Environmental predictions produced with numerical models of the atmosphere and of the ocean possess intrinsic uncertainty.

This uncertainty is caused through both errors in the specification of the initial state of the model, as well as errors in the model formulation itself. In the process of forecast simulation, the consideration of both error sources is important, because the nature of atmospheric dynamics is such that it acts to increase errors originating from either error source. In addition to this overall error-growth effect, forecast error possesses considerable day-to- day variability depending, among other things, on the flow regime.

The quantitative and reliable assessment (i. e., prediction) of the uncertainty of environmental prediction is important, both for scientific and economic reasons. Scientifically, quantification of atmospheric/ocean predictability asks for the rate at which two initially close trajectories diverge (on average) for given atmospheric dynamics. Such estimates place upper bounds on time horizons over which useful forecasts may be expected. Economically, a reliable estimate of the uncertainty of a particular forecast will lead to increased credibility and utility of environmental forecast.

The limited predictability of atmospheric flows, considered here on time scales of days, results essentially from the intrinsic error growth in the atmosphere/ocean.

The numerical techniques permit to obtain a better approximation of the numeric solution of the equations describing the evolution of the atmosphere/ocean status increasing the spatial resolution. From the technical point of view, this implies the increasing of the need of memory and storage, because of more data for initial and boundaries conditions and more computing power for the rising of the calculations complexity.

Currently the CCMMMA uses the following models: