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Statistical modeling of extreme rain...

McGill University (Canada).

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Statistical modeling of extreme rainfall processes in consideration of climate change.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical modeling of extreme rainfall processes in consideration of climate change./
Author:	Cung, Annie.
Description:	118 p.
Notes:	Source: Masters Abstracts International, Volume: 46-03, page: 1624.
Contained By:	Masters Abstracts International46-03.
Subject:	Atmospheric Sciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR32684
ISBN:	9780494326848

Statistical modeling of extreme rainfall processes in consideration of climate change.
Cung, Annie.

Statistical modeling of extreme rainfall processes in consideration of climate change. - 118 p.

Source: Masters Abstracts International, Volume: 46-03, page: 1624.

Thesis (M.Sc.)--McGill University (Canada), 2007.

Furthermore, a regional analysis was performed and homogenous regions of weather stations within Quebec were identified. A method for the estimation of missing data at ungauged sites based on regional NCMs was found to yield good estimates.

ISBN: 9780494326848Subjects--Topical Terms:

1019179
Atmospheric Sciences.

Statistical modeling of extreme rainfall processes in consideration of climate change.
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020 $a 9780494326848
035 $a (UMI)AAIMR32684
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040 $a UMI $c UMI
100 1 $a Cung, Annie. $3 1033944
245 1 0 $a Statistical modeling of extreme rainfall processes in consideration of climate change.
300 $a 118 p.
500 $a Source: Masters Abstracts International, Volume: 46-03, page: 1624.
502 $a Thesis (M.Sc.)--McGill University (Canada), 2007.
520 $a Furthermore, a regional analysis was performed and homogenous regions of weather stations within Quebec were identified. A method for the estimation of missing data at ungauged sites based on regional NCMs was found to yield good estimates.
520 $a Extreme rainfall events may have catastrophic impacts on the population and infrastructures, therefore it is essential to have accurate knowledge of extreme rainfall characteristics. Moreover, both the scientific community and policymakers have recently shown a growing interest in the potential impacts of climate change on water resources management. Indeed, changes in the intensity and frequency of occurrence of extreme rainfall events may have serious impacts. As such, it is important to understand not only the current patterns of extreme rainfalls but also how they are likely to change in the future.
520 $a The objective of the present research is therefore to find the best method for estimating accurately extreme rainfalls for the current time period and future periods in the context of climate change. The analysis of extreme rainfall data from the province of Quebec (Canada) revealed that, according to L-moment ratio diagrams, the data may be well described by the Generalized-Extreme-Value (GEV) distribution. Results also showed that a simple scaling relationship between non-central moments (NCM) and duration can be established and that a scaling method based on NCMs and scaling exponents can be used to generate accurate estimates of extreme rainfalls at Dorval station (Quebec, Canada). Other results demonstrated that the method of NCMs can accurately estimate distribution parameters and can be used to construct accurate Intensity-Duration-Frequency (IDF) curves.
520 $a In addition, the potential impacts of climate change on extreme rainfalls were assessed. Changes in the distribution of annual maximum (AM) precipitations were evaluated using simulations from two Global Climate Models (GCMs) under the A2 greenhouse gas emission scenario: the Coupled Global Climate Model version 2 (CGCM2A2) of the Canadian Centre for Climate Modelling and Analysis, and the Hadley Centre's Model version 3 (HadCM3A2). Simulations from these two models were downscaled spatially using the Statistical DownScaling Model (SDSM). A bias-correction method to adjust the downscaled AM daily precipitations for Dorval station was tested and results showed that after adjustments, the values fit the observed AM daily precipitations well. The analysis of future AM precipitations revealed that, after adjustments, AM precipitations downscaled from CGCM2A2 increase from current to future periods, while AM precipitations downscaled from HadCM3A2 show a mild decrease from current to future periods, for daily and sub-daily scales.
590 $a School code: 0781.
650 4 $a Atmospheric Sciences. $3 1019179
650 4 $a Engineering, Civil. $3 783781
690 $a 0543
690 $a 0725
710 2 $a McGill University (Canada). $3 1018122
773 0 $t Masters Abstracts International $g 46-03.
790 $a 0781
791 $a M.Sc.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR32684