• Title/Summary/Keyword: four precipitation cases

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Tail dependence of Bivariate Copulas for Drought Severity and Duration

  • Lee, Tae-Sam;Modarres, Reza;Ouarda, Taha B.M.J.
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.571-575
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    • 2010
  • Drought is a natural hazard with different properties that are usually dependent to each other. Therefore, a multivariate model is often used for drought frequency analysis. The Copula based bivariate drought severity and duration frequency analysis is applied in the current study in order to show the effect of tail behavior of drought severity and duration on the selection of a copula function for drought bivariate frequency analysis. Four copula functions, namely Clayton, Gumbel, Frank and Gaussian, were fitted to drought data of four stations in Iran and Canada in different climate regions. The drought data are calculated based on standardized precipitation index time series. The performance of different copula functions is evaluated by estimating drought bivariate return periods in two cases, [$D{\geq}d$ and $S{\geq}s$] and [$D{\geq}d$ or $S{\geq}s$]. The bivariate return period analysis indicates the behavior of the tail of the copula functions on the selection of the best bivariate model for drought analysis.

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Analysis of Drought Propagation from Meteorological to Hydrological Drought Considering Spatio-temporal Moving Pattern of Drought Events (가뭄사상의 시공간적 이동 패턴을 고려한 기상학적 가뭄에서 수문학적 가뭄으로의 전이 분석)

  • Yoo, Jiyoung;So, Byung-Jin;Lee, Joo-Heon;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.2
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    • pp.135-143
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    • 2020
  • Natural drought is a three-dimensional phenomenon that simultaneously evolves in time and space. To evaluate the link between meteorological and hydrological droughts, we defined a drought event from a three-dimensional perspective and analyzed the propagation characteristics in time and spaces. Overall results indicated that 77 % of the total cases of spatio-temporal droughts was propagated based on the single category relationship between meteorological and hydrological drought events, while 23 % was affected by multiple meteorological drought events to the occurrence of hydrological drougts. Especially, it turned out that the hydrological drought was caused by the spatio-temporal effects of the propagation of four meteorological drought events generated due to long-term lack of precipitation in 1994-1995. In addition, the meteorological drought caused by the lack of precipitation in the summer of 2001 lasted for several months, and was propagated to the hydrological drought in April 2002.

Implement of Search Cases of Environmental Data Based on Fuzzy Criteria for Development of Environmental Scenario Generator (환경 시나리오 발생기 개발을 위한 퍼지 논리 기반 환경 자료의 검색 사례 구현)

  • Park, Jongchul;Kim, Man-Kyu
    • Journal of the Korea Society for Simulation
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    • v.26 no.3
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    • pp.73-86
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    • 2017
  • Environmental data plays an important role to enhance the reliability of experimental results in M&S(Modeling and Simulation). Especially in Military M&S, extreme weather events can be used for virtual training and simulation importantly. However, the environmental data is huge and it is dispersed among multiple organizations. It is difficult for M&S operators to select the date and area where the weather phenomenon occurs in the real environmental data and to acquire them. Environmental data retrieval technology based on Fuzzy criteria is one of the important technologies for developing Environmental Scenario Generator. As a result of this study, a fuzzy retrieval algorithm composed of four main parameters(RV, MF, FRA, and MRV) was presented. This study suggests that the RV can be used as 14 m/s for wind speed and 80 mm/d for precipitation to search the date of storm accompanied by high wind. The MF, the FRA, and MRV can be used sigmoid, 0.2, and 1 respectively. The algorithm proposed in this study is expected to be very useful for searching the date on which weather phenomena necessary for simulation occurred.

Optimal distance exponent of inverse distance method (역거리법의 최적 거리 지수)

  • Yoo, Ju-Hwan
    • Journal of Korea Water Resources Association
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    • v.51 no.5
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    • pp.451-459
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    • 2018
  • We calculated the optimal exponent values based on the hourly rainfall data observed in South Korea by treating the exponent value as a variable without fixing it as a square in the inverse distance method. For this purpose, rainfall observation stations providing the data are classified into four groups which are located at the Han river upstream, downstream, the Geum river upstream, and the Nakdong river midstream area. A total of 52 cases were analyzed for seven stations in each group. The optimal exponent value of distance was calculated in a case including one base station and four surrounding stations in a group. We applied the golden section search method to calculating this optimum values using rainfall data for 10 years (2004~2013) and verified the optimum values for the last three years (2014~2016). We compared and analyzed two results of the conventional inverse distance method and the inverse distance method in this study. The optimal values of distance exponent obtained in this study were 3.280, 1.839, 2.181, and 2.005 respectively, in the four groups, and totally mean value was 2.326. It is shown the proposed inverse distance method applying the optimal exponent is superior to the conventional inverse distance method.

Frequency and Pattern of Traffic Accidents in Different Atmospheric Phenomena (기상(氣象)에 따른 교통사고(交通事故) 발생양상(發生樣相)과 빈도(頻度))

  • Kim, Doo-Hie;Lee, Jung-Mi
    • Journal of Preventive Medicine and Public Health
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    • v.23 no.1 s.29
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    • pp.98-105
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    • 1990
  • In order to fine out the relationship between traffic accidents and atmospheric phenomena, we have analyzed 2,562 cases, one tenth of the total traffic accidents occurred in Taegu city for a year in 1988. The meteorological elements observed by Taegu Weather Bureau were used. It was divided into two largy categories : the patterns of accident as human injuries and destructions of car. When the accidents were overlapped in each other, it was considered as human injury. Human injuries were subdivided into three parts : death, severe wound and slight in, when more then two cases were overlapped, we choiced severe damage. The average number of daily traffic accidents including human injuries were lowest in winter of four seasons. The accident patterns in accordance with the seasons showed statistically significant difference. The frequency was the highest as 3.3 cases in an hour at $25.1-30.0^{\circ}C$ of atmospheric temperature, the rate of human injury showed the increase by the increased temperature. But there were not significant. Also it was the highest as 3.7 cases in less than 31% of humidity and the rate of human injury as the highest at 41-50%, but not significant. And it was the increasing tendency as wind speed increase, and the rate of human injury was the highest at 6.1-7.0 m/sec, but it was not significant. In relation to precipitation, and visibility, were the highest as 5.4 cases at 5.1-10.0 mm of rainfall, the rate of human injury was increased by the increased precipitation and showed statistically significant. And it was highest within 6 Km of visibility, but the rate of the human injury was the lowest within same distance, and also showed significance. The accidents were higher with snow on the road, but the rate of human injury was comparatively lower, but no significance.

