Using Adjoint Models for Stability and Predictability Analysis

The primary purpose of data assimilation in meteorology and oceanography is to initialise numerical models so that they can be used to forecast the state of the atmosphere or ocean at some time in the future. The reliability of the resulting model prediction depends upon a number of factors. These include the accuracy of the model and the quality of the assimilated observational data, both of which are reflected in uncertainties in the model initial conditions produced by the initialisation procedure. The predictability of the system will also depend upon its initial state in that certain configurations of the system are dynamically more unstable than others when subjected to perturbations arising from errors in the initial conditions or model physics. The model may also have inaccuracies which may not reflected in the initial conditions but which will also influence the predictability of the system.

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