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| Titel |
An optimally tuned ensemble of the "eb_go_gs" configuration of GENIE: parameter sensitivity and bifurcations in the Atlantic overturning circulation |
| VerfasserIn |
R. Marsh, A. Sobester, E. E. Hart, K. I. C. Oliver, N. R. Edwards, S. J. Cox |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 5 ; Nr. 6, no. 5 (2013-10-21), S.1729-1744 |
| Datensatznummer |
250085004
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| Publikation (Nr.) |
 copernicus.org/gmd-6-1729-2013.pdf |
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| Zusammenfassung |
| The key physical parameters for the "eb_go_gs" configuration of version
2.7.4 of GENIE, an Earth system model of intermediate complexity (EMIC), are
tuned using a multi-objective genetic algorithm. An ensemble of 90 parameter
sets is tuned using two ocean and two atmospheric state variables as targets.
These are "Pareto-optimal", representing a range of trade-offs between the
four tuning targets. For the leading five parameter sets, simulations are
evaluated alongside a simulation with untuned "default" parameters,
comparing selected variables and diagnostics that describe the state of the
atmosphere, ocean and sea ice. Further experiments are undertaken with these
selected parameter sets to compare equilibrium climate sensitivities and
transient climate responses. The pattern of warming under doubled CO2 is
strongly shaped by changes in the Atlantic meridional overturning circulation
(AMOC), while the pattern and rate of warming under rising CO2 is closely
linked to changing sea ice extent. One of the five tuned parameter sets is
identified as marginally optimal, and the objective function (error)
landscape is further analysed in the vicinity of the tuned values of this
parameter set. "Cliffs" along some dimensions motivate closer inspection of
corresponding variations in the AMOC. This reveals that bifurcations in the
AMOC are highly sensitive to parameters that are not typically associated
with MOC stability. Specifically, the state of the AMOC is sensitive to
parameters governing the wind-driven circulation and atmospheric heat
transport. For the GENIE configuration presented here, the marginally
optimal parameter set is recommended for single simulations,
although the leading five parameter sets may be used in ensemble mode to
admit a constrained degree of parametric uncertainty in climate prediction. |
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