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Assimilation algorithm - Specification of the forecast error variance

The time evolution of the variances is represented by a law of the form:

with

	Variance of the forecast error at time k
	Operator representing the transport
	Time step of the model
	Ozone relaxation time
	Relative amplitude of the error model
	Climatological ozone mixing ratio

The first term represents the predictability error (as defined by Daley, MWR 120, 1735, 1992; that is the propagation of the error by the model), the second is the model error (that is the error made by the model over 1 time step).

·       The quality of the analyses depends on the correct estimation of the forecast error covariance matrix;

·       In the present case, the correlation is estimated from the difference between analysed (resulting from the assimilation of MLS data) and forecast ozone fields (Parrish & Derber, MWR 120, 1747, 1992).