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Very short-term rainfall prediction based on radar image learning using deep neural network (심층신경망을 이용한 레이더 영상 학습 기반 초단시간 강우예측)

  • Yoon, Seongsim;Park, Heeseong;Shin, Hongjoon
    • Journal of Korea Water Resources Association
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    • v.53 no.12
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    • pp.1159-1172
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    • 2020
  • This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

A Study on the Statistical Characteristics of Precipitation & Temperature Data of Four Cities and the Statistical Criterion of Climate Change (우리나라 4개 도시의 강수량과 기온자료의 통계적 특성과 기후변화의 통계적 기준에 관한 연구)

  • 이상훈;장영기
    • Journal of Korean Society for Atmospheric Environment
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    • v.7 no.3
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    • pp.180-188
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    • 1991
  • 기후변화를 나타내는 연구 결과들은 기온이나 강수량을 대상으로 하여 두 기간 평균치의 비교, 5년 이동평균치의 圖示, 회귀분석 등의 방법들을 사용하여 발표되지만 대부분의 경우 밑바탕이 되는 모집단의 통계적 특성을 엄격히 검토하지 않는 정성적인 분석인 경우가 많다. 서울, 부산, 인천, 목포 등 4개 지점의 80년 동안의 연강수량과 연평균기온자료를 분석한 결과 기온은 정규분포를 나타내므로 전통적인 t-검정과 회귀분석을 적용할 수 있다. t-검정 결과 두 기간(1920 $sim$ 1949, 1961 ~ 1990)은 연평균기온에서 0.3$^{\circ}$C에서 $0.8^{\circ}$C의 의의있는 차이를 보였다. 최근 30년의 연평균기온자료를 회귀분석한 결과 1년에 $0.02^{\circ}$C의 증가경향을 나타내었다. 연강수량은 정적인 왜곡도를 보이므로 정규분포를 가정하는 母數的 통계분석을 적용해서는 안되며 비모수적 통계분석법을 적용해야 한다. 연강수량의 분석에는 t-검정에 상응하는 Mann-Whitney 검정을 적용해 본 결과 두 기간(1920 ~ 1949, 1961 ~ 1990)의 평균은 통계적으로 의의있는 차이가 없었다. 회귀분석에 상응하는 Mann's 검정과 이 연구에서 새로이 제안된 Median Slope Change Estimator를 적용해 본 결과 역시 통계적으로 의의있는 변화가 없었다. Median Slope Change Estimator는 비모수적 통계치로서 회귀분석의 기울기에 해당하는 연변화를 나타낼 수 있는데 분석하려는 자료의 정규분포성을 요구하지 않으며 異常點(outlier) 영향에 덜 민감하다는 장점이 있으므로 주목하여 연구할 만한 가치가 있다.^{\circ}$~40$^{\circ}$ 구간에서는 ${\sigma}_c$와 I$_{sa}$, 40$^{\circ}$~90$^{\circ}$ 구간에서는 ${\sigma}_c$와 I$_{sd}$가 각각 양호한 상관관계를 보여준다. 또한 상관비(K=${\sigma}_c$/I$_s$)는 약 13정도로서 일반적으로 적용되는 비, 24와 상당한 차이가 있다. 이러한 현상은 호상편마암의 구조적 및 역학적 이방성 특성으로 인한 결과라고 판단된다. 한편 맥암류에서 K가 약 23정도로서 일반적인 비 24에 상당히 접근한다. 따라서, 이방성 구조가 뚜렷한 암석에서 상관비 24는 항상 적용할 수는 없으며 일축압축강도시험과 병행 실시하여 적용하는 것이 바람직하다.다. 한편, 감작감염후 77일과 도전감염후 7일의 시점에 있어서 sRBC에 대한 면역능에 미치는 영향은 전자의 양상과 비슷하였는데 대조에 비하여 지연형 과민반응과 로제트 형성능이 현저하게 저하되었다. 이 시점에 있어서의 유충회수율은 대조가 10.5% 이었는데 비하여 8.3%이었다.e also compared for the cases of Kim et al, which again gives promising agreement.면적 306~453$\textrm{cm}^2$, 유색계의 경우 수당면적 340~453$\textrm{cm}^2$ 일 때 경제능력을 제대로 발휘할 수 있고 경제성이 있는 것으로 나타났다. 첨가구가 높은 경향이 있었다8.4%. 79.7% 그리고 80.2%였다.

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Fog Detection over the Korean Peninsula Derived from Satellite Observations of Polar-orbit (MODIS) and Geostationary (GOES-9) (극궤도(MODIS) 및 정지궤도(GOES-9) 위성 관측을 이용한 한반도에서의 안개 탐지)

  • Yoo, Jung-Moon;Yun, Mi-Young;Jeong, Myeong-Jae;Ahn, Myoung-Hwan
    • Journal of the Korean earth science society
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    • v.27 no.4
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    • pp.450-463
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    • 2006
  • Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.