• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.53-63
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• 2007

This study is to evaluate the probable snowfall depth by the point frequency analysis and to draw the map of probable snowfall depth in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum depth of snowfall data. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. The estimated parameters were checked by parameter validity conditions of each assumed probability distribution. Four tests that are $X^2-test$, Kolmogorov-Smirnov test, Cramer von Mises test and probability plot correlation coefficient test are used in this study to determine the goodness of fit of the distributions. Mostly the 2-parameter gamma distribution was determined as appropriate distribution for the annual maximum new snowfall depth. The probable snowfall depth were obtained from appropriate distribution for the selected return periods and the maps of probable snowfall depth were presented. It will be useful to specify the snowfall load for the design of agricultural facilities such as vinyl house and cattle shed.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.33-40
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• 2007

This study is to grasp and analyse the temporal and spatial distribution of record-breaking heavy snowfall rarely occurred in the middle and southwest region of South Korea during March of 2004 and December of 2005 respectively. Snow cover area was extracted using the channels 1, 3 and 4 of NOAA AVHRR images and the snow depth distribution was spatially interpolated using snowfall data of meteorological stations. Using administration boundary and Digital Elevation Model from 1:5,000 NGIS digital map, the snowfall impact was assessed spatially and compared with the reports at that time. The damaged area by heavy snowfall over 15 cm snow depth could be identified successfully within the spatial extent of snowfall area extracted by NOAA AVHRR image.

• Journal of Environmental Science International
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• v.18 no.3
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• pp.255-261
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• 2009

We need water equivalent unit data of snowfall for the purpose of forecast and hydrology related research area. This study developed new method of automatic recording snowfall as weight unit. The instrument designed for measuring weight of snowfall by stain-gauge loadcell. Field test of instrument carried out at Daegwallyeong Obs. Station from 22 Jan. to 22 Feb. 2007. During observation period there is 15.3 cm snow depth and 16.0 mm of accumulated water equivalent depth at Daegwallyeong Obs. Station on 13 to 14 Feb. 2007. But the instrument of this study recorded 22.1 mm of water equivalent depth. It is not easy to explain difference between Daegwallyeong and this study. Because this study is only one case of comparison of snow measurement and there is very little amount of snow observation research. The density of snowfall calculated from 0.09 to $0.15g/cm^3$ from the observation data of 13 to 14 Feb. 2007. There is high relation between radar echo and snowfall amount measured by weight unit. It can supports forecast of snowfall and development of numerical model for forecast.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2B
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• pp.103-111
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• 2012

This study is to analyze the spatio-temporal trend of snowfall using 30 years (1980-2010) data for 5 selected heavy snowfall areas (Ulleungdo (a), Northeastern Region (b), Western Taebaek Range Inland Region (c), Northwestern Sobaek Range Inland Region (d) and Southern Coastal Region (e)). The snow depth and snowfall frequency during 30 years showed some decreasing trend in parts of c and d. From the spatial comparison for 2 periods between 1980-2000 (A) and 1990-2010 (B), we could identified that the frequency of advisory for heavy snowfall from A to B decreased in c and d showing clear bounds for some areas in period B. For the average snow depth from A to B, the area d decreased while the area b increased with enlarging the areal range.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.97-104
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• 2012

In this paper, the GPS precipitable water vapor was retrieved by estimating of GPS signal delay in the troposphere during the progress of heavy snowfall on the Gangwon Province, 2011. For this period, the time series analysis between GPS precipitable water vapor and fresh snow depth was accomplished. The time series and the comparison with the GPS precipitable water vapor and the fresh snow depth indicates that the temporal change of two variations is closely related to the progress of the heavy snowfall. Also, the periodicity of GPS precipitable water vapor using the wavelet transform method was showed a similar cycle of saturated water vapor pressure as the limitation of this study span. The result shows that the decrement of GPS precipitable water vapor was conflicted with the increment of fresh snow depth at two sites, Gangneung and Uljin. The correlation between the GPS precipitable water vapor and the saturated water vapor pressure for the event was showed a positive correlation, compare with the non-heavy snowfall periods.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.33-43
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• 2011

This study is to make snowfall distribution map for the 4 heavy snowfall events of January 2001, March of 2004, December of 2005 and January of 2010, and compare the results for three cases of construction methods. The cases are to generate the map by applying IDW(Inverse Distance Weighting) interpolation to 76 ground measured snowfall point data (Snow Depth Map; SDM), mask out the SDM with the MODIS snow cover area (MODIS SCA) of Terra MODIS (MODerate resolution Imaging Spectroradiometer) (SDM+MODIS SCA; SDM_M), and consider the snowdepth lapse rate of snowfall by elevation (Digital Elevation Model; DEM) to the second case (SDM_M+DEM; SDM_MD). By applying the MODIS SCA, the SCA of 4 events was 62.9%, 44.1%, 52.0%, and 69.0% for the area of South Korea. For the average snow depth, the SDM_M decreased 0.9cm, 1.9cm, 0.8cm, and 1.5cm compared to SDM and the SDM_MD increased 1.3cm, 0.9cm, 0.4cm, and 1.2cm respectively.

• Proceedings of the KSRS Conference
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• v.1
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• pp.110-113
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• 2006

This study is to grasp and analyse the temporal and spatial distribution of record-breaking heavy snowfall rarely occurred in the middle and southwest region of South Korea during March of 2004 and December of 2005 respectively. Snow cover area was extracted using the channels 1, 3 and 4 of NOAA AVHRR images and the snow depth distribution was spatially interpolated using snowfall data of meteorological stations. Using administration boundary and Digital Elevation Model from 1:5,000 NGIS digital map, the snowfall impact was assessed spatially and compared with the reports at that time.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.1-12
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• 2015

This study is to analyze the heavy snowfall vulnerable area of snow load design criteria for greenhouse, cattle shed and building using ground measured snow depth data and Terra MODIS snow cover area(SCA). To analyze the heavy snowfall vulnerable area, Terra MODIS satellite images for 12 years(2001-2012) were used to obtain the characteristics of snow depth and snow cover areas respectively. By comparing the snow load design criteria for greenhouse(cm), cattle shed($kg/m^2$), and building structure($kN/m^2$) with the snow depth distribution results by Terra MODIS satellite images, the facilities located in Jeolla-do, Chungcheong-do, and Gangwon-do areas were more vulnerable to exceed the current design criteria.

• Atmosphere
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• v.24 no.1
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• pp.1-15
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• 2014

This study compared ensemble mean and probability forecasts of snow depth amount associated with winter storm over South Korea on 28 December 2012 at five operational forecast centers (CMA, ECMWF, NCEP, KMA, and UMKO). And cause of difference in predicted snow depth at each Ensemble Prediction System (EPS) was investigated by using THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data. This snowfall event occurred due to low pressure passing through South Sea of Korea. Amount of 6 hr accumulated snow depth was more than 10 cm over southern region of South Korea In this case study, ECMWF showed best prediction skill for the spatio-temporal distribution of snow depth. At first, ECMWF EPS has been consistently enhancing the indications present in ensemble mean snow depth forecasts from 7-day lead time. Secondly, its ensemble probabilities in excess of 2~5 cm/6 hour have been coincided with observation frequencies. And this snowfall case could be predicted from 5-day lead time by using 10-day lag ensemble mean 6 hr accumulated snow depth distribution. In addition, the cause of good performances at ECMWF EPS in predicted snow depth amounts was due to outstanding prediction ability of forming inversion layer with below $0^{\circ}C$ temperature in low level (below 850 hPa) according to $35^{\circ}N$ at 1-day lead time.