• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.947-960
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• 2017

Soil moisture plays an important role to affect the Earth's radiative energy balance and water cycle. In general, satellite observations are useful for estimating the soil moisture content. Passive microwave satellites have an advantage of direct sensitivity on surface soil moisture. However, their coarse spatial resolutions (10-36 km) are not suitable for regional-scale hydrological applications. Meanwhile, in-situ ground observations of point-based soil moisture content have the disadvantage of spatially discontinuous information. This paper presents an experimental soil moisture retrieval using Sentinel-1 SAR (Synthetic Aperture Radar) with 10m spatial resolution for cropland in South Korea. We developed a soil moisture retrieval algorithm based on the technique of linear regression and SVR (support vector regression) using the ground observations at five in-situ sites and Sentinel-1 SAR data from April to October in 2015-2017 period. Our results showed the polarization dependency on the different soil sensitivities at backscattered signals, but no polarization dependence on the accuracies. No particular seasonal characteristics of the soil moisture retrieval imply that soil moisture is generally more affected by hydro-meteorology and land surface characteristics than by phenological factors. At the narrower range of incidence angles, the relationship between the backscattered signal and soil moisture content was more distinct because the decreasing surface interference increased the retrieval accuracies under the condition of evenly distributed soil moisture (during the raining period or on the paddy field). We had an overall error estimate of RMSE (root mean square error) of approximately 6.5%. Our soil moisture retrieval algorithm will be improved if the effects of surface roughness, geomorphology, and soil properties would be considered in the future works.

• Journal of the Korean earth science society
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• v.31 no.4
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• pp.354-369
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• 2010

The synoptic and kinematic characteristics of a heavy rainfall that occurred in Gangneung region on 22 to 24 October 2006 were investigated using weather maps, infrared images, AWS observation data and NCEP global final analyses data. The total amount of rainfall observed in the region for the period was 316.5 mm, and the instanteneous maximum wind speed was $63.7m\;s^{-1}$. According to the analysis of weather maps, before the starting of the heavy rainfall, an extratropical low pressure system was developed in the middle region of the Korean Peninsula, and an inverted trough was formed in the northern region of the peninsula. In addition, a jet stream on the upper charts of 300 hPa was located over the Yellow Sea and the southern boundary of the peninsula. A cutoff low in the cyclonic shear side of the upper jet streak, which was linked to an anomaly of isentropic potential vorticity, was developed over the northwestern part of the peninsula. And there are analyzed potential vorticity and wind, time-height cross section of potential vorticity, vertical air motion, maximums of the divergence and convergence and vertical distribution of potential temperature in Gangneung region. The analyzed results of the synoptic conditions and kinematic processes strongly suggest that the tropopause folding made a significant role of initializing the heavy rainfall.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.1-21
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• 2015

The present study aims to characterize the synoptic climatic patterns of winter extreme low temperature events occurred in different regions of Korea based on daily temperature data observed at 61 weather stations under the supervision of the Korea Meteorological Administation and NCEP/NCAR reanalysis I data for the recent 40 years (1973~2012) period. Analyses of daily maximum and minimum temperatures below 10th percentile thresholds show that high frequencies of winter extreme low temperature events appear across the entire regions of Korea or in either the western or eastern half region divided by major mountain ridges at the 2~7 dayintervals particularly in the first half of the winter period (before mid-January). Composite analyses of surface synoptic climatic data including sea level pressure and wind vector reveal that 13 regional types of winter extreme low temperature events in Korea are closely associated with the relative location and intensity of both the Siberian high pressure and the Aleutian low pressure systems as well as major mountain ridges. Investigations of mid-troposphere (500 hPa) synoptic climatic charts demonstrate that the blocking-like upper troposphere low pressure system advecting the cold air from the Arctic toward the Korean Peninsula may provide favorable synoptic conditions for the outbreaks of winter extreme low temperature events in Korea. These results indicate that the monitoring of synoptic scale climatic systems in East Asia including the Siberian high pressure system, the Aleutian low pressure system and upper level blocking system is critical to the improvement of the predictability of winter extreme low temperature events in Korea.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.137-148
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• 2015

