Nowcasting precipitation — a proposal for a way forward

Abstract

There is little doubt that hybrid mesoscale model and image extrapolation systems will eventually become widespread for the nowcasting 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 high-order statistics of rain patterns should also allow improved extrapolation schemes for nowcasting. A well-known technique that preserves space–time statistics is presented as an example of this. It is argued that the relative scoring of forecast systems is highly space–time resolution dependent, and that even when the same meteorological event is being considered this resolution dependency must be taken into account.