• Title/Summary/Keyword: snow depth

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Variations of Soil Temperatures in Winter and Spring at a High Elevation Area (Boulder, Colorado)

  • Lee, Jin-Yong;Lim, Hyoun Soo;Yoon, Ho Il;Kim, Poongsung
    • Journal of Soil and Groundwater Environment
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    • v.20 no.5
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    • pp.16-25
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    • 2015
  • The City of Boulder is located at an average elevation of 1,655 m (5,430 feet), the foothills of the Rocky Mountains in Colorado. Its daily air temperature is much varying and snow is very frequent and heavy even in spring. This paper examines characteristics of shallow (surface and depth = 10 cm) soil temperatures measured from January to May 2015 in the high elevation city Boulder, Colorado. The surface soil temperature quickly responded to the air temperature with the strongest periodicity of 1 day while the subsurface soil temperatures showed a less correlation and delayed response with that. The short-time Fourier of the soil temperatures uncovered their very low frequencies characteristics in heavy snow days while it revealed high frequencies of their variations in warm spring season. The daily minimum air temperature exhibited high cross-correlations with the soil temperatures without lags unlike the maximum air temperature, which is derived from its higher and longer auto-correlation and stronger spectrums of low frequencies than the maximum air temperature. The snow depth showed an inverse relationship with the soil temperature variations due to snow's low thermal conductivity and high albedo. Multiple regression for the soil temperatures using the air temperature and snow depth presented its predicting possibility of them even though the multiple r2 of the regression is not that much satisfactory (r2 = 0.35-0.64).

CFD-DEM modeling of snowdrifts on stepped flat roofs

  • Zhao, Lei;Yu, Zhixiang;Zhu, Fu;Qi, Xin;Zhao, Shichun
    • Wind and Structures
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    • v.23 no.6
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    • pp.523-542
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    • 2016
  • Snowdrift formation on roofs should be considered in snowy and windy areas to ensure the safety of buildings. Presently, the prediction of snowdrifts on roofs relies heavily on field measurements, wind tunnel tests and numerical simulations. In this paper, a new snowdrift modeling method by using CFD (Computational Fluid Dynamics) coupled with DEM (Discrete Element Method) is presented, including material parameters and particle size, collision parameters, particle numbers and input modes, boundary conditions of CFD, simulation time and inlet velocity, and coupling calculation process. Not only is the two-way coupling between wind and snow particles which includes the transient changes in snow surface topography, but also the cohesion and collision between snow particles are taken into account. The numerical method is applied to simulate the snowdrift on a typical stepped flat roof. The feasibility of using coupled CFD with DEM to study snowdrift is verified by comparing the simulation results with field measurement results on the snow depth distribution of the lower roof.

Studies on the Structural Design of Biological Production Facility I. Frequency Analysis of Weather Data for Design Load Estimation (생물생산시설의 구조설계에 관한 연구 I. 설계하중 산정을 위한 기상자료 빈도분석)

  • 김문기;손정익;남상운;이동근;이석재
    • Journal of Bio-Environment Control
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    • v.1 no.1
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    • pp.1-13
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    • 1992
  • This study was attemped to provide some fundamental data for the safety structural design of biological production facility. Wind speed and snow depth according to recurrence intervals for design load estimation were calculated by frequency analysis using the weather data of 60 stations in Korea. The following results were obtained : 1. Type-I extremal distribution was selected for the probability density function of yearly maximum wind speed and snow depth and result of Chi-square goodness of fit showed highly significance at most regions. 2. Design frequency factors for given number of samples and recurrence intervals were calculated, and also design wind speed and snow depth as shown in Table 5-Table 6 and Fig.3-Fig.4 were derived. 3. About 46.4% of the winds having maximum wind speed at every station was analyzed to be same direction, and the consideration of this fact may improve the structural safety. 4. Considering wind speed and snow depth, protected cultivation is very difficult in Ullungdo and the Youngdong districts, and strong structural design is needed in the Chungnam and Junbuk west seaside against snow depth and the west-south seaside against wind speed in Korea.

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Application of Artificial Neural Network for estimation of daily maximum snow depth in Korea (우리나라에서 일최심신적설의 추정을 위한 인공신경망모형의 활용)

  • Lee, Geon;Lee, Dongryul;Kim, Dongkyun
    • Journal of Korea Water Resources Association
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    • v.50 no.10
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    • pp.681-690
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    • 2017
  • This study estimated the daily maximum snow depth using the Artificial Neural Network (ANN) model in Korean Peninsula. First, the optimal ANN model structure was determined through the trial-and-error approach. As a result, daily precipitation, daily mean temperature, and daily minimum temperature were chosen as the input data of the ANN. The number of hidden layer was set to 1 and the number of nodes in the hidden layer was set to 10. In case of using the observed value as the input data of the ANN model, the cross validation correlation coefficient was 0.87, which is higher than that of the case in which the daily maximum snow depth was spatially interpolated using the Ordinary Kriging method (0.40). In order to investigate the performance of the ANN model for estimating the daily maximum snow depth of the ungauged area, the input data of the ANN model was spatially interpolated using Ordinary Kriging. In this case, the correlation coefficient of 0.49 was obtained. The performance of the ANN model in mountainous areas above 200m above sea level was found to be somewhat lower than that in the rest of the study area. This result of this study implies that the ANN model can be used effectively for the accurate and immediate estimation of the maximum snow depth over the whole country.

