Abstract
The use of analysis increments to represent model error in the Met Office ensemble prediction system is compared with the use of stochastic parametrizations. Since analysis increments can take into account more possible sources of forecast error than stochastic parametrizations which only represent specific sources of error, the spread of the ensemble and the reliability are markedly improved. There is an increase in the rms error of the ensemble mean for some fields. This may be because analysis increments cannot represent state‐dependent statistics, but may also result from the use of initial condition perturbations from the operational ETKF rather than an ensemble data assimilation with a consistent treatment of model error.
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