• Title/Summary/Keyword: Frequency based precipitation

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Regional Frequency Analysis for Future Precipitation from RCP Scenarios (대표농도경로 시나리오에 의한 미래 강수량의 지역빈도해석)

  • Kim, Duck Hwan;Hong, Seung Jin;Choi, Chang Hyun;Han, Dae Gun;Lee, So Jong;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.17 no.1
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    • pp.80-90
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    • 2015
  • Variability of precipitation pattern and intensity are increasing due to the urbanization and industrialization which induce increasing impervious area and the climate change. Therefore, more severe urban inundation and flood damage will be occurred by localized heavy precipitation event in the future. In this study, we analyze the future frequency based precipitation under climate change based on the regional frequency analysis. The observed precipitation data from 58 stations provided by Korea Meteorological Administration(KMA) are collected and the data period is more than 30 years. Then the frequency based precipitation for the observed data by regional frequency analysis are estimated. In order to remove the bias from the simulated precipitation by RCP scenarios, the quantile mapping method and outlier test are used. The regional frequency analysis using L-moment method(Hosking and Wallis, 1997) is performed and the future frequency based precipitation for 80, 100, and 200 years of return period are estimated. As a result, future frequency based precipitation in South Korea will be increased by 25 to 27 percent. Especially the result for Jeju Island shows that the increasing rate will be higher than other areas. Severe heavy precipitation could be more and more frequently occurred in the future due to the climate change and the runoff characteristics will be also changed by urbanization, industrialization, and climate change. Therefore, we need prepare flood prevention measures for our flood safety in the future.

The ETCCDI and Frequency Analysis using RCP Scenarios (RCP 시나리오를 고려한 극치통계분석 및 빈도해석)

  • Kim, Duck Hwan;Kim, Yon Soo;Hong, Seung Jin;Ly, Sidoeun;Jung, Younghun;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.15 no.4
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    • pp.595-607
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    • 2013
  • In this study we estimated ETCCDI and frequency based precipitation using observed precipitation and precipitation from Representative Concentration Pathway(RCP) scenarios for 58 weather stations which have the recorded data more than 30 years. We tried to eliminate the bias by Quantile Mapping and tested for outliers of simulated data under climate change scenario. Then we estimated ETCCDI related to precipitation and frequency based precipitation for the future. In addition to this study examined the changes of frequency based precipitation for the future target periods. According to the result, dry days will be increased in Korean Peninsula in the 2090s. Also it showed that the number of heavy precipitation day more than 80mm/day tends to be increased in 3~7% in the future. The precipitation of 24-hour duration under climate change will be increased by 17.7% for 80-year frequency, 18.2% for 100-year frequency and 19.6% for 200-year frequency in 2090s. In the 21st century, the damage caused by natural disasters is expected to be increased due to increase of precipitation and the change of runoff characteristics under climate change. Therefore, the proposed ETCCDI and precipitation frequency under climate change are expected to be used for the future natural disaster plan.

Design of Optimized Type-2 Fuzzy RBFNN Echo Pattern Classifier Using Meterological Radar Data (기상레이더를 이용한 최적화된 Type-2 퍼지 RBFNN 에코 패턴분류기 설계)

  • Song, Chan-Seok;Lee, Seung-Chul;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.6
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    • pp.922-934
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    • 2015
  • In this paper, The classification between precipitation echo(PRE) and non-precipitation echo(N-PRE) (including ground echo and clear echo) is carried out from weather radar data using neuro-fuzzy algorithm. In order to classify between PRE and N-PRE, Input variables are built up through characteristic analysis of radar data. First, the event classifier as the first classification step is designed to classify precipitation event and non-precipitation event using input variables of RBFNNs such as DZ, DZ of Frequency(DZ_FR), SDZ, SDZ of Frequency(SDZ_FR), VGZ, VGZ of Frequency(VGZ_FR). After the event classification, in the precipitation event including non-precipitation echo, the non-precipitation echo is completely removed by the echo classifier of the second classifier step that is built as Type-2 FCM based RBFNNs. Also, parameters of classification system are acquired for effective performance using PSO(Particle Swarm Optimization). The performance results of the proposed echo classifier are compared with CZ. In the sequel, the proposed model architectures which use event classifier as well as the echo classifier of Interval Type-2 FCM based RBFNN show the superiority of output performance when compared with the conventional echo classifier based on RBFNN.

