• Title/Summary/Keyword: snowfall days

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The Distribution of Precipitation in Donghae-Shi (동해시의 강수 분포 특성)

  • 이장렬
    • The Korean Journal of Quaternary Research
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    • v.13 no.1
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    • pp.45-52
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    • 1999
  • This study examined the spatial distribution of precipitation in Donghae-Shi. The daily, monthly precipitaion on the 2 stations, 3 AWS(Automatic Weather Station) were analyzed by altitudinal distribution, the air pressure type and days of daily precipitation. The results of the study are as follows. 1 Hour greatest precipitation is 62.4mm(1994. 10. 12), Daily greatest precipitation, 200mm(1994. 10. 12), Monthly greatest precipitation, 355.5mm(1994. 10), Maximum depth of snow fall, 35.5cm(1994. 1. 29) in Donghae-Shi, 1993∼1997. Altitudinal distribution of precipitation in Summer tends to have more precipitation at higher altitude, in Winter, high mountains and coast have more precipitation than other sites do. The heavy rainfall in Donghae-Shi is mainly formed by a Typhoon, next is Jangma front. The number of consecutive days of daily precipitation $\geq$20mm is 81days, 44days of those appeared in Summer season. The synoptic environment causes the difference in observed the heavy snowfall amount between high mountains and coast.

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Binary Forecast of Asian Dust Days over South Korea in the Winter Season (남한지역 겨울철 황사출현일수에 대한 범주 예측모형 개발)

  • Sohn, Keon-Tae;Lee, Hyo-Jin;Kim, Seung-Bum
    • The Korean Journal of Applied Statistics
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    • v.24 no.3
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    • pp.535-546
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    • 2011
  • This study develops statistical models for the binary forecast of Asian dust days over South Korea in the winter season. For this study, we used three kinds of data; the rst one is the observed Asian dust days for a period of 31 years (1980 to 2010) as target values, the second one is four meteorological factors(near surface temperature, precipitation, snowfall, ground wind speed) in the source regions of Asian dust based on the NCEP reanalysis data and the third one is the large-scale climate indices. Four kinds of statistical models(multiple regression models, logistic regression models, decision trees, and support vector machines) are applied and compared based on skill scores(hit rate, probability of detection and false alarm rate).

Analysis of Rain Impacts on Freeway Trip Characteristics (강우와 고속도로 통행특성의 관계 연구)

  • Baek, Seung-Kirl;Kim, Bum-Jin;Lim, Yong-Taek
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.119-128
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    • 2008
  • Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in rainy days of 2006. We compare the normal travel patterns with those of rainy days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in rainy days as we expect, and also show different travel patterns for weekday and weekend.

Comparative Analysis of GNSS Precipitable Water Vapor and Meteorological Factors (GNSS 가강수량과 기상인자의 상호 연관성 분석)

  • Jae Sup, Kim;Tae-Suk, Bae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.317-324
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    • 2015
  • GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (Tm), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

Study of Snow Depletion Characteristics at Two Mountainous Watersheds Using NOAA AVHRR Time Series Data

  • Shin, Hyungjin;Park, Minji;Chae, Hyosok;Kim, Saetbyul;Kim, Seongjoon
    • Korean Journal of Remote Sensing
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    • v.29 no.3
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    • pp.315-324
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    • 2013
  • Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.

An Empirical Study on the Influence of Weather and Daytime on Restaurant Menu search System (날씨 및 요일 특성이 음식점 메뉴 검색시스템 이용에 미치는 영향에 관한 실증 연구)

  • Cho, Chan-Yeol;Jung, Ku-Imm;Seo, Yang-Min;Choi, Hae-Lim
    • Smart Media Journal
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    • v.6 no.2
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    • pp.50-56
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    • 2017
  • Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

Current and Future Changes in the Type of Wintertime Precipitation in South Korea (현재와 미래 우리나라 겨울철 강수형태 변화)

  • Choi, Gwang-Yong;Kwon, Won-Tae
    • Journal of the Korean Geographical Society
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    • v.43 no.1
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    • pp.1-19
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    • 2008
  • This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

Calculation of Non-Working Days due to Weather Factors during Structural Steel Works (기후요소에 의한 철골공사 작업불가능일 산정에 관한 연구)

