scholarly journals Review: Methods for the estimation of extreme rainfall events

Water SA ◽  
2019 ◽  
Vol 45 (3 July) ◽  
Author(s):  
KA Johnson ◽  
JC Smithers

The estimation of design rainfalls is necessary to estimate the exceedance probabilities of extreme floods required to design hydraulic structures and to quantify the risk of failure of these structures. New approaches to estimating extreme rainfall events are being developed internationally. This paper reviews methods for estimating design rainfalls, particularly extreme events, in South Africa and internationally, and highlights the need to update methods used for estimating extreme rainfall events in South Africa as a platform for future research.

Author(s):  
Carlo Montes ◽  
Nachiketa Acharya ◽  
Quamrul Hassan

This work focuses on the analysis of the performance of satellite-based precipitation products for monitoring extreme rainfall events. Five precipitation products are inter-compared and evaluated in capturing indices of extreme rainfall events during 1998-2019 considering four indices of extreme rainfall. Satellite products show a variable performance, which in general indicates that the occurrence and amount of rainfall of extreme events can be both underestimated or overestimated by the datasets in a systematic way throughout the country. Also, products that consider the use of ground truth data have the best performance.


2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa

Abstract East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard; the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended Fluctuation Analysis (DFA) is used to show the future development of extreme events. Pearson’s correlation analysis is performed to show the relationship of extreme events between different rainfall zones and their association with El Niño -Southern Oscillation (ENSO and Indian Ocean dipole (IOD) IOD-DMI indices. Results revealed that the consecutive wet day's index (CWD) was decreasing trend in 72% of the stations analyzed, moreover consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall days (R25mm) index, 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events in the regions; and between rainfall extreme indices with the atmospheric teleconnection indices (Dipole Mode Index-DMI and Nino 3.4) (r = -0.1 to r = 0.35). Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p. In light of the highly variable trends of extremes events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, stored and used during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts is highly advised.


Author(s):  
Vinicius Alexandre Sikora de Souza ◽  
Marcos Leando Alves Nunes ◽  
Sandra Ferronatto Francener ◽  
Ana Lúcia Denardin da Rosa

<p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Este estudo objetivou estimar a função Intensidade-Duração-Frequência (IDF) de eventos pluviométricos extremos a partir dos dados de precipitação das estações pluviométricas instaladas no estado de Rondônia, de modo que posteriormente tais informações possam ser utilizadas no dimensionamento de obras hidráulicas. Utilizou-se 41 estações pluviométricas com séries históricas acima de 10 anos, disponibilizadas pela Agência Nacional de Águas (ANA). Essas séries passaram inicialmente pelo teste de aderência Kolmogorov-Smirnov (KS), a fim de verificar o ajuste das mesmas as </span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">distribuições: Normal, Log-Normal, Exponencial, Gama, Gumbel, Weibull e Logística</span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">. O trabalho denotou que o teste de aderência </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Kolmogorov-Smirnov de forma geral forneceu uma expressiva aceitação na maioria das distribuições estatística testadas.</span></p><p> </p><p align="center"><strong><em>Analysis of fitness for extreme rainfall events in western amazon in static models: state Rondônia</em></strong></p><p> </p><p><strong>ABSTRACT: </strong>This study aimed to estimate the Intensity - Duration - Frequency (IDF) function extreme rainfall events from the data of precipitation of rainfall stations located in the State of Rondônia, so that such information can be later used in hydraulic structures. We used 41 rainfall stations with historical series over 10 years, provided by the National Water Agency (ANA). These series originally started by adherence Kolmogorov -Smirnov (KS) in order to check the fit of the same distributions: Normal, Log- Normal, Exponential, Gamma, Gumbel, Weibull and Logistics. Work denoted that the Kolmogorov - Smirnov test of adherence generally provided a significant acceptance in most of the tested statistical distributions.<strong></strong></p><p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"><br /></span></p>