Quantifying the 2022 Extreme Drought Using Global Grid-Based Satellite Rainfall Products (전지구 강수관측위성 기반 격자형 강우자료를 활용한 2022년 국내 가뭄 분석)

  • Mun, Young-Sik;Nam, Won-Ho;Jeon, Min-Gi;Lee, Kwang-Ya;Do, Jong-Won;Isaya Kisekka
    • Journal of The Korean Society of Agricultural Engineers
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    • v.66 no.4
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    • pp.41-50
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    • 2024
  • Precipitation is an important component of the hydrological cycle and a key input parameter for many applications in hydrology, climatology, meteorology, and weather forecasting research. Grid-based satellite rainfall products with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions. Therefore, this study aims to evaluate the commonly used new global grid-based satellite rainfall product, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), using data collected at different spatial and temporal scales. Additionally, in this study, grid-based CHIRPS satellite precipitation data were used to evaluate the 2022 extreme drought. CHIRPS provides high-resolution precipitation data at 5 km and offers reliable global data through the correction of ground-based observations. A frequency analysis was performed to determine the precipitation deficit in 2022. As a result of comparing droughts in 2015, 2017, and 2022, it was found that May 2022 had a drought frequency of more than 500 years. The 1-month SPI in May 2022 indicated a severe drought with an average value of -1.8, while the 3-month SPI showed a moderate drought with an average value of 0.6. The extreme drought experienced in South Korea in 2022 was evident in the 1-month SPI. Both CHIRPS precipitation data and observations from weather stations depicted similar trends. Based on these results, it is concluded that CHIRPS can be used as fundamental data for drought evaluation and monitoring in unmeasured areas of precipitation.

Assessment of the Meteorological Characteristics and Statistical Drought Frequency for the Extreme 2017 Spring Drought Event Across South Korea (2017년 극심한 봄 가뭄의 기상학적 특성 및 통계학적 가뭄빈도해석)

  • Bang, Na-Kyoung;Nam, Won-Ho;Hong, Eun-Mi;Michael, J. Hayes;Mark, D. Svoboda
    • Journal of The Korean Society of Agricultural Engineers
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    • v.60 no.4
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    • pp.37-48
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    • 2018
  • The extreme 2017 spring drought affected a large portion of central and western South Korea, and was one of the most climatologically driest spring seasons over the 1961-2016 period of record. This drought was characterized by exceptionally low precipitation, with total precipitation from January to June being 50% lower than the mean normal precipitation (1981-2010) over most of western South Korea. In this study, for the quantitative drought impact analysis, the widely-used Standardized Precipitation Index (SPI) and the statistical drought frequency are compared with observed meteorological characteristics and anomalies. According to the drought frequency analysis of monthly cumulative precipitation during January and May in 2017, Gyeonggi-do, Chungcheong-do, and Jeollanam-do areas showed more than drought frequency over 100 years. Gyeongsangnam-do area showed more than drought frequency over 200 years based on annual precipitation in 2017. The South Korean government (Ministry of Agriculture, Food and Rural Affairs (MAFRA) and Korea Rural Community Corporation (KRC)) have been operating a government-level drought monitoring system since 2016. Results from this study can be used to improve the drought monitoring applications of future drought events, as well as drought planning and preparedness in South Korea.

Investigating Changes over Time of Precipitation Indicators (강수지표의 시간에 따른 변화 조사)

  • Han, Bong-Koo;Chung, Eun-Sung;Lee, Bo-Ram;Sung, Jang Hyun
    • Journal of Wetlands Research
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    • v.15 no.2
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    • pp.233-250
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    • 2013
  • Gradually or radically change how the characteristics of the climate characteristic using change point analysis for the precipitation indicators were investigated. Significantly the amount, extreme and frequency were separated by precipitation indicators, each indicator RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes) and RIF(Rainfall Index for Frequency) was defined. Bayesian Change Point was applied to investigate changing over time of precipitation indicators calculated. As the result of analysis, precipitation indicators in South Korea was found to recently increase all indicators except for the annual precipitation days and 200-yr precipitation. RIA revealed that there was a very clear point of significance for the change in Ulleungdo, Relatively significant results for RIE were identified in Gumi, Jecheon and Seogwipo. Also, since the 1990s, an increase in the number of variation points, and the horizontal width of the fluctuation point was being relatively wider. Based on these results, rethink the precipitation on the assumption of stationarity was judged necessary.

