• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.149-163
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• 2004

Evapotranspiration (ET) is a critical component of the hydrologic cycle which influences economic activities as well as the natural ecosystem. While there have been numerous studies on ET estimation for homogeneous areas using point measurements of meteorological variables, monitoring of spatial ET has not been possible at landscape - or watershed - scales. We propose a site-specific application of the land surface model, which is enabled by spatially interpolated input data at the desired resolution. Gyunggi Province of South Korea was divided into a regular grid of 10 million cells with 30m spacing and hourly temperature, humidity, wind, precipitation and solar irradiance were estimated for each grid cell by spatial interpolation of synoptic weather data. Topoclimatology models were used to accommodate effects of topography in a spatial interpolation procedure, including cold air drainage on nocturnal temperature and solar irradiance on daytime temperature. Satellite remote sensing data were used to classify the vegetation type of each grid cell, and corresponding spatial attributes including soil texture, canopy structure, and phenological features were identified. All data were fed into a standalone version of SiB2(Simple Biosphere Model 2) to simulate latent heat flux at each grid cell. A computer program was written for data management in the cell - based SiB2 operation such as extracting input data for SiB2 from grid matrices and recombining the output data back to the grid format. ET estimates at selected grid cells were validated against the actual measurement of latent heat fluxes by eddy covariance measurement. We applied this system to obtain the spatial ET of the study area on a continuous basis for the 2001-2003 period. The results showed a strong feasibility of using spatial - data driven land surface models for operational monitoring of regional ET.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.321-334
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• 2006

The need for economical and accurate presentations of equivalent radar reflectivity( $Z_e$) data in an orthogonal coordinate system has existed for some time. So, in this study, a fast and efficient procedure has been developed which allows the systematic interpolation of digital reflectivity data from radar space into Cartesian space. At first, QC(Quality Control) of radar data has been executed for extracting uncontaminated Constant Altitude Plan Position Indicator(CAPPI) data. The algorithm is designed so that only one ordered pass through the original Plan Position Indicator(PPI) scan data is necessary to complete the interpolation process. The model can calculate various resolution and altitude reflectivity data for many kinds of hydrological usage.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.30-34
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• 2012

National Meteorological Satellite Center(NMSC) of Korea Meteorological Administration(KMA) has launched to implement the application development to get prepared for the space weather operation since 2010. As a action of KMA's space weather work, NMSC constructed Global Navigation Satellite System(GNSS) application system for meteorology and space weather. We will introduce NMSC's space weather application system which derives regional TEC(Total Electron Content) in near real time using nation-wide GNSS network data. First, We constructed system for collecting GNSS data, which is currently collecting about 80 stations operated by agencies like NGII(National Geographic Information Institute), Central Office of DGPS(Differential GPS), and KASI(Korea Astronomy and Space Science) including KMA's own data of 2 stations. In order to retreive regional TEC over Korean peninsular, we build up the automatic processes running every 1-hour. In these processes, firstly, GNSS data of every stations with 24 hours time window are processed to derive DCBs(Differential Code Biases) of each GNSS station and TEC values on every ionosphere piercing point(IPP). Then we made gridded regional TEC map with resolution of 0.25 degree from 31N, 121E to 41N, 135E by combination of all station results within 30 minutes window with assumption that TEC of a given point during a given 30 minutes window would have a constant value. The grid points without TEC value are interpolated using Barnes objective analysis. We presentour regional TEC maps, which can describe better on the status of ionosphere over Korean peninsular compared to IGS TEC maps.

• Journal of Korea Water Resources Association
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• v.51 no.7
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• pp.575-584
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• 2018

An increase in heavy rainfall and floods have been observed over South Korea due to recent abnormal weather. In this perspective, the high-resolution weather forecasts have been widely used to facilitate flood management. However, these models are known to be biased due to initial conditions and topographical conditions in the process of model building. Theretofore, a bias correction scheme is largely applied for the practical use of the prediction to flood management. This study introduces a new mean field bias correction (MFBC) approach for the high-resolution numerical rainfall products, which is based on a Bayesian Kriging model to combine an interpolation technique and MFBC approach for spatial representation of the error. The results showed that the proposed method can reliably estimate the bias correction factor over ungauged area with an improvement in the reduction of errors. Moreover, it can be seen that the bias corrected rainfall forecasts could be used up to 72 hours ahead with a relatively high accuracy.

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

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.209-215
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• 2007

To improve the accuracy of frost warning system for pear orchard in a complex terrain in Naju area, the daily minimum temperature forecasted by Korea Meteorological Administration (KMA) was interpolated using a regional climate model based on topoclimatic estimation and optimum scale interpolation from 2004 to 2005. Based on the validation experiments done for three pear orchards in the spring of 2004, the results showed a good agreement between the observed and predicted values, resulting in improved predictability compared to the forecast from Korea Meteorological Administration. The differences between the observed and the predicted temperatures were $-2.1{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the valley, $-1.6{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the riverside and $-1.1{\sim}3.5^{\circ}C$ (on average $0.6^{\circ}C$) in the hills. Notably, the errors have been reduced significantly for the valley and riverside areas that are more affected by the cold air drainage and more susceptible to frost damage than hills.

• Ocean and Polar Research
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• v.23 no.2
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• pp.181-188
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• 2001

We describe here the Korea ocean prediction system that closely resembles operational numerical weather prediction systems. This prediction system will be served for real-time forecasts. The core of the system is a three-dimensional primitive equation numerical circulation model, based on ${\sigma}$-coordinate. Remotely sensed multi-channel sea surface temperature (MCSST) is imposed at the surface. Residual subsurface temperature is assimilated through the relationship between vertical temperature structure function and residual of sea surface height (RSSH) using an optimal interpolation scheme. A unified grid system, named as [K-E-Y], that covers the entire seas around Korea is used. We present and compare hindcasting results during 1990-1999 from a model forced by MCSST without incorporating RSSH data assimilation and the one with both MCSST and RSSH assimilated. The data assimilation is applied only in the East Sea, hence the comparison focuses principally on the mesoscale features prevalent in the East Sea. It is shown that the model with the data assimilation exhibits considerable skill in simulating both the permanent and transient mesoscale features in the East Sea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.273-282
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• 1999

For appling the GSIS on a air environment division, first of all, spatial-distribution of environmental factor which has distinction of continuous surface such as air-pollutant and a factor of weather must be able to be drawn. So we should estimate a distribution of whole area with point observation value which is observed on several restricted point. On this study, we investigate and study the application of GSIS technique which can be visible emission characteristic by regions, items, and time using data such as traffic quantity data, digital map for GIS-T and emission factor of each pollutant of vehicles about whole area of Seoul surveyed by traffic sensus of Seoul to air environment division.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.