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OCIAM**

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Oxford Centre for Industrial and Applied Mathematics
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Dr Leonard A Smith's Publications**

The Role of Operational Constraints in Selecting Supplementary Observations

J. A. Hansen & L.A. Smith J. Atmos. Sci. 57: (17) 2859-2871.

ABSTRACT
Adaptive observation strategies in numerical weather prediction aim to improve
forecasts by exploiting ad- ditional observations at locations that are themselves
optimized with respect to the current state of the atmosphere. The role played by an
inexact estimate of the current state of the atmosphere (i.e., error in the
``analysis'') in restricting adaptive observation strategies is investigated;
necessary conditions valid across a broad class of modeling strategies are identified
for strategies based on linearized model dynamics to be productive. It is
demonstrated that the assimilation scheme, or more precisely, the magnitude of the
analysis error is crucial in limiting the applicability of dynamically based
strategies. In short, strategies based on linearized dynamics require that analysis
error is sufficiently small so that the model linearization about the analysis is
relevant to linearized dynamics of the full system about the true system state.
Inasmuch as the analysis error depends on the assimilation scheme, the level of
observational error, the spatial distribution of observations, and model
imperfection, so too will the preferred adaptive observation strategy. For analysis
errors of sufficiently small magnitude, dynamically based selection schemes will
outperform those based only upon uncertainty estimates; it is in this limit that
singular vector-based adaptive observation strategies will be productive. A test to
evaluate the relevance of this limit is demonstrated.

## Contact Information

Tel: 01865-2-70517

E-mail: lenny@maths.ox.ac.uk
Last updated: 14 Feb 2001

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