A radar data based short-term rainfall prediction model for urban areas - a simulation using meso-scale meteorological modelling

A conceptual short-term rainfall prediction model for urban catchments is p resented. The only input variables are surface rainfall and vertically inte grated liquid water content (VIL), both measurable by radar on site. The fo recast is based on simple mass balancing of water within air columns and th e spatial advection of the variables using information from consecutive tim e steps. This paper describes a qualitative study, in which the conceptual model is rested within an idealised numerical framework: instead of using o bserved and potentially noisy radar data, it is initialised with output fro m a three-dimensional physically based meso-scale meteorological model. The meteorological model provides the microphysical data as well as detailed i nformation on the dynamics and structure of the atmosphere, which are gener ally not available with observational data. The performance of the predicti on model is assessed with regard to different types of rainfalls as well as respond time of the catchments. First results suggest that the conceptual model is capable of qualitatively predicting future surface rainfall develo pment, including formation of new cells, cell splitting and decay. There is also indication that the conceptual model performs better than simple adve ction routines: for lead times that correspond roughly to the respond times of the catchments. The results lead to the conclusion that the information of VIL may be useful for quantitative rainfall prediction, and that the co nceptual model should be further developed