EDWARD S. SARACHIK
Coupled atmosphere-ocean-land-cryosphere models are basic tools in the study of climate and its variability. Since the atmosphere is sensitive to changes in lower-boundary conditions on long enough time scales, we must simulate the time evolution of these conditions in order to ensure the consistent simulation of the atmosphere. The time scales of atmospheric sensitivity depend on the geographic region of interest: The tropical atmosphere responds to sea surface temperature (SST) variability on monthly and longer time scales, while it has not been shown that the mid-latitude atmosphere responds significantly to SST unless the anomaly lasts for several years. Furthermore, variations in mid-latitude soil moisture seem to affect the distribution of precipitation over the continents seasonally. Variations of snow cover and sea ice have also been implicated in atmospheric variability beyond the seasonal time scale.
In turn, the evolution of the lower boundary conditions is partly determined by atmospheric processes, so coupled models become essential for simulating the mutually consistent evolution of the interacting systems. It is safe to say that if we are interested in decade-to-century-scale climate variability, the global atmosphere must be coupled to the global ocean, to the global land surface, and to global snow and ice.
While this realization has been with us since the beginning of climate modeling, progress in coupled modeling over the past decade has been fitful and hard won. The basic problem has been one of resources: A 100-year run of a coupled model consisting of a global atmosphere of modest resolution, with land processes parameterized, coupled to a global coarse-resolution ocean, with sea ice, uses a major part of a dedicated supercomputer. Increasing the resolution by just a factor of two increases the computer demands by an order of magnitude. If we are to understand and simulate climate variability on decade-to-century time scales, model runs of thousands of years are required. Up to this time, fully coupled models of satisfactory (but never sufficient) resolution have been run only at major institutions having access to large amounts of supercomputer time.
As computers become more capable, resource problems are ameliorated and the real problems of physical climate simulation come to the fore. The fundamental problem has been that the coupling of a reasonably well-understood atmospheric model to a reasonably well-understood oceanic model has produced a coupled model that is not only not well understood but also exhibits unexpected and unaccounted-for properties. The sensitivities of the two models to errors in each other, which are not apparent when each model is run in decoupled mode, seem to produce unusual sensitivity in the coupled model (Ma et al., 1994). It has become increasingly clear that a coupled model is a unique beast, with properties distinct from those of the component models. Coupled modeling therefore requires a quite different set of outlooks and approaches from those needed for modeling the component systems.
The coupled-model papers that appear in this chapter can best be put into perspective by recounting a bit of the history of coupled climate modeling, by pointing out where we now stand with respect to coupled modeling (and the data needed to support such modeling), and by suggesting