Emerging selection bias in large-scale climate change simulations
[1] Climate change simulations are the output of enormously complicated models containing resolved and parameterized physical processes ranging in scale from microns to the size of the Earth itself. Given this complexity, the application of subjective criteria in model development is inevitable. Her...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.400.6103 2023-05-15T14:57:41+02:00 Emerging selection bias in large-scale climate change simulations Kyle L. Swanson The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.400.6103 http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.400.6103 http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf text ftciteseerx 2022-02-06T01:25:07Z [1] Climate change simulations are the output of enormously complicated models containing resolved and parameterized physical processes ranging in scale from microns to the size of the Earth itself. Given this complexity, the application of subjective criteria in model development is inevitable. Here we show one danger of the use of such criteria in the construction of these simulations, namely the apparent emergence of a selection bias between generations of these simulations. Earlier generation ensembles of model simulations are shown to possess sufficient diversity to capture recent observed shifts in both the mean surface air temperature as well as the frequency of extreme monthly mean temperature events due to climate warming. However, current generation ensembles of model simulations are statistically inconsistent with these observed shifts, despite a marked reduction in the spread among ensemble members that by itself suggests convergence towards some common solution. This convergence indicates the possibility of a selection bias based upon warming rate. It is hypothesized that this bias is driven by the desire to more accurately capture the observed recent acceleration of warming in the Arctic and corresponding decline in Arctic sea ice. However, this convergence is difficult to justify given the significant and widening discrepancy between the modeled and observed warming rates outside of the Text Arctic Climate change Sea ice Unknown Arctic |
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[1] Climate change simulations are the output of enormously complicated models containing resolved and parameterized physical processes ranging in scale from microns to the size of the Earth itself. Given this complexity, the application of subjective criteria in model development is inevitable. Here we show one danger of the use of such criteria in the construction of these simulations, namely the apparent emergence of a selection bias between generations of these simulations. Earlier generation ensembles of model simulations are shown to possess sufficient diversity to capture recent observed shifts in both the mean surface air temperature as well as the frequency of extreme monthly mean temperature events due to climate warming. However, current generation ensembles of model simulations are statistically inconsistent with these observed shifts, despite a marked reduction in the spread among ensemble members that by itself suggests convergence towards some common solution. This convergence indicates the possibility of a selection bias based upon warming rate. It is hypothesized that this bias is driven by the desire to more accurately capture the observed recent acceleration of warming in the Arctic and corresponding decline in Arctic sea ice. However, this convergence is difficult to justify given the significant and widening discrepancy between the modeled and observed warming rates outside of the |
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The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Kyle L. Swanson |
spellingShingle |
Kyle L. Swanson Emerging selection bias in large-scale climate change simulations |
author_facet |
Kyle L. Swanson |
author_sort |
Kyle L. Swanson |
title |
Emerging selection bias in large-scale climate change simulations |
title_short |
Emerging selection bias in large-scale climate change simulations |
title_full |
Emerging selection bias in large-scale climate change simulations |
title_fullStr |
Emerging selection bias in large-scale climate change simulations |
title_full_unstemmed |
Emerging selection bias in large-scale climate change simulations |
title_sort |
emerging selection bias in large-scale climate change simulations |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.400.6103 http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf |
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Arctic |
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Arctic |
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Arctic Climate change Sea ice |
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Arctic Climate change Sea ice |
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http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf |
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.400.6103 http://www.seas.harvard.edu/climate/seminars/pdfs/Swanson_GRL_2013.pdf |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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