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Estimating extremes from global ocean and climate models: a Bayesian hierarchical model approach
Citation
Oliver, ECJ and Wotherspoon, SJ and Holbrook, NJ, Estimating extremes from global ocean and climate models: a Bayesian hierarchical model approach, Progress in Oceanography, 122 pp. 77-91. ISSN 0079-6611 (2014) [Refereed Article]
Copyright Statement
Copyright 2013 Elsevier Ltd.
DOI: doi:10.1016/j.pocean.2013.12.004
Abstract
Estimating oceanic and atmospheric extremes from global climate models is not trivial as these models
often poorly represent extreme events. However, these models do tend to capture the central climate statistics
well (e.g., the mean temperature, variances, etc.). Here, we develop a Bayesian hierarchical model
(BHM) to improve estimates of extremes from ocean and climate models. This is performed by first modeling
observed extremes using an extreme value distribution (EVD). Then, the parameters of the EVD are
modeled as a function of climate variables simulated by the ocean or atmosphere model over the same
time period as the observations. By assuming stationarity of the model parameters, we can estimate
extreme values in a projected future climate given the climate statistics of the projected climate (e.g.,
a climate model projection under a specified carbon emissions scenario). The model is demonstrated
for extreme sea surface temperatures off southeastern Australia using satellite-derived observations
and downscaled global climate model output for the 1990s and the 2060s under an A1B emissions scenario.
Using this case study we present a suite of statistics that can be used to summarize the probabilistic
results of the BHM including posterior means, 95% credible intervals, and probabilities of
exceedance. We also present a method for determining the statistical significance of the modeled changes
in extreme value statistics. Finally, we demonstrate the utility of the BHM to test the response of extreme
values to prescribed changes in climate.
Item Details
Item Type: | Refereed Article |
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Keywords: | Bayesian hierarchical model, extreme values, cliamte models |
Research Division: | Earth Sciences |
Research Group: | Oceanography |
Research Field: | Physical oceanography |
Objective Division: | Environmental Policy, Climate Change and Natural Hazards |
Objective Group: | Understanding climate change |
Objective Field: | Climate variability (excl. social impacts) |
UTAS Author: | Oliver, ECJ (Dr Eric Oliver) |
UTAS Author: | Wotherspoon, SJ (Dr Simon Wotherspoon) |
UTAS Author: | Holbrook, NJ (Professor Neil Holbrook) |
ID Code: | 88801 |
Year Published: | 2014 |
Web of Science® Times Cited: | 8 |
Deposited By: | IMAS Research and Education Centre |
Deposited On: | 2014-02-17 |
Last Modified: | 2017-11-01 |
Downloads: | 0 |
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