Author(s):  
Douglas Schaefer

Variations in temperature and precipitation are both components of climate variability. Based on coral growth rates measured near Puerto Rico, the Caribbean was 2–3ºC cooler during the “Little Ice Age” during the seventeenth century (Winter et al. 2000). At the millennial scale, temperature variations in tropical regions have been inferred to have substantial biological effects (such as speciation and extinction), but not at the multidecadal timescales considered here. My focus is on precipitation variability in particular, because climate models examining effects of increased greenhouse gases suggest greater changes in precipitation than in temperature patterns in tropical regions. Some correspondence between both the El Niño–Southern Oscillation (ENSO) and the Northern Atlantic Oscillation (NAO) and average temperatures and total annual precipitation have been reported for the LTER site at Luquillo (Greenland 1999; Greenland and Kittel 2002), but those studies did not refer to extreme events. Based on climate records for Puerto Rico since 1914, Malmgren et al. (1997) found small increases in air temperature during El Niño years and somewhat greater total rainfall during the positive phase of the NAO. Similar to ENSO, the NAO index is characterized by differences in sea-level atmospheric pressure, in this case based on measurements in Iceland and Portugal (Walker and Bliss 1932). Its effects on climate have largely been described in terms of temperature and precipitation anomalies in countries bordering the North Atlantic (e.g., Hurrell 1995). Puerto Rico is in the North Atlantic hurricane zone, and hurricanes clearly play a major role in precipitation variability. The association between extreme rainfall events and hurricanes is discussed in detail in this chapter. I examine the degree to which extreme rainfall events are associated with hurricanes and other tropical storms. I discuss whether the occurrence of these extreme events has changed through time in Puerto Rico or can be linked to the recurrent patterns of the ENSO or the NAO. I examine the 25-year daily precipitation record for the Luquillo LTER site, the 90-year monthly record from the nearest site to Luquillo with such a long record, Fajardo, and those of the two other Puerto Rico stations with the longest daily precipitation records, Manati and Mayaguez (figure 8.1).


2016 ◽  
Vol 29 (16) ◽  
pp. 5915-5934 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
S. J. Mason ◽  
A. W. Robertson

Abstract Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December–February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross–time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden–Julian oscillation, and combinations of both). Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur.


2010 ◽  
Vol 11 (4) ◽  
pp. 950-965 ◽  
Author(s):  
Guobin Fu ◽  
Neil R. Viney ◽  
Stephen P. Charles ◽  
Jianrong Liu

Abstract The temporal variability of the frequency of short-duration extreme precipitation events in Australia for the period 1910–2006 is examined using the high-quality rainfall dataset identified by the Bureau of Meteorology, Australia, for 189 stations. Extreme events are defined by duration and recurrence interval: 1, 5, 10, and 30 days, and 1, 5, and 20 yr, respectively. The results indicate that temporal variations of the extreme precipitation index (EPI) for various durations and recurrence intervals in the last 100 yr, except for the low frequencies before 1918, have experienced three U-shaped cycles: 1918–53, 1953–74, and 1974–2006. Seasonal results indicate that about two-thirds of 1-day, 1-yr recurrence interval extreme events occur from December to March. Time series of anomalies of the regional EPIs for four regions indicate that northeast Australia and southeast Australia have almost the same temporal variation as the national anomalies, South Australia experienced a negative anomaly of extreme rainfall events in the mid-1950s, and southwest Western Australia (SWWA) experienced relatively small temporal variation. The relationships between extreme rainfall events and the Southern Oscillation index (SOI) and the interdecadal Pacific oscillation (IPO) indicate that extreme rainfall events in Australia have a strong relationship with both, especially during La Niña years and after 1942.


2007 ◽  
Vol 135 (3) ◽  
pp. 1128-1150 ◽  
Author(s):  
A. T. Singleton ◽  
C. J. C. Reason

Abstract Investigations of extreme rainfall events in the southern African region are limited by the paucity of the observational network. Furthermore, the lack of full radar coverage for South Africa makes quantitative precipitation estimation difficult. Therefore, numerical modeling represents the most effective method for improving the understanding of the mechanisms that contribute to extreme rainfall events in this region with the caveat that accurate validation of model simulations is hampered by the limited observations in the region. This paper describes an intense cutoff low event over South Africa that led to record rainfall and flash flooding along the south coast of the country and adjoining hinterland. Analyses from the Global Forecast System model showed that the cutoff aloft was accompanied by a strong low-level jet (LLJ) impinging onto the south coast where rainfall was heaviest, and that lapse rates were steep in the lower troposphere. Simulations of the event were carried out using a numerical model [i.e., the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)], which showed that severe convection occurred over the ocean on the right-hand side of the LLJ, and at its leading edge where it impinged on the coastal topography. This topography was also very important in providing additional forcing for the ascent of moist air. A factor separation technique was used to show that surface heat fluxes from the warm sea surface temperature (SST) of the Agulhas Current were important in enhancing low-level cyclogenesis, and that topography was important in maintaining the position of the low-level coastal depression, which led to favorable conditions for rainfall remaining in the same area for an extended period of time. It is suggested that improved representation of the tight topographic and SST gradients of the southern African region in NWP models or postprocessing systems would help to provide more accurate forecasts of the amount and location of heavy precipitation during cutoff low events where surface forcing is important.


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