Quantifying Uncertainties in Climate Science.

Many climate-critical process vary partly on scales that are too small or fast to be resolved explicitly by global climate models.  These processes really should be represented stochastically, not deterministically.  This talk will use air-sea fluxes as a case study, to show how stochastic perturbations can affect various aspects of the mean climate (even though the mean perturbation is zero) and also the climate variability. The findings demonstrate that noise-induced drift and noise-enhanced variability, which are familiar concepts from simple climate models, continue to apply in comprehensive climate models with millions of degrees of freedom.  The findings also suggest that the lack of representation of sub-grid variability in air-sea fluxes may contribute to some of the biases exhibited by contemporary climate models.