• Proceedings of the KSRS Conference
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• v.1
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• pp.394-397
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• 2006

Gridded products of surface wind/wind-stress over the world ocean have been constructed by using satellite scatterometer as the Japanese Ocean Flux data sets with Use of Remote-sensing Observation (J-OFURO) data. Our previous validation study in the tropical Pacific using TAO/Triton and NDBC buoys revealed high reliability of our products. In this study, the Kuroshio Extension Observatory (KEO) buoy data are used for validation of other gridded wind-stress products including the NCEP-1 and 2 in the western North Pacific region where there have been few in-situ data. Results reveal that our J-OFURO product has almost zero mean difference and smallest root-mean-square (RMS) difference, while the NCEP-1 and 2 ones significantly positive biases and relatively high RMS difference. Intercomparison between the J-OFURO and NCEP products in a wide region of the North Pacific covered by the westerly winds exhibits that the NCEPs have larger magnitudes in the wind stress than the J-OFURO's, suggesting overestimation of the NCEPs.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.31-44
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• 2019

The main objective of this research is to develop a hydroclimate drought index (HCDI) using the gridded climate data inputs in a Variable Infiltration Capacity (VIC) modeling platform. Typical drought indices, including, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Self-calibrated Palmer Drought Severity Index (SC-PDSI) in South Korea are also used and compared. Inverse Distance Weighting (IDW) method is applied to create the gridded climate data from 56 ground weather stations using topographic information between weather stations and the respective grid cell ($12km{\times}12km$). R statistical software packages are used to visualize HCDI in Google Earth. Skill score (SS) are computed to evaluate the drought predictability based on water information derived from the observed reservoir storage and the ground weather stations. The study indicates that the proposed HCDI with the gridded climate data input is promising in the sense that it can help us to predict potential drought extents and to mitigate its impacts in a changing climate. The longer term drought prediction (e.g., 9 and 12 month) capability, in particular, shows higher SS so that it can be used for climate-driven future droughts.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.307-307
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• 2019

General Ciculation Model (GCM) 모형에 대한 평가를 본 연구에서 수행한다. 모형의 적용을 위해서는 국지적 일 강우량 및 기온자료를 이용한다. 31개의 GCM 모의를 통해 도출되는 결과가 성능 평가에서 활용되었다. 일 최대, 최소 기온와 강우량이 파키스탄 지역을 대상으로 모의되었다. 모의를 위해서는 Gridded 데이터가 적용되었으며 각각 Asian Precipitation-Highly-Resolved Observational Data Integration Toward Evaluation, Berkeley Earth Surface Temperature, Princeton Global Meteorological Forcing, Climate Prediction Centre에 해당된다. GCM의 순위를 결정하기 위해서는 Symmetrical Uncertainty 방법이 이용된다. 결과를 통해서 Gridded 데이터의 종류에 따라 가장 높은 효율을 나타내는 GCM의 공간 분포가 달라진다는 점을 확인하였다. 이러한 특성은 기온과 강우량 자료 모두에서 확인된다. 기온의 경우에는 Commonwealth Scientific and Industrial Research Organization, Australia-MK3-6-0과 Max Planck Institute-ESM-LR이 우수한 결과를 모의하는 것으로 나타났다. 반면 강우량의 경우에는 EC-Earth와 MIROC가 우수한 것으로 나타났다. 파키스탄 지역에서의 기온 및 강우량 자료의 합리적 반영을 위해서는 ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES, MIRCO5와 같은 6개 GCM을 이용하였을 때 다양한 기상 인자를 고려한 모의가 가능한 것으로 평가된다.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.800-809
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• 2014

The gridded environmental data is usually provided by the numerical simulation coupled with a data assimilation technique and various inter- or extrapolation algorithms, both of which are based on the observation spanning from simple equipments to satellites. But it is difficult to represent the natural phenomenon such as sea mount, internal-wave, warm eddy in modeling or observation because of increase in the complexity of model. This paper introduces the algorithm artificially representing the natural phenomenon and the techniques applying it to the gridded volume data and smoothing for natural effects. Moreover, the inserted results are analyzed by use of graphical tool. The results can be used for the battle simulation or acoustic model.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.143-146
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• 2016

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.309-312
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• 2008

The advent of high resolution products of surface wind and temperature derived by satellite data has permitted us to investigate ocean and atmosphere interaction studies in detail. Especially the Kuroshio extension region of the western North Pacific is considered to be a key area for such studies. We have constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (Qscat/SeaWinds), available as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO). Using new data based on improved algorithm which have been recently delivered, we are reconstructing gridded product with higher spatial resolution. Intercomparison of this product with the previous one reveals that there are some discrepancies between them in short-period and high wind-speed ranges especially in the westerly wind region. The products are validated by not only comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON in the tropical Pacific and the Kuroshio Extension Observation (KEO) buoys, but also intercomparison with numerical weather prediction model (NWPM) products (the NRA-1 and 2). Our products have much smaller mean difference in the study areas than the NWPM ones, meaning higher reliability compared with the NWPM products. Using the high resolution products together with sea surface temperature (SST) data, we examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region. It is suggested that the spatial relation between the wind speed and SST depends upon, more or less, the surrounding oceanic condition.

• Journal of Korea Water Resources Association
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• v.38 no.3 s.152
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• pp.245-257
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• 2005

The purpose of the present study is examining the changes of runoff characteristics and extracting hydrologic parameters by applying ModClark model on grid divided watershed. Bocheong stream basin in Geum River system, one of the representative watersheds of IHP projects, is selected. Hydrology-based topographical informations are calculated using GIS data in the HEC-GeoHMS V1.1 extension in Arcview 3.2. The ModClark model requires precipitation data in a gridded format. The gridded data must be recorded in the HEC Data Storage System file format. Therefore, kriging method was used to interpolate the point values to create a grid that gives each cell over the entire watershed a precipitation value. Hec-DSSVue program was used to create DSS file for the rain gage data. The completed HEC-HMS model was calibrated for use in simulating three measured storm events and cell size of 10000m, 5000m, 2000m, 1000m was chosen for the application. As the result of applying distributed rainfall-runoff model to analyze relatively good agreement for peak discharge, runoff volume and peak time.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.49-56
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• 2010

The Genetic Algorithm is one of the population surface modelling tool in the field of urban and environmental research based on the gridded population data. Taking the East-Hwasung area as the case, this study first builds a gridded population data based on the GIS databases as well as municipal population survey data. The study then constructs the attribute values of the explanatory variables by way of GIS tools. The regression model constructed with the same variables is also run as a comparative purpose at the same time. It is shown that the GenAlg output predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression model, indicating that it is a very useful interdisciplinary research tool to find optimal solutions in urban problems.