Development of Weight Type Rounded Snow Plate (중량식 원형 적설판 개발에 관한 연구)

  • Lee, Bu-Yong;Kim, Hyun-Chul
    • Atmosphere
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    • v.19 no.1
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    • pp.1-8
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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 with circle type plate using stain-gauge loadcell. Field test of instrument carried out at Daegwallyeong Obs. Station from 20 to 23 Jan. 2008 during heavy snowfall. There is 74.2cm snow depth and 54.6mm precipitation by Daegwallyeong Obs. Station. But the instrument of this study recorded 71.0mm of precipitation amount. Because of different observation method can cause more 15.4mm than Daegwallyeong Obs. Station. But this study gives the possibility of observation of new snow fall measurement under freezing conditions of snow. From the observation data the density of snowfall calculated from 0.09 to $1015g/cm_3$ from the observation period. And have a good relations between manual observation and automatic observation data from this study instrument with slope of 1.35 to 1.39.

Mapping Technique for Heavy Snowfall Distribution Using Terra MODIS Images and Ground Measured Snowfall Data (Terra MODIS 영상과 지상 적설심 자료를 이용한 적설분포도 구축기법 연구)

  • Kim, Saet-Byul;Shin, Hyung-Jin;Lee, Ji-Wan;Yu, Young-Seok;Kim, Seong-Joon
    • 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.

Development of Dynamical Seasonal Prediction System for Northern Winter using the Cryospheric Condition of Late Autumn (가을철 빙권 조건을 활용한 겨울철 역학 계절 예측시스템의 개발)

  • Shim, Taehyoun;Jeong, Jee-Hoon;Kim, Baek-Min;Kim, Seong-Joong;Kim, Hyun-Kyung
    • Atmosphere
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    • v.23 no.1
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    • pp.73-83
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    • 2013
  • In recent several years, East Asia, Europe and North America have suffered successive cold winters and a number of historical records on the extreme weathers are replaced with new record-breaking cold events. As a possible explanation, several studies suggested that cryospheric conditions of Northern Hemisphere (NH), i.e. Arctic sea-ice and snow cover over northern part of major continents, are changing significantly and now play an active role for modulating midlatitude atmospheric circulation patterns that could bring cold winters for some regions in midlatitude. In this study, a dynamical seasonal prediction system for NH winter is newly developed using the snow depth initialization technique and statistically predicted sea-ice boundary condition. Since the snow depth shows largest variability in October, entire period of October has been utilized as a training period for the land surface initialization and model land surface during the period is continuously forced by the observed daily atmospheric conditions and snow depths. A simple persistent anomaly decaying toward an averaged sea-ice condition has been used for the statistical prediction of sea-ice boundary conditions. The constructed dynamical prediction system has been tested for winter 2012/13 starting at November 1 using 16 different initial conditions and the results are discussed. Implications and a future direction for further development are also described.

Evaluation of bias and uncertainty in snow depth reanalysis data over South Korea (한반도 적설심 재분석자료의 오차 및 불확실성 평가)

  • Jeon, Hyunho;Lee, Seulchan;Lee, Yangwon;Kim, Jinsoo;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.56 no.9
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    • pp.543-551
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    • 2023
  • Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

Fishing investigation with trammel nets by mesh size in the Korean deep-water of the East Sea (삼중자망에 의한 동해 심해 수산자원의 망목별 어획특성)

  • Park, Hae-Hoon
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.49 no.1
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    • pp.1-17
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    • 2013
  • The investigation for species composition and catch in the Korean deep-water of the East Sea (also known as Sea of Japan) was carried out with trammel nets of 7 mesh sizes (6.1~24.2cm) offshore Donghae (2006) and Yangyang (2007) of Korea. The catches were 1,268kg and composed of 37 species between 200m and 1,200m in depth. The principal species caught were Taknka's snailfish, salmon snailfish, red snow crab, hunchback sculpin, snow crab, spinyhead sculpin, Tanaka's eelpout, Alaska cod and so on. Those were target fish for commercial value except salmon snailfish. The mesh sizes for the largest catch were 10.6cm and 15.2cm in the fishing ground of Donghae and Yangyang, respectively. The habitat of snow crab was shallower than that of red snow crab in both areas. Trammel net enabled to investigate fish in deep-water with small fishing vessel and rather cheap expenses in contrast to bottom trawl that required too much of it. With increasing inner mesh size of trammel net the mean size of some principal species such as Taknka's snailfish, spinyhead sculpin, hunchback sculpin, Pacific cod, snow crab, red snow crab and hybrid between snow crab and red snow crab tended to be large in certain range of mesh size.

Correlation Analysis between GPS Precipitable Water Vapor and Heavy Snowfall on Gangwon Province in Early 2011 (2011년 강원 폭설과 GPS 가강수량의 상관성 분석)

  • Song, Dong-Seob
    • 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.