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Risk-Based Trend Detection for Clima...

Rosner, Ana.

Risk-Based Trend Detection for Climate Change Adaptation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Risk-Based Trend Detection for Climate Change Adaptation.
Author:	Rosner, Ana.
Description:	57 p.
Notes:	Source: Masters Abstracts International, Volume: 50-06, page: 4124.
Notes:	Advisers: Richard M. Vogel; Paul. H. Kirshen; Elena N. Naumova.
Contained By:	Masters Abstracts International50-06.
Subject:	Statistics.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1512956
ISBN:	9781267414175

Risk-Based Trend Detection for Climate Change Adaptation.
Rosner, Ana.

Risk-Based Trend Detection for Climate Change Adaptation. - 57 p.

Source: Masters Abstracts International, Volume: 50-06, page: 4124.

Thesis (M.S.)--Tufts University, 2012.

The usual procedure for detecting climate change impacts from historic records chooses statistical criteria (usually alpha=0.05) to minimize the probability of Type I error, claiming a trend exists where it does not. However, it ignores Type II error, failing to detect an increasing trend in storm surges.

ISBN: 9781267414175Subjects--Topical Terms:

182057
Statistics.

Risk-Based Trend Detection for Climate Change Adaptation.
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100 1 $a Rosner, Ana. $3 603365
245 1 0 $a Risk-Based Trend Detection for Climate Change Adaptation.
300 $a 57 p.
500 $a Source: Masters Abstracts International, Volume: 50-06, page: 4124.
500 $a Advisers: Richard M. Vogel; Paul. H. Kirshen; Elena N. Naumova.
502 $a Thesis (M.S.)--Tufts University, 2012.
520 $a The usual procedure for detecting climate change impacts from historic records chooses statistical criteria (usually alpha=0.05) to minimize the probability of Type I error, claiming a trend exists where it does not. However, it ignores Type II error, failing to detect an increasing trend in storm surges.
520 $a For coastal climate change adaptation, the physical implication of a Type I error is wasted money on unneeded infrastructure. Repercussions of a Type II error, however, are major storm damages and flooding due to inadequate protection. Decision-makers are poorly served by statistical methods that do not carefully consider this type of error.
520 $a We propose a new method that combines hypothesis testing, Risk-Based Decision Making, and decision analysis, to evaluate adaptations for a possibly costly but highly uncertain increase in storms. We propose a new metric, Expected Regret, that integrates the statistical certainty and the economic impacts of a trend. This method gives needed attention to the risks of under-preparing; conveys the statistical uncertainty in a physically meaningful way; and addresses the question, "Should we adapt now, despite the uncertainty?"
590 $a School code: 0234.
650 4 $a Statistics. $3 182057
650 4 $a Water Resource Management. $3 492849
650 4 $a Engineering, Environmental. $3 212478
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710 2 $a Tufts University. $b Civil Engineering. $3 603366
773 0 $t Masters Abstracts International $g 50-06.
790 1 0 $a Vogel, Richard M., $e advisor
790 1 0 $a Kirshen, Paul. H., $e advisor
790 1 0 $a Naumova, Elena N., $e advisor
790 1 0 $a Kirshen, Paul H. $e committee member
790 1 0 $a Naumova, Elena N. $e committee member
790 $a 0234
791 $a M.S.
792 $a 2012
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