The complexity of the climate system means computer models are essential tools for analysing observations and for predicting the future as a function of the various changes that can be anticipated in the input parameters or boundary conditions. Simple models have a role to play, particularly for education, but also to develop parameterizations of specific features, such as radiative fluxes in atmospheres with high concentrations of aerosols or clouds of different types. These can then be incorporated into more complete climate models, including coupled atmospheric and oceanic GCMs with physical processes and parameters such as concentrations of greenhouse gases, the salinity of the deep layers of the oceans, the biosphere, glaciers and ice sheets, rates of volcanic emission and the topography of continents and mountains.

Even the most complex models must make assumptions and simplifications, including compromises in the resolution in space and time represented by the grid on which the equations are solved. Subgrid-scale phenomena, such as radiative transfer in irregular cloud formations or turbulent heat transfer, cannot be represented purely by the relevant laws of physics and have to be parameterized. A wide range of schemes is in use in state-of-the-art climate forecasting, and the Intergovernmental Panel on Climate Change uses the spread between forecasts from control runs by research laboratories in several countries as a way of estimating the uncertainty they introduce. The uncertainty in the input data itself, such as the expected rate at which greenhouse gases will build up in the atmosphere, is treated by IPPC 2001 using 'scenarios' ranging from strict controls over emissions and new clean technology through 'business as usual' to pessimistic assumptions about population growth and per capita power consumption increases.

Some processes that are likely to be important are not properly included even in state of the art models. The melt rate of large ice masses like the Greenland ice sheet, which potentially can raise by around 7 m the global sea level in the relatively near future, and the evolution of cloud cover in the atmosphere in response to other changes such as a general warming, are examples currently receiving much attention. So are changes in the important ocean currents like the Gulf Stream and the snow and sea-ice cover, with their important contributions to the Earth's albedo, and chemical and biological processes in response to factors such as air pollution and deforestation.

To date, the combined efforts of experimentalists, data analysts, and modellers, have revealed much of the basic physics that produce the present-day climate. We are still a long way from the point where past, let alone future, climatic variations can be reliably explained, nor can we use the models we have developed for the Earth to explain many of the major climate phenomena on the neighbouring Earth-like planets. These failures clearly indicate that the physics in even apparently successful terrestrial climate and weather-forecasting models may be fundamentally deficient.

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