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Gradient free descent: shadowing, and state estimation using limited derivative informations

Judd, Kevin, Smith, Leonard A. and Weisheimer, Antje (2004) Gradient free descent: shadowing, and state estimation using limited derivative informations. Physica D: Nonlinear Phenomena, 190 (3-4). pp. 153-166. ISSN 0167-2789

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Identification Number: 10.1016/j.physd.2003.10.011


Shadowing trajectories can play an important role in assessing the reliability of forecasting models, they can also play an important role in providing state estimates for ensemble forecasts. Gradient descent methods provide one approach for obtaining shadowing trajectories, which have been shown to have many useful properties. There remains the important question whether shadowing trajectories can be found in very high-dimensional systems, like weather and climate models. The principle impediment is the need to compute the derivative (or adjoint) of the system dynamics. In this paper we investigate gradient descent methods that use limited derivative information. We demonstrate the methods with an application to a moderately high-dimensional system using no derivative information at all.

Item Type: Article
Official URL:
Additional Information: © Elvesier 2003
Divisions: Centre for Analysis of Time Series
Subjects: Q Science > QC Physics
Sets: Research centres and groups > Centre for the Analysis of Time Series (CATS)
Departments > Statistics
Date Deposited: 29 Sep 2008 13:16
Last Modified: 20 May 2020 01:03

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