Ross Bannister, Data Assimilation Research Centre
Read-in the initial guess,
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Set-up the background state,
(
for first run, from last forecast for later runs)
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Set-up the linearization state
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Work out perturbation of the background from the linearization state,
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Do a forecast to the end of the current cycle, starting from
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Calculate the gradient of w.r.t. model observations
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Linearize the forward model,
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Calculate the Hessian in model space,
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Diagonalize the Hessian, eigenvectors , eigenvalues
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Calculate the components of the -transform,
(this makes the Hessian in transformed space identity, )
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Calculate the gradient of w.r.t. the transformed variables,
(the analysis increment in transformed space is )
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Calculate the analysis increment in model space,
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Calculate a new linearization state,
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¬ If , go to
, otherwise
is the analysis: perform an integration from
and go to