• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2005.10a
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• pp.138-144
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• 2005

• 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.

• Current Research on Agriculture and Life Sciences
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• v.31 no.4
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• pp.280-285
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• 2013

This study supplies basic data to develop a greenhouse model for reducing the damage to single-span greenhouses caused by strong winds and heavy snow. Single-span plastic greenhouses are predominantly used for growing crops in Korea. Thus, the safety wind speeds for single-span greenhouses were calculated and compared with the actual wind speeds and snow depths over a period of 8 years in different regions to analyze the structural safety of single-span greenhouses. The unit wind load and unit snow load were applied to different designs of single-span greenhouse according to the cultivated crop to achieve a structural analysis. As a result, the maximum section force for the wind and snow load was greatest for leaf and root vegetables, where the safety wind speeds for single-span greenhouses according to the cultivated crop were 17.7 m/s(leaf vegetables), 20.2 m/s (fruit vegetables), and 22.3 m/s (root vegetables). Thus, the single-span greenhouses were not found to be safe for the wind load in most regions, except for Hongcheon, Icheon and Sungju. Plus, the safety snow depths for single-span greenhouses according to the crop were 8.8 cm (leaf vegetables), 9.4 cm (fruit vegetables), and 11.8cm (root vegetables). Thus, when comparing the safety snow depths with the actual snow depths, the single-span greenhouses were not found to be safe. Therefore, to improve the safety of single-span greenhouses, the structures need reinforcement by reducing the interval between rafters or increasing the size of the pipes. However, additional research is needed.

• Atmosphere
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• v.33 no.2
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• pp.223-246
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• 2023

This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.1-7
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• 2010

Recently, the damage of the farmhouse has been increased due to frequent collapsing accidents of the pipe greenhouse caused by the heavy snow load derived from unusual weather phenomena. However, the study about it is rare and tenuous so that the damage is happened repeatedly. Although there are a few ways to improve the greenhouse such as increasing section, decreasing the distance between rafters in order to avoid the collapsing accidents, those ways have some shortcomings like cost and frame ratio increase, etc. Therefore, this study performed the large displacement analysis considering geometric non-linearity on each load level with respect to many kind of reinforcement methods and analyzed combined strength ratio and stress so as to search the ways, which enhance the structural stability of greenhouse and minimize the frame ratio increase. As a result, this paper is aimed at suggesting the optimal reinforcement method model.

• Journal of Korean Association for Spatial Structures
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• v.10 no.2
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• pp.61-68
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• 2010

The collapsing accidents of pipe greenhouses in the farmhouse have been increased duo to heavy snow load. However, the study on exact structure analysis to prevent the collapse of pipe greenhouses is rare and the damage of the farmhouse is annually repeated. The method of existing structure analysis is basically made of linear elastic analysis based on the micro displacement. But the actual stiffness of the pipe greenhouse is significantly weaker than the stiffness of buildings and the load acting on the greenhouses gets to become relatively bigger. It means that the geometry shape of greenhouses changes so that the relation of strain-displacement gets to indicate a nonlinear behavior. Therefore, this study is performed to evaluate the structural safety so as to prevent the collapse of pipe greenhouses, which are the single-span greenhouse(farmhouse guidance shape, G) and multi-span greenhouse(farmhouse supply shape, 1-2W), by performing the large-displacement analysis considering nonlinear effects.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.21-33
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• 2020

Purpose: The objective of this research is to classify snowfall area types with consideration of past regional snowfall characteristics and times for the effective local snow removal response systems of 229 local government districts. Method: This research first collected snowfall data of South Korea meteorological stations, and classified regional types using successive snowfall time. This research finally produced GIS maps using regional type information of snowfalls by applying GIS analysis methods. Result: This research provides five types of snowfall regions including 'frequent heavy snowfall regions', 'frequent light snowfall regions', 'rare heavy snowfall regions', 'average snowfall regions', and 'rare light snowfall regions' based on analysis results. Conclusion: Results of this research can be used as basic information for regional demand estimations of snow removal equipments, materials, vehicles, and personnel for the efficient snow removal response systems.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.135-143
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• 2012

Remote sensing which observes repeatedly the whole Earth and GIS-based decision-making technology have been utilized widely in disaster management such as early warning monitoring, damage investigation, emergent rescue and response, rapid recovery etc. In addition, various countermeasures of national level to collect timely satellite imagery in emergency have been considered through the operation of a satellite with onboard multiple sensors as well as the practical joint use of satellite imagery by collaboration with space agencies of the world. In order to respond heavy snowfall disaster occurred on the east coast of the Korean Peninsula in February 2011, snow-covered regions were analyzed and detected in this study through NDSI(Normalized Difference Snow Index) considering reflectance of wavelength for MODIS sensor and change detection algorithm using satellite imagery collected from International Charter. We present the application case of National Disaster Management Institute(NDMI) which supported timely decision-making through GIS spatial analysis with various spatial data and snow cover map.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1125-1135
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• 2022

Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.