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Quantifying uncertainties in climate system properties using recent climate observations

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dc.contributor Forest, Chris Eliot.
dc.contributor Stone, Peter H.
dc.contributor Sokolov, Andrei P.
dc.contributor Allen, Myles R.
dc.contributor Webster, Mort David.
dc.date 2003-10-24T14:55:57Z
dc.date 2003-10-24T14:55:57Z
dc.date 2001-07
dc.date.accessioned 2013-10-09T02:31:10Z
dc.date.available 2013-10-09T02:31:10Z
dc.date.issued 2013-10-09
dc.identifier no. 78
dc.identifier http://mit.edu/globalchange/www/abstracts.html#a78
dc.identifier http://hdl.handle.net/1721.1/3567
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description We apply the optimal fingerprint detection algorithm to three independent diagnostics of the recent climate record and derive joint probability density distributions for three uncertain properties of the climate system. The three properties are climate sensitivity, the rate of heat uptake by the deep ocean, and the strength of the net aerosol forcing. Knowing the probability distribution for these properties is essential for quantifying uncertainty in projections of climate change. We briefly describe each diagnostic and indicate its role in constraining these properties. Based on the marginal probability distributions, the 5 to 95% confidence intervals are 1.4 to 7.7K for climate sensitivity and 0.30 to 0.95 W/m^2 for the net aerosol forcing using uniform priors; and 1.3 to 4.2K and 0.26 to 0.88 W/m^2 using an expert prior for climate sensitivity. The oceanic heat uptake is not so well constrained. The uncertainty in the net aerosol forcing in either case is much less than the uncertainty range usually quoted for the indirect aerosol forcing alone.
dc.description Includes bibliographical references (p. 8-11).
dc.description Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/)
dc.description Supported in part by NOAA Office of Global Programs (NA06GP0061). Supported in part by the UK Natural Environment Research Council, and by UK DETR (PECD 7/12/37).
dc.format 15 p.
dc.format 289170 bytes
dc.format application/pdf
dc.language eng
dc.publisher MIT Joint Program on the Science and Policy of Global Change
dc.relation Report no. 78
dc.rights http://mit.edu/globalchange/www/abstracts.html#a78
dc.subject QC981.8.C5 M58 no.78
dc.title Quantifying uncertainties in climate system properties using recent climate observations


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