Stochastic parametrisation models for GFD

TitleStochastic parametrisation models for GFD
Publication TypeConference Paper
Date Published05/2016
EventECMWF/WWRP Workshop: Model Uncertainty
AuthorHolm, D
Conference LocationECMWF, Reading
Keywordsmodel uncertainty, workshop

In next-generation weather and climate models, stochastic parameterisation should be an important element in providing reliable estimates of model uncertainty. A fundamental conclusion of Berner, Jung & Palmer [2012] is that

“a posteriori addition of stochasticity to an already tuned model is simply not viable [satisfactory]. This in turn suggests that stochasticity must be incorporated at a very basic level within the design of physical process parameterisations and improvements to the dynamical core."

This talk responded to the workshop’s challenge of “How do we improve the physical basis for model uncertainty schemes?” It proposed an a priori introduction of stochasticity for GFD models at various levels of approximation, by introducing the methodology of Holm [2015] as a potential framework for quantifying model transport error. In turn, the stochastic representation of model transport error would introduce stochasticity into the parameterisations of subgrid scale processes.


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