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Simulated Annealing: A Tool for Data Assimilation into an Almost Steady Model State

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  • 1 Alfred-Wegener-Institute for Polar and Marine Research, Bremerhaven, Germany
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Abstract

A new method is used to calculate a steady-state best fit of a given strongly nonlinear time-dependent model to observed data. The proposed technique has a statistical nature and is known as simulated annealing. It is described in detail and two examples are presented. In the first example a simple but highly nonlinear model is considered. It is shown that simulated annealing is robust and converges to the solution, whereas the adjoint technique, a sophisticated optimization method, fails. The second example illustrates that simulated annealing is also able to handle a problem with many degrees of freedom (∼4000). The required amount of computer time can be accepted.

Abstract

A new method is used to calculate a steady-state best fit of a given strongly nonlinear time-dependent model to observed data. The proposed technique has a statistical nature and is known as simulated annealing. It is described in detail and two examples are presented. In the first example a simple but highly nonlinear model is considered. It is shown that simulated annealing is robust and converges to the solution, whereas the adjoint technique, a sophisticated optimization method, fails. The second example illustrates that simulated annealing is also able to handle a problem with many degrees of freedom (∼4000). The required amount of computer time can be accepted.

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