  The purpose of this review-and-research paper is twofold: (i) to review the
role played in climate dynamics by fluid-dynamical models; and (ii) to
contribute to the understanding and reduction of the uncertainties in future
climate-change projections. To illustrate the first point, we focus on the
large-scale, wind-driven flow of the mid-latitude oceans which contribute in a
crucial way to Earth's climate, and to changes therein. We study the
low-frequency variability (LFV) of the wind-driven, double-gyre circulation in
mid-latitude ocean basins, via the bifurcation sequence that leads from steady
states through periodic solutions and on to the chaotic, irregular flows
documented in the observations. This sequence involves local, pitchfork and
Hopf bifurcations, as well as global, homoclinic ones. The natural climate
variability induced by the LFV of the ocean circulation is but one of the
causes of uncertainties in climate projections. Another major cause of such
uncertainties could reside in the structural instability in the topological
sense, of the equations governing climate dynamics, including but not
restricted to those of atmospheric and ocean dynamics. We propose a novel
approach to understand, and possibly reduce, these uncertainties, based on the
concepts and methods of random dynamical systems theory. As a very first step,
we study the effect of noise on the topological classes of the Arnol'd family
of circle maps, a paradigmatic model of frequency locking as occurring in the
nonlinear interactions between the El Nino-Southern Oscillations (ENSO) and the
seasonal cycle. It is shown that the maps' fine-grained resonant landscape is
smoothed by the noise, thus permitting their coarse-grained classification.
This result is consistent with stabilizing effects of stochastic
parametrization obtained in modeling of ENSO phenomenon via some general
circulation models.
