 is utilized to simulate two cases that were affected by different synoptic environments. One case from 2 to 6 April 2012 presents the substantial low-level wind speed over the Korean peninsula where the synoptic environment is characterized by the baroclinic instability. The other case from 14 to 18 April 2012 presents the relatively weak low-level wind speed and distinct diurnal cycle of low-level meteorological fields. The control simulations of both cases represent the systematic overestimation of the low-level wind speed. The positive bias for the case under the baroclinic instability is considerably alleviated by applying the subgrid-scale orography parameterization. However, the improvement of wind speed for the other case showing relatively weak low-level wind speed is not significant. Applying the high-resolution topography and land-use data also improves the simulated wind speed by reducing the positive bias. Our analysis shows that the increased roughness length in the high-resolution topography and land-use data is the key contributor that reduces the simulated wind speed. The simulated wind direction is also improved with the high-resolution data for both cases. Overall, our study indicates that wind forecasts can be improved through the application of the subgrid-scale orography parameterization and high-resolution topography/land-use data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.135-139
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• 1999

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.43-48
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• 2001

Many applications in the areas of agricultural, hydrological and environmental resource management require data over very large areas and with a high imaging frequency - monitoring crop growth, water stress, seasonal wetland flooding and natural vegetation development. This precludes the use of fine resolution data (Landsat, Spot) on the grounds of cost, accessibility and low imaging frequency. Meteorological satellites have the potential to fill this need, given their very wide spatial coverage, and high repeat imaging. The Remote Sensing Unit (RSU) at the Zambia Meteorological Department routinely receives, processes and archives imagery from both Meteosat and NOAA AVHRR satellites. Here I wish to present some examples of applications of these data sets that arise from the RSU work - relationships between rainfall and vegetation development as assessed by satellite, derived information and seasonal patterns of flooding in the Barotse floodplain and the Kafue flats. I also wish to outline ways in which a more widespread use of this data by the Zambian institutions canbe achieved.