In a classic paper in 1969, Lorenz demonstrated how in a two dimensional barotropic system an initial error in small scales induces error growth in larger scales. He showed that the predictability limit depended sensitively on the equilibrium energy spectrum. For a -5/3 slope, predictability is intrinsically limited no matter how small the initial error. However, for a spectral slope of -3 or greater, increases in predictability were possible with the reduction in the scale and size of the initial error.

Experience with operational numerical weather prediction (NWP) during the past 25 years has shown that as we continue to reduce the resolution of NWP models and improve the initial conditions of the atmosphere with better data analysis and assimilation schemes, we continue to improve medium range weather forecasts. Does this mean that we are still in the -3 regime? Or, is it possible that although our current high resolution models are beginning to resolve the upper portions of the -5/3 spectral range, the reason we continue to improve forecasts is because the scaling arguments on which intrinsic limits of predictability were based are not valid for the small scale of the real atmosphere? Recent observations of the atmospheric energy spectrum will be used to address the above questions, including the potential for further improvements in medium range weather forecasts with improved models and improved observations.

In the second part of the lecture it will be shown that certain regions of the global atmosphere are so strongly determined by the underlying boundary conditions (viz sea surface temperature) that they do not show sensitive dependence on initial conditions of the atmosphere, and it should be possible to predict the atmospheric circulation (and rainfall) for as long as the lower boundary forcing can be predicted.