The National Institute of Meteorological Research (NIMR) has operated the Fourier Transform InfraRed (FTIR) spectrometer which is the Atmospheric Emitted Radiance Interferometer (AERI) in Anmyeon island, Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of retrieval quality from the AERI, particularly cloud-data filtering method. The AERI spectrum which is measured on a typical clear day is selected reference spectrum and we used region of atmospheric window. We performed test of threshold in order to select valid threshold. We retrieved methane using new method which is used reference spectrum, and the other method which is used KLAPS cloud cover information, each retrieved methane was compared with that of ground-based in-situ measurements. The quality of AERI methane retrievals of new method was significantly more improved than method of used KLAPS. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.729-741
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• 2012

Among the methods of precipitation data acquisition, a rain gauge station has a distinctive advantage of direct measurement of rainfall itself, but multiple stations should be installed in order to obtain areal precipitation data required for hydrological analysis. On the other hand, a rainfall radar may provide areal distribution of rainfall in real time though it is an indirect measurement of radar echoes on rain drops. Rainfall radars have been shown useful especially for forecasting short-term localized torrential storms that may cause catastrophic flash floods. CAPPI (Constant Altitude Plan Position Indicator), which is one of the several types of radar rainfall image data, has been provided on the Internet in real time by Korea Meteorological Administration (KMA). It is one of the most widely available rainfall data in Korea with fairly high level of confidence as it is produced with bias adjustment and quality control procedures by KMA. The objective of this study is to develop an improved way to extract quantitative rainfall data applicable to even very small watersheds from CAPPI using CIVCOM, which is a new image processing method based on a vector-based scheme proposed in this study rather than raster-based schemes proposed by other researchers. This study shows usefulness of CIVCOM through comparison of rainfall data produced by image processing methods including traditional raster-based schemes and a newly proposed vector-based one.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.315-329
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• 2015

We investigated the characteristics of meteorological conditions related to the strong downslope wind over the leeward side of the Taebaek Mountains during the period 2005~2010. The days showing the strong wind exceeding $14ms^{-1}$ in Gangwon province were selected as study cases. A total of 15 days of strong wind were observed at Sokcho, Gangneung, Donghae, and Taebaek located over the Yeongdong region. Seven cases related to tropical cyclone (3 cases) and heavy snowfall (2 cases) and heavy rainfall (2 cases) over the Yeongdong region were excluded. To investigate the characteristics of the remaining 8 cases, we used synoptic weather chart, Sokcho radiosonde, Gangneung wind profiler and numerical model. The cases showed no precipitation (or ${\leq}1mm\;day^{-1}$). From the surface and upper level weather chart, we found the pressure distribution of southern high and northern low pattern over the Korean peninsula and warm ridge over the Yeongdong region. Inversion layer (or stable layer) and warm ridge with strong wind were located in about 1~3 km (925~700 hPa) over mountains. The Regional Data Assimilation and Prediction System (RDAPS) indicated that warm core and temperature ridge with horizontal temperature gradient were $0.10{\sim}0.23^{\circ}C\;km^{-1}$ which were located on 850 hPa pressure level above mountaintop. These results were summarized as a forecasting guidance of downslope windstorm in the Yeongdong region.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.463-472
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• 2015

Solar radiation data are important data that can be used as basic research data in diverse areas. In particular, solar radiation data are essential for diverse studies that have been recently conducted in South Korea including those for new and renewable energy resource map making and crop yield forecasting. So purpose of this study is modification of Heliosat-II method to estimate solar irradiance in Korea by using COMS-MI imagery. For this purpose, in this study, errors appearing in ground albedo images were corrected through linear transformation. And method of producing background albedo map which is used in Heliosat-II method is modified to get more finely tuned one. Through the study, ground albedo correction could be successfully performed and background albedo maps could be successfully derived. Lastly, In this study, solar irradiance was estimated by using modified Heliostat-II method. And it was compared with actually measured values to verify the accuracy of the methods. Accuracy of estimated solar irradiance was 30.8% RMSE(%). And this accuracy level means that solar irradiance was estimated on 10% higher level than previous Heliosat-II method.