An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

Lazoglou, Georgia; Αnagnostopoulou, Christina

doi:10.3390/ecas2017-04132

Cited by 25 publications

(22 citation statements)

References 20 publications

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“…Application of extreme value theory to evaluate some of the most important statistical methods that are used for occurrence anaysis of the extreme precipitation (rainfall) event has been discussed in the work of [2,3,4,5]. Extreme value theory is applied on ten station data located in the Mediterranean region using two main fundamental approaches, block-maxima and Peak over threshold and three commonly used methods for the calculation of the extreme distributions parameters(Maximum Likelihood, L Moment and Bayesian) are analysed and compared.…”

Section: Original Research Articlementioning

confidence: 99%

Bayesian Modelling of Extreme Rainfall Data of Some Selected Locations in Nigeria

Akanbi

2020

JSRR

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Climate change occurs when there is rise in average surface temperature on earth, which is mostly due to the burning of fossil fuels usually by human activities. It has been known to contribute greatly to the occurrence of extreme storms and rainfall, this trend continues as the effect of climate change becomes more pronounced. Therefore, this study modelled the extreme rainfall data of three locations (Calabar, Ikeja, Edo) in Nigeria. The block maxima method was used to pick out the maximum rainfall data in each year to form annual maxima data set. The parameters [location, scale, shape] were estimated using both the Classical and Bayesian methods. The result shows that the Bayesian Informative approach is a very good procedure in modelling the Nigerian Extreme Rainfall data.

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Section: Original Research Articlementioning

confidence: 99%

Bayesian Modelling of Extreme Rainfall Data of Some Selected Locations in Nigeria

Akanbi

2020

JSRR

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“…This distribution is one of the most widely used. Countries like the United States (especially in the eastern portion), the United Kingdom, Australia, Bangladesh, Canada, South Africa, and New Zealand have adopted it in some areas [46][47][48][49][50][51].…”

Section: Generalized Extreme Value Distributionmentioning

confidence: 99%

Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region

González-Álvarez¹,

Viloria-Marimón

Coronado-Hernández

et al. 2019

Water

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In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values.

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“…The R package "extRemes" was used for the computations. Both EVDs are commonly applied to the analysis of extreme precipitation (e.g., Lazoglou and Anagnostopoulou, 2017). GEV includes estimates of shape, location, and slope, and GP shape, location, and threshold.…”

Section: Calculating Precipitation Extremesmentioning

confidence: 99%

Quantitative scenarios for future hydrologic extremes in the U.S. Southern Great Plains

Mullens

McPherson

2019

Intl Journal of Climatology

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Decision‐makers using climate projection information are often faced with the problem of data breadth, complexity, and uncertainty, which complicates the translation of climate science products in addressing management challenges. Recently, the concept of climate scenario planning attempts to simplify climate information by developing a series of plausible future “storylines.” In some cases, however, these storylines lack quantitative detail on extremes that may be useful to decision‐makers. Here, we analyse a large suite of statistically downscaled climate projections from two methods to develop quantitative projections for hydrologic extremes (heavy precipitation and drought) across Oklahoma and Texas in the United States. Downscaled projections are grouped into four specific temperature/precipitation scenarios, including “Warm/Wet,” “Hot/Dry,” “Central Tendency,” and the full multi‐model ensemble average. The region is split into three sub‐domains spanning the region's west–east precipitation gradient, and projections are examined throughout the mid‐ and late‐21st century, using two emissions scenarios (“mid‐range” and “high”). Most scenarios project increased frequency and duration of moderate or greater drought across the whole domain, with the high‐emissions Hot/Dry projections showing the most severe examples. The Warm/Wet scenario also increases the frequency of dry months, particularly in the Southern High Plains, but does not discernably alter duration, and retains a similar frequency of pluvial (wet) periods. The mid‐range projections generally retain similar evolutions among scenarios, but they reduce drought intensity and project no change in drought/pluvial frequency with the Warm/Wet scenario. Notably, the occurrence of intense precipitation increases across all scenarios and emissions categories and does not significantly differ between any of the scenarios, including Hot/Dry versus Warm/Wet. Some observed differences in extreme precipitation magnitudes between the two downscaled data sets are briefly discussed.

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An Overview of Statistical Methods for Studying the Extreme Rainfalls in Mediterranean

Cited by 25 publications

References 20 publications

Bayesian Modelling of Extreme Rainfall Data of Some Selected Locations in Nigeria

Bayesian Modelling of Extreme Rainfall Data of Some Selected Locations in Nigeria

Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region

Quantitative scenarios for future hydrologic extremes in the U.S. Southern Great Plains

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