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Statistical Predict...
Statistical Prediction of Global Sea Level From Global Temperature
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- Bolin, David, 1983 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology
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- Guttorp, P. (author)
- University of Washington
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- Januzzi, A. (author)
- Seattle Public Schools
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- Jones, D. (author)
- House of Representatives
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Novak, M. (author)
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- Podschwit, H. (author)
- University of Washington
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- Richardson, L. (author)
- Carnegie Mellon University (CMU)
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- Särkkä, Aila, 1962 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,Chalmers tekniska högskola,Chalmers University of Technology,University of Gothenburg
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- Sowder, C. (author)
- University of Washington
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- Zimmerman, A. (author)
- University of Washington
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(creator_code:org_t)
- 2015
- 2015
- English.
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In: Statistica Sinica. - : Statistica Sinica (Institute of Statistical Science). - 1017-0405. ; 25:1, s. 351-367
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Abstract
Subject headings
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- Sea level rise is a threat to many coastal communities, and projection of future sea level for different climate change scenarios is an important societal task In this paper, we first construct a time series regression model to predict global sea level from global temperature. The model is fitted to two sea level data sets (with and without corrections for reservoir storage of water) and three temperature data sets. The effect of smoothing before regression is also studied. Finally, we apply a novel methodology to develop confidence bands for the projected sea level, simultaneously for 2000-2100, under different scenarios, using temperature projections from the latest climate modeling experiment. The main finding is that different methods for sea level projection, which appear to disagree, have confidence intervals that overlap, when taking into account the different sources of variability in the analyses.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- ARMA time series models
- climate projections
- singular spectrum smoothing
- ARMA time series models
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Bolin, David, 19 ...
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Guttorp, P.
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Januzzi, A.
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Jones, D.
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Novak, M.
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Podschwit, H.
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show more...
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Richardson, L.
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Särkkä, Aila, 19 ...
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Sowder, C.
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Zimmerman, A.
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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Mathematics
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and Probability Theo ...
- Articles in the publication
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Statistica Sinic ...
- By the university
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University of Gothenburg
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Chalmers University of Technology