Analysis of Spatial-temporal Variability and Trends of Extreme Precipitation Indices over Chungcheong Province, South Korea (충청지역 극한강우지수의 시공간적 경향과 변동성 분석)

  • Bashir, Adelodun;Golden, Odey;Seulgi, Lee;Kyung Sook, Choi
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.6
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    • pp.101-112
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    • 2022
  • Extreme precipitation events have recently become a leading cause of disasters. Thus, investigating the variability and trends of extreme precipitation is crucial to mitigate the increasing impact of such events. Spatial distribution and temporal trends in annual precipitation and four extreme precipitation indices of duration (CWD), frequency (R10 mm), intensity (Rx1day), and percentile-based threshold (R95pTOT) were analyzed using the daily precipitation data of 10 observation stations in Chungcheong province during 1974-2020. The precipitation at all observation stations, except the Boryeong station, showed nonsignificant increasing trends at 95% confidence level (CL) and increasing magnitudes from the west to east regions. The high variability in mean annual precipitation was more pronounced around the northeast and northwest regions. Similarly, there were moderate to high patterns in extreme precipitation indices around the northeast region. However, the precipitation indices of duration and frequency consistently increased from the west to east regions, while those of intensity and percentile-based threshold increased from the south to east regions. Nonsignificant increasing trends dominated in CWD, R10 mm, and Rx1day at all stations, except for R10 mm at Boeun station and Rx1day at Cheongju and Jecheon stations, which showed a significantly increasing trend. The spatial distribution of trend magnitude shows that R10 mm increased from the west to east regions. Furthermore, variations in precipitation were very strongly correlated (99% CL) with R10 mm, Rx1day, and R95pTOT at all stations, except with wR10 mm at Cheongju station, which was strongly correlated with a 95% CL.

Conversion Factor Estimates between the Rain Data per Minute and Fixed-Time-Interval (분단위 강우자료를 활용한 임의-고정시간 환산계수의 추정)

  • Moon, Young-Il;Oh, Tae-Suk;Oh, Kun-Taek;Jun, Si-Young
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.679-682
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    • 2008
  • Probability precipitation is one of the most important factor for designing the hydrology structures. Probability precipitation is calculated based on the frequency analysis on each durations of annual maximum rainfall data. For frequency analysis we need a conversion factor between the rain data per random-time interval and fixed-time-interval. In this study, the minutely precipitation data on observatory of the Meteorological Administration are used for 37 stations. Therefore, we should conversion factors between the rain data per minute and fixed-time-interval.

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Analysis of Drought Characteristics in Gyeongbuk Based on the Duration of Standard Precipitation Index

  • Ahn, Seung Seop;Park, Ki bum;Yim, Dong Hee
    • Journal of Environmental Science International
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    • v.28 no.10
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    • pp.863-872
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    • 2019
  • Using the Standard Precipitation Index (SPI), this study analyzed the drought characteristics of ten weather stations in Gyeongbuk, South Korea, that precipitation data over a period of 30 years. For the number of months that had a SPI of -1.0 or less, the drought occurrence index was calculated and a maximum shortage months, resilience and vulnerability in each weather station were analyzed. According to the analysis, in terms of vulnerability, the weather stations with acute short-term drought were Andong, Bonghwa, Moongyeong, and Gumi. The weather stations with acute medium-term drought were Daegu and Uljin. Finally the weather stations with acute long-term drought were Pohang, Youngdeok, and Youngju. In terms of severe drought frequency, the stations with relatively high frequency of mid-term droughts were Andong, Bonghwa, Daegu, Uiseong, Uljin, and Youngju. Gumi station had high frequency of short-term droughts. Pohang station had severe short-term ad long-term droughts. Youngdeok had severe droughts during all the terms. Based on the analysis results, it is inferred that the size of the drought should be evaluated depending on how serious vulnerability, resilience, and drought index are. Through proper evaluation of drought, it is possible to take systematic measures for the duration of the drought.

Downscaling Technique of Monthly GCM Using Daily Precipitation Generator (일 강수발생모형을 이용한 월 단위 GCM의 축소기법에 관한 연구)

  • Kyoung, Min Soo;Lee, Jung Ki;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.5B
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    • pp.441-452
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    • 2009
  • This paper describes the evaluation technique for climate change effect on daily precipitation frequency using daily precipitation generator that can use outputs of the climate model offered by IPCC DDC. Seoul station of KMA was selected as a study site. This study developed daily precipitation generation model based on two-state markov chain model which have transition probability, scale parameter, and shape parameter of Gamma-2 distribution. Each parameters were estimated from regression analysis between mentioned parameters and monthly total precipitation. Then the regression equations were applied for computing 4 parameters equal to monthly total precipitation downscaled by K-NN to generate daily precipitation considering climate change. A2 scenario of the BCM2 model was projected based on 20c3m(20th Century climate) scenario and difference of daily rainfall frequency was added to the observed rainfall frequency. Gumbel distribution function was used as a probability density function and parameters were estimated using probability weighted moments method for frequency analysis. As a result, there is a small decrease in 2020s and rainfall frequencies of 2050s, 2080s are little bit increased.