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Stochastic Parametrisation and Model Uncertainty in the Lorenz ‘96 System Ìý

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Date and time:Ìý

Thursday, September 25, 2014 - 9:30am

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ECCR 257

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Representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic forecasts: we seek to provide firm foundations for the use of stochastic parametrisation schemes for this purpose. Idealised experiments are carried out in the Lorenz ‘96 (L96) simplified model of the atmosphere, in which all sources of uncertainty apart from model uncertainty can be removed. Stochastic parametrisations are found to be a skilful way of representing model uncertainty in weather forecasts in this system. Stochastic schemes that have a realistic representation of model error produce reliable forecasts, improving on the deterministic and the more ``traditional’’ perturbed parameter schemes tested. The potential of using stochastic parametrisations for simulating the climate is considered. A significant improvement is observed when stochastic parametrisation schemes are used to represent model uncertainty in climate simulations in the L96 system. This improvement is particularly pronounced when considering the regime behaviour of the L96 system – the stochastic forecast models are significantly more skilful than using a deterministic perturbed parameter ensemble to represent model uncertainty. Finally, the lessons learned in the L96 system are used to test and develop stochastic and perturbed parameter representations of model uncertainty for use in operational atmospheric models.
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