Sensitivity analysis of the climate of a chaotic system

This paper addresses some fundamental methodological issues concerning the sensitivity analysis of chaotic geophysical systems. We show, using the Lorenz system as an example, that a naive approach to variational ('adjoint') sensitivity analysis is of limited utility. Applied to trajectori...

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Main Authors: Lea, D, Allen, M, Haine, T
Format: Journal article
Language:English
Published: 2000
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author Lea, D
Allen, M
Haine, T
author_facet Lea, D
Allen, M
Haine, T
author_sort Lea, D
collection OXFORD
description This paper addresses some fundamental methodological issues concerning the sensitivity analysis of chaotic geophysical systems. We show, using the Lorenz system as an example, that a naive approach to variational ('adjoint') sensitivity analysis is of limited utility. Applied to trajectories which are long relative to the predictability time scales of the system, cumulative error growth means that adjoint results diverge exponentially from the 'macroscopic climate sensitivity' (that is, the sensitivity of time-averaged properties of the system to finite-amplitude perturbations). This problem occurs even for time-averaged quantities and given infinite computing resources. Alternatively, applied to very short trajectories, the adjoint provides an incorrect estimate of the sensitivity, even if averaged over large numbers of initial conditions, because a finite time scale is required for the model climate to respond fully to certain perturbations. In the Lorenz (1963) system, an intermediate time scale is found on which an ensemble of adjoint gradients can give a reasonably accurate (O(10%)) estimate of the macroscopic climate sensitivity. While this ensemble-adjoint approach is unlikely to be reliable for more complex systems, it may provide useful guidance in identifying important parameter-combinations to be explored further through direct finite-amplitude perturbations.
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spelling oxford-uuid:9d1893b2-e21c-48c3-a231-faebe638234d2022-03-27T00:40:32ZSensitivity analysis of the climate of a chaotic systemJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9d1893b2-e21c-48c3-a231-faebe638234dEnglishSymplectic Elements at Oxford2000Lea, DAllen, MHaine, TThis paper addresses some fundamental methodological issues concerning the sensitivity analysis of chaotic geophysical systems. We show, using the Lorenz system as an example, that a naive approach to variational ('adjoint') sensitivity analysis is of limited utility. Applied to trajectories which are long relative to the predictability time scales of the system, cumulative error growth means that adjoint results diverge exponentially from the 'macroscopic climate sensitivity' (that is, the sensitivity of time-averaged properties of the system to finite-amplitude perturbations). This problem occurs even for time-averaged quantities and given infinite computing resources. Alternatively, applied to very short trajectories, the adjoint provides an incorrect estimate of the sensitivity, even if averaged over large numbers of initial conditions, because a finite time scale is required for the model climate to respond fully to certain perturbations. In the Lorenz (1963) system, an intermediate time scale is found on which an ensemble of adjoint gradients can give a reasonably accurate (O(10%)) estimate of the macroscopic climate sensitivity. While this ensemble-adjoint approach is unlikely to be reliable for more complex systems, it may provide useful guidance in identifying important parameter-combinations to be explored further through direct finite-amplitude perturbations.
spellingShingle Lea, D
Allen, M
Haine, T
Sensitivity analysis of the climate of a chaotic system
title Sensitivity analysis of the climate of a chaotic system
title_full Sensitivity analysis of the climate of a chaotic system
title_fullStr Sensitivity analysis of the climate of a chaotic system
title_full_unstemmed Sensitivity analysis of the climate of a chaotic system
title_short Sensitivity analysis of the climate of a chaotic system
title_sort sensitivity analysis of the climate of a chaotic system
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