On the predictability of rainfall patterns

There is little doubt that hybrid mesoscale model and image extrapolation systems will eventually become widespread for the forecasting of precipitation for hydrology and aviation safety. Arguably the final forecast output that is required for these applications needs to be probabilistic in nature, therefore appropriate forecast schemes should statistically account for both the chaotic and intermittent nature of the intrinsic fields. In principle, the detailed knowledge that we have about the statistics of rain patterns should allow improved extrapolation schemes for precipitation forecasting. A well-known technique that preserves space-time statistics is presented as an example of this. The relevance of these results to the issue of intrinsic predictability of rainfall patterns will be discussed.