• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.869-875
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• 2016

The purpose of this study is to analyze the long-term wave characteristics and tendencies of coastal waters near Korea based on wave hind-casting modelling. Wave hind-casting modelling was performed with a wind data set from ECMWF (2001~2014), which provides data from 1979 to the present. The results of numerical modelling were verified with observed data collected using wave buoys installed by the Korea Meteorological Administration (KMA) and Korea Hydrographic and Oceanographic Agency (KHOA) in offshore waters. The results agreed well with observations from buoy stations, especially during event periods such as typhoons. The quantitative RMSE value was 0.5 m, which was significant. Consequently, the results of a wave tendency analysis for 14 years (2001~2014) showed an increased appearance ratio for waves of more than 2 m in height at all regional domains. The mean appearance ratio was 0.082 % per year, which implies that coastal waves have been increasing continuously. This coastal wave tendency analysis data can be used to evaluate coastal vulnerability due to recent climate change and the design of coastal erosion prevention structures.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.245-255
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• 2015

This study used high density network of integrated meteorological sensor, which are operated by SK Planet, with KMA weather stations to estimate the quantitative precipitation field in Seoul area. We introduced SK Planet network and analyzed quality of the observed data for 3 months data from 1 July to 30 September 2013. As the quality analysis result, we checked most SK Planet stations observed similar with previous KMA stations. We developed the real-time quality check and adjustment method to reduce the error effect for hydrological application by missing and outlier value and we confirmed the developed method can be corrected the missing and outlier value. Through this method, we used the 190 stations(KMA 34 stations, SK Planet 156 stations) that missing ratio is less than 20% and the effect of the outlier was the smallest for quantitative precipitation estimation. Moreover, we evaluated reproducibility of rainfall field high density rain gauge network has $3km^2$/gauge. As the result, the spatial relative frequency of rainfall field using SK Planet and KMA stations is similar with radar rainfall field. And, it supplement the blank of KMA observation network. Especially, through this research we will take advantage of the density of the network to estimate rainfall field which can be considered as a very good approximation of the true value.

• Atmosphere
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• v.29 no.5
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• pp.671-687
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• 2019

This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.47-64
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• 2013

Landscape structure changes over the past three decades were determined with land use and land cover(LULC) maps, and their relationships with mean air temperature time series were the analyzed for the Busan metropolitan area and South Kyeongsang Province, Korea. The geometric structures of the LULC data were quantitatively represented based on FRAGSTATS, a spatial pattern analysis program for quantifying landscape structure. FRAGSTATS-derived landscape metrics confirmed that there were major changes in LULC and landscape fragmentation in the region. Meteorological observation records showed that mean air temperature had increased from $14.1^{\circ}C$ in the 1990's to $14.8^{\circ}C$ in the 2000's in Busan. For South Kyeongsang Province, they increased from $13.2^{\circ}C$ to $13.9^{\circ}C$ during the same time period. These long-term temperature changes are correlated with typical spatial pattern changes of LULC in the southeastern region of the country. Spatial metrics analysis showed that urban area expanded from 9.7% to 26.8% of Busan while forest and agricultural land decreased by 9.6% and 14.9%, respectively over the past thirty years. The significant urbanization are tightly associated with deforestation, removal of agricultural land, and fast temperature increases since the 1990's. The urban area of South Kyeongsang Province rapidly increased, and it became 12 times as large as it was. The degree of temperature increases differed among three different sub-regions. The temperature increasing rate was lowest in the coastal region while the colder mountainous region had the highest figure.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.599-607
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• 2015

The purpose of this study is to reproduce long-term wave fields in coastal waters of Korea based on wave hind-casting modelling and discuss its applications. To validate wind data(NCEP, ECMWF, JMA-MSM), comparison of wind data was done with wave buoy data. JMA-MSM predicted wind data with high accuracy. But due to relatively longer period of ECMWF wind data as compared to that of JMA-MSM, wind data set of ECMWF(2001~2014) was used to perform wave hind-casting modelling. Results from numerical modelling were verified with the observed data of wave buoys installed by Korea Meteorological Administration(KMA) and Korea Hydrographic and Oceanographic Agency(KHOA) on offshore waters. The results agree well with observations at buoy stations, especially during the event periods such as a typhoon. Consequently, the wave data reproduced by wave hind-casting modelling was used to obtain missing data in wave observation buoys. The obtained missing data indicated underestimation of maximum wave height during the event period at some points of buoys. Reasons for such underestimation may be due to larger time interval and resolution of the input wind data, water depth and grid size etc. The methodology used in present study can be used to analyze coastal erosion data in conjunction with a wave characteristic of the event period in coastal areas. Additionally, the method can be used in the coastal disaster vulnerability assessment to generate wave points of interest.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.305-311
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• 2019

