• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.117-120
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• 2006

Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.124-124
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• 2020

This study proposes a framework to evaluate extreme drought using the natural drought index and hot spot analysis. The study area was South Korea. Data were used from 59 automatic synoptic observing system stations. The variable infiltration capacity model was used for the period from 1981 to 2016. The natural drought index was constructed from precipitation, runoff and soil moisture data, which reflect the water cycle. The average interval, duration and severity of extreme drought events were determined following Run theory. The most extreme drought period occurred in 2014-2016, with 46 of 59 weather stations exhibition drought conditions and 78% exhibition extreme drought conditions. The Inje and Seosan station exhibited the longest drought duration of 6 months, and the most severe drought was 5 times higher than the extreme drought severity threshold. The hot spot analysis was used to explore the extreme drought conditions and showed an increasing trend in the middle and northeastern parts of South Korea. Overall, this study provides water resource managers with essential information about locations and significant trends of extreme drought.

• Journal of the Korean association of regional geographers
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• v.19 no.3
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• pp.384-400
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• 2013

In this study, spatio-temporal patterns of extreme precipitation events caused by typhoons are examined based on observational daily precipitation data at approximately 340 weather stations of Korea Meterological Administration's ASOS (Automated Synoptic Observation System) and AWS (Automatic Weather System) networks for the recent 10 year period (2002~2011). Generally, extreme precipitation events by typhoons exceeding 80mm of daily precipitation commonly appear in Jeju Island, Gyeongsangnam-do, and the eastern coastal regions of the Korean Peninsula. However, the frequency, intensity and spatial extent of typhoon-driven extreme precipitation events can be modified depending on the topography of major mountain ridges as well as the pathway of and proximity to typhoons accompanying the anti-clockwise circulation of low-level moisture with hundreds of kilometers of radius. Yellow Sea-passing type of typhoons in July cause more frequent extreme precipitation events in the northern region of Gyeonggi-do, while East Sea-passing type or southern-region-landfall type of typhoons in August-early September do in the interior regions of Gyeongsangnam-do. These results suggest that when local governments develop optimal mitigation strategies against potential damages by typhoons, the pathway of and proximity to typhoons are key factors.

• Atmosphere
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• v.32 no.3
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• pp.207-221
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• 2022

In Jeju, on January 23, 2016, a cold surge accompanied by heavy snowfall with the most significant amount of 12 cm was the highest record in 32 years. During this period, the temperature of 850 hPa in January was the lowest in 2016. Notably, in 2016, the average surface temperature of January on the Polar cap was the highest since 1991, and 500 hPa geopotential height also showed the highest value. With this condition, the polar vortex in the northern hemisphere meandered and expanded into the subtropics regionally, covering the Korean Peninsula with very high potential vorticity up to 7 Potential Vorticity Unit. As a result, the strong cold advection, mostly driven by a northerly wind, around the Korean Peninsula occurred at over 2𝜎. Previous studies have not addressed this extreme synoptic condition linked to polar vortex expansion due to the unprecedented Arctic warming. We suggest that the occurrence of a strong Ural blocking event after the abrupt warming of the Barents/Karas seas is a major cause of unusually strong cold advection. With a specified mesoscale model simulation with SST (Sea Surface Temperature), we also show that the warmer SST condition near the Korean Peninsula contributed to the heavy snowfall event on Jeju Island.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of Environmental Science International
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• v.24 no.1
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• pp.81-96
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• 2015

The characteristics of atmospheric dispersion of radioactive material (i.e. $^{137}Cs$) related to local wind patterns around the Kori nuclear power plant (KNPP) were studied using WRF/HYSPLIT model. The cluster analysis using observed winds from 28 weather stations during a year (2012) was performed in order to obtain representative local wind patterns. The cluster analysis identified eight local wind patterns (P1, P2, P3, P4-1, P4-2, P4-3, P4-4, P4-5) over the KNPP region. P1, P2 and P3 accounted for 14.5%, 27.0% and 14.5%, respectively. Both P1 and P2 are related to westerly/northwesterly synoptic flows in winter and P3 includes the Changma or typhoons days. The simulations of P1, P2 and P3 with high wind velocities and constant wind directions show that $^{137}Cs$ emitted from the KNPP during 0900~1400 LST (Local Standard Time) are dispersed to the east sea, southeast sea and southwestern inland, respectively. On the other hands, 5 sub-category of P4 have various local wind distributions under weak synoptic forcing and accounted for less than 10% of all. While the simulated $^{137}Cs$ for P4-2 is dispersed to southwest inland due to northeasterly flows, $^{137}Cs$ dispersed northward for the other patterns. The simulated average 137Cs concentrations of each local wind pattern are $564.1{\sim}1076.3Bqm^{-3}$. The highest average concentration appeared P4-4 due to dispersion in a narrow zone and weak wind environment. On the other hands, the lowest average concentration appeared P1 and P2 due to rapid dispersion to the sea. The simulated $^{137}Cs$ concentrations and dispersion locations of each local wind pattern are different according to the local wind conditions.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.983-999
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• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.491-493
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• 2022

Flood damage due to torrential rains and typhoons is occurring in many parts of the world. In this paper, we propose a water level prediction model using water level, precipitation, and humidity data, which are key parameters for flood prediction, as input data. Based on the LSTM and GRU models, which have already proven time-series data prediction performance in many research fields, different input datasets were constructed using the ASOS(Automated Synoptic Observing System) data and AWS(Automatic Weather System) data provided by the Korea Meteorological Administration, and performance comparison experiments were conducted. As a result, the best results were obtained when using ASOS data. Through this paper, a performance comparison experiment was conducted according to the input data, and as a future study, it is thought that it can be used as an initial study to develop a system that can make an evacuation decision in advance in connection with the flood risk determination model.

• 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 association of regional geographers
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• v.20 no.4
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• pp.393-408
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• 2014

In this study, the spatio-temporal characteristics of summer extreme precipitation events in the Republic of Korea are examined based on the daily precipitation data observed at approximately 360 sites of both Automatic Weather Station (AWS) and Automated Synoptic Observation System (ASOS) networks by the Korea Meteorological Administration for the recent decade(2002~2011). During the summer Changma period(late June~mid July), both the frequency of extreme precipitation events exceeding 80mm of daily precipitation and their decadal maximum values are greatest at most of weather stations. In contrast, during the Changma pause period (late July~early August), these patterns are observed only in the northern regions of Geyeonggi province and western Kangwon province as such patterns are detected around Mt. Sobaek and Mt. Halla as well as in the southern regions of Geyeonggi province and western Kangwon province during the late Changma period (mid August~early September) due to north-south oscillation of the Changma front. Investigation of their regional patterns confirms that not only migration of the Changma front but also topological components in response to the advection of moistures such as elevation and aspect of major mountain ridges are detrimental to spatio-temporal patterns of extreme precipitation events. These results indicate that each local administration needs differentiated strategies to mitigate the potential damages by extreme precipitation events due to the spatiotemporal heterogeneity of their frequency and intensity during each Changma period.