• 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).

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.272-289
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• 2004

The spatial resolution of local weather and climate information for agronomic practices exceeds the current weather service scale. To supplement the insufficient spatial resolution of official forecasts and observations, gridded climate data are frequently generated. Most ecological models can be run using gridded climate data to produce ecosystem responses at landscape scales. In this lecture, state of the art techniques derived from geospatial climatology, which can generate gridded climate data by spatially interpolating point observations at synoptic weather stations, will be introduced. Removal of the urban effects embedded in the interpolated surfaces of daily minimum temperature, incorporation of local geographic potential for cold air accumulation into the minimum temperature interpolation scheme, and solar irradiance correction for daytime hourly temperature estimation are presented. Some experiences obtained from their application to real landscapes will be described.

• 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 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.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.33-36
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• 2007

We have persistently constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (ERS and Qscat). They are available for users as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO) data together with heat flux components. Recently, a new version data of the Qscat/SeaWinds based on improved algorithm for rain flag and high wind-speed range have been delivered, and allowed us to reconstruct gridded product with higher spatial resolution. These products are validated by comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON, NDBC and the Kuroshio Extension Observation (KEO) buoys, together with numerical weather prediction model products such as the NCEP-1 and 2. Results reveal that the new product has almost the same magnitude in mean difference as the previous version of Qscat product and much smaller than the NCEP-1 and 2. On the other hand, it is slightly larger root-mean-square (RMS) difference than the previous one and NCEPs for the comparison using the KEO buoy data. This may be due to the deficit of high wind speed data in the buoy measurement. The high resolution product, together with sea surface temperature (SST) one, is used to examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region.

• 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.

• Ocean and Polar Research
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• v.31 no.1
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• pp.11-29
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• 2009

Variability of sea surface temperature (SST) in the Japan/East Sea (JES) was studied using complex empirical orthogonal function (CEOF) analysis. Two daily data sets were analyzed: (1) New Generation 0.05o-gridded SST from Tohoku University, Japan (July 2002-July 2006), and (2) 0.25o-gridded SST from the Japan Meteorological Agency (October 1993-November 2006). Linkages with wind stress curl were revealed using 6-h 1o-gridded surface zonal and meridional winds from ancillary data of the Sea- WiFS Project, a special National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) product (1998-2005). SST anomalies (SSTA) were obtained by removing the seasonal signal, estimated as the leading mode of the CEOF decomposition of the original SST. Leading CEOF modes of residual SSTA obtained from both data sets were consistent with each other and were characterized by annual, semiannual, and quasi-biennial time scales estimated with 95% statistical significance. The Semiannual Mode lagged 2 months behind the increased occurrence of the anticyclonic (AC) wind stress curl over the JES. Links to dynamic processes were investigated by numerical simulations using an oceanic model. The suggested dynamic forcings of SSTA are the inflow of subtropical water into the JES through the Korea Strait, divergence in the surface layer induced by Ekman suction, meridional shifts of the Subarctic Front in the western JES, AC eddy formation, and wind-driven strengthening/weakening of large-scale currents. Events of west-east SSTA movement were identified in July-September. The SSTA moved from the northeastern JES towards the continental coast along the path of the westward branch of the Tsushima Current at a speed consistent with the advective scale.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.68-76
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• 2006

A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.556-572
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• 2015

This paper presents the applications of spatial interpolation and assimilation methods for satellite and ground meteorological data, including temperature, relative humidity, and precipitation in regions of Vietnam. In this work, Universal Kriging is used for spatially interpolating ground data and its interpolated results are assimilated with corresponding satellite data to anticipate better gridded data. The input meteorological data was collected from 98 ground weather stations located all over Vietnam; whereas, the satellite data consists of the MODIS Atmospheric Profiles product (MOD07), the ASTER Global Digital Elevation Map (ASTER DEM), and the Tropical Rainfall Measuring Mission (TRMM) in six years. The outputs are gridded fields of temperature, relative humidity, and precipitation. The empirical results were evaluated by using the Root mean square error (RMSE) and the mean percent error (MPE), which illustrate that Universal Kriging interpolation obtains higher accuracy than other forms of Kriging; whereas, the assimilation for precipitation gradually reduces RMSE and significantly MPE. It also reveals that the accuracy of temperature and humidity when employing assimilation that is not significantly improved because of low MODIS retrieval due to cloud contamination.

• 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.