• Title/Summary/Keyword: maximum consecutive dry days

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A Study on Variability of Consecutive Dry Days by Riverbasin in South Korea (한국의 유역별 연속건조일의 변화에 관한 연구)

  • Lee, Seung-Ho;Kim, Eun-Kyung;Heo, In-Hye
    • Journal of the Korean association of regional geographers
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    • v.17 no.6
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    • pp.666-678
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    • 2011
  • This study is aimed to examine the variability of consecutive dry days in South Korea. The country is divided into six basins including Han river, Nakdong river, Geum river. Seomjin Yeongsan river, Eastern Coast area and Island area, and three extreme precipitation indices-related to dry days are analyzed at sixty weather stations. Trends of max number of consecutive dry days were unstable during 1973~2010. Variability range of max number of consecutive dry days trends in Nakdong and Seomjin Yeongsan river was larger than that in Han and Geum river. Recently, the range in Nakdong and Seomjin Yeongsan river was bigger and bigger. Maximum dry spell was observed in autumn and winter in most of riverbasins. Especially, Maximum dry spell in winter was more frequent than in other seasons in Nakdong river. Variability range of persistence dry spells was smaller than that of max number of consecutive dry days. However, the increasing trends of the Geum river and the Seomjin Yeongsan river are statistically significant in recent. In Nakdong river, difference between persistence dry spell average and persistence dry spell median was larger than any other riverbasin. It means that there is strong possibility of occurrence of long term consecutive dry days in Nakdong river.

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Trends on Temperature and Precipitation Extreme Events in Korea (한국의 극한 기온 및 강수 사상의 변화 경향에 관한 연구)

  • Choi, Young-Eun
    • Journal of the Korean Geographical Society
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    • v.39 no.5 s.104
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    • pp.711-721
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    • 2004
  • The aim of this study is to clarify whether frequency and/or severity of extreme climate events have changed significantly in Korea during recent years. Using the best available daily data, spatial and temporal aspects of ten climate change indicators are investigated on an annual and seasonal basis for the periods of 1954-1999. A systematic increase in the $90^{th}$ percentile of daily minimum temperatures at most of the analyzed areas has been observed. This increase is accompanied by a similar reduction in the number of frost days and a significant lengthening of the thermal growing season. Although the intra-annual extreme temperature range is based on only two observations, it provides a very robust and significant measure of declining extreme temperature variability. The five precipitation-related indicators show no distinct changing patterns for spatial and temporal distribution except for the regional series of maximum consecutive dry days. Interestingly, the regional series of consecutive dry days have increased significantly while the daily rainfall intensity index and the fraction of annual total precipitation due to events exceeding the $95^{th}$ percentile for 1901-1990 normals have insignificantly increased.

Rainfall Trend Detection Using Non Parametric Test in the Yom River Basin, Thailand

  • Mama, Ruetaitip;Bidorn, Butsawan;Namsai, Matharit;Jung, Kwansue
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.424-424
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    • 2017
  • Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

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Stochastic Structure of Daily Rainfall in Korea (한국 일강우의 추계학적 구조)

  • 이근후
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.31 no.4
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    • pp.72-80
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    • 1989
  • Various analyses were made to investigate the stochastic structure of the daily rainfall in Korea. Records of daily rainfall amounts from 1951 to 1984 at Chinju Metesrological Station were used for this study. Obtained results are as follows : 1. Time series of the daily rainfall at Chinju were positively, serially correlated for the lag as large as one day. 2. Rainfall events, defined as a sequence of consecutive wet days separated by one or more dry days, showed a seasonal variation in the occurrence frequency. 3. The marginal distribution of event characteristics of each month showed significant dif- ferences each other. Events occurred in summer had longer duration and higher magnitude with higher intensity than those of events occurred in winter. 4. There were significant positive correlations among four event characteristics ; dura- tion, magnitude, average intensity, and maximum intensity. 5. Correlations among the daily rainfall amounts within an event were not significant in general. 6. There were no consistant significancy in identity or difference between the distribu- tions of daily rainfall amounts for different days within events. 7. Above mentioned characteristics of daily rainfall time series must be considered in building a stochastic model of daily rainfall.

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Development of a Stochastic Precipitation Generation Model for Generating Multi-site Daily Precipitation (다지점 일강수 모의를 위한 추계학적 강수모의모형의 구축)

  • Jeong, Dae-Il
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.5B
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    • pp.397-408
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    • 2009
  • In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.