Recently, global climate change causes abnormal weather and disaster countermeasures do not provide sufficient defense and mitigation because they were established according to the historical climate condition. Repeated torrential rains, in particular, are causing damage even in the robust urban flood defense system. Therefore, in this study, the change of runoff considering the spatial distribution of rainfall and urban characteristics was analyzed. For rainfall concentrated in small catchment, rainfall in the watershed must be accurately measured. This study is based on the rainfall data observed with Automated Surface Observing System (ASOS) and Automatic Weather Stations (AWS) provided by the Seoul Meteorological Administration. Effluent from the pumping station was estimated using the EPA-SWMM model and compared and analyzed. Catchments with rainwater pumping station are small with large portion of impermeable areas. Thus, when the ASOS data where is located from from the chatchment, runoff is often calculated using rainfall data that is different from rainfall in the catchment. In this study, the difference between rainfall data observed in the AWS near the catchment and ASOS away from the catchment was calculated. It was found that accurate rainfall should be used to operate rainwater pumping stations or forecast urban flooding floods. In addition, the results of this study may be helpful for estimating design rainfall and runoff calculation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.83-91
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• 2014

The occurrence of abnormal sunshine duration was analyzed using meteorological data collected from 60 observation stations during the last 38 years (1973-2010). The 20 agro-climatic zones defined by the Rural Development Administration, were used as a spatial unit for the analysis. On average, abnormal duration of sunshine occurred 1.24 times per year since 1973. The abnormally long duration of sunshine occurred less frequenctly in 2000s (0.47 per year) than in 1970s (1.26 per year). However, the frequency of abnormally short duration of sunshine has increased from an average of 0.58 per year in 1970s to 0.98 in 2000s. The highest frequency of abnormally long duration of sunshine appeared in Central Inland zone with an average of 1.35 frequencies per year. On the other hand, abnormally short duration of sunshine was the most frequent in South Eastern Coastal zone with an average of 0.97 frequencies per year.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.232-245
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• 2017

In this study, the high-resolution numerical simulation results considering landuse characteristics are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, the impact of urban parameters such as roughness length and anthropogenic heat in UCM is analyzed. These values are adjusted to Seoul metropolitan area in Korea. The results of assessment are verified against observation from surface and flux tower. Forecast system equipped with UCM shows an overall improvement in the simulations of meteorological parameters, especially temperature at 2 m, surface sensible and latent heat flux. Major contribution of UCM is appreciably found in urban area rather than non-urban. The non-urban area is indirectly affected. In simulated latent heat flux, applying UCM is possible to simulate the change similarly with observations on urban area. Anthropogenic heat employed in UCM shows the most realistic results in terms of temperature and surface heat flux, indicating thermodynamic treatment of UCM could enhance the skills of high resolution forecast model in urban and non-urban area.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.123-137
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• 1992

We analyzed a time series composed of the annual precipitations of Seoul based on the measurements of a Korean raingage and a modern raingage. The precipitations measured with a Korean raingage for the period of 1771 to 1907 are followed by the precipitations with a modern raingage for the period of 1908 to 1990. The latter part of the time series of annual precipitations were obtained from a book for annual precipitations of Korea by Korea Meteorological Administration and the former from Wada's table 1 for monthly precipitations reproduced from the daily rainfall measurements by a Korean raingage for the period of the Yi Dynasty. In our analysis three different precipitation regimes clearly stand out of the entire period. In order to define objectively the period of each precipitation regime we made a time series of 9 year moving averages from the above time series. By taking into account the shapes of the moving average time series and by using a threshold value of annual precipitation 1050 mm, we defined three precipitation regimes of wet period 1(WP1), dry period (DP), and wet period 2 (WP2). The WP1 and WP2 show very similar characteristics in out statistical analyses. On the other hand, DP is very different from the two periods in many statistical aspects. The strong similarities of the WP1 and WP2 regimes in the magnitudes of statistical parameters and in the shapes of their power spectrum distribution are supporting very positively the soundness of precipitation amounts measured with a Korean raingage in spite of numerous conceivable errors which might have been introduced into measurements of precipitation due to changes of observation site and environment, the scale of units employed, and urbanization of Seoul, etc. However, the annual precipitation amounts are not enough to examine throughly the characteristic of precipitation variations during the two regimes. It is definitely necessarly to recover the daily amounts of precipitation, based on two or three times measurements of rainfall with a Korean raingage, scattered in various ancient documents such as the official diary of 'Seungjeong-weon'