  • Lee, Duk-Hyung;You, Jung-Sik;You, Jae-Kil;Jung, Jae-Hun;Jung, Hee-Kyung;Yu, Jung-Ho;Kim, Chang-Duk
    • Korean Journal of Construction Engineering and Management
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    • v.7 no.4 s.32
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    • pp.137-145
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    • 2006
  • Calculating non-working days is very important element for the accurate estimation of construction time. And non-working days are largely affected by weather factors such as rainfall, wind velocity, snowfall and temperature. In the case of concrete works, there are lots of referable information for the calculation of non-working days due to the weather factors. However, for the structural steel works, there are very limited information only. Through literature survey and interviews with a few engineers, this paper established the weather factors that affect steel structural works and the impact of those factors. Based on the factors and the expected impact of the factors together with the weather data during the last 15 years in Seoul region gathered from Korea Meteorological Administration, this paper suggests the monthly non-working day of structural steel work due to weather factors. This information can be used for the early estimation of construction time.

Gamma-ray Exposure Rate Monitoring by Energy Spectra of NaI(Tl) Scintillation detectors

  • Lee, Mo Sung
    • Journal of Radiation Protection and Research
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    • v.42 no.3
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    • pp.158-165
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    • 2017
  • Background: Nuclear facilities in South Korea have generally adopted pressurized ion chambers to measure ambient gamma ray exposure rates for monitoring the impact of radiation on the surrounding environment. The rates assessed with pressurized ion chambers do not distinguish between natural and man-made radiation, so a further step is needed to identify the cause of abnormal variation. In contrast, using NaI(Tl) scintillation detectors to detect gamma energy rates can allow an immediate assessment of the cause of variation through an analysis of the energy spectra. Against this backdrop, this study was conducted to propose a more effective way to monitor ambient gamma exposure rates. Materials and Methods: The following methods were used to analyze gamma energy spectra measured from January to November 2016 with NaI detectors installed at the Korea Atomic Energy Research Institute (KAERI) dormitory and Hanbat University. 1) Correlations of the variation of rates measured at the two locations were determined. 2) The dates, intervals, duration, and weather conditions were identified when rates increased by $5nSv{\cdot}h^{-1}$ or more. 3) Differences in the NaI spectra on normal days and days where rates spiked by $5nSv{\cdot}h^{-1}$ or more were studied. 4) An algorithm was derived for automatically calculating the net variation of the rates. Results and Discussion: The rates measured at KAERI and Hanbat University, located 12 kilometers apart, did not show a strong correlation (coefficient of determination = 0.577). Time gaps between spikes in the rates and rainfall were factors that affected the correlation. The weather conditions on days where rates went up by $5nSv{\cdot}h^{-1}$ or more featured rainfall, snowfall, or overcast, as well as an increase in peaks of the gamma rays emitted from the radon decay products of $^{214}Pb$ and $^{214}Bi$ in the spectrum. This study assumed that $^{214}Pb$ and $^{214}Bi$ exist at a radioactive equilibrium, since both have relatively short half-lives of under 30 minutes. Provided that this assumption is true and that the gamma peaks of the 352 keV and 1,764 keV gamma rays emitted from the radionuclides have proportional count rates, no man-made radiation should be present between the two energy levels. This study proved that this assumption was true by demonstrating a linear correlation between the count rates of these two gamma peaks. In conclusion, if the count rates of these two peaks detected in the gamma energy spectrum at a certain time maintain the ratio measured at a normal time, such variation can be confirmed to be caused by natural radiation. Conclusion: This study confirmed that both $^{214}Pb$ and $^{214}Bi$ have relatively short half-lives of under 30 minutes, thereby existing in a radioactive equilibrium in the atmosphere. If the gamma peaks of the 352 keV and 1,764 keV gamma rays emitted from these radionuclides have proportional count rates, no man-made radiation should exist between the two energy levels.

Characteristics of Meteorological Variables in the Leeward Side associated with the Downslope Windstorm over the Yeongdong Region (영동지역 지형성 강풍과 관련된 풍하측 기상요소의 특징)

  • Cho, Young-Jun;Kwon, Tae-Yong;Choi, Byoung-Cheol
    • 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.