|Title||Stochastic parametrisation models for GFD|
|Publication Type||Conference Paper|
|Event||ECMWF/WWRP Workshop: Model Uncertainty|
|Conference Location||ECMWF, Reading|
|Keywords||model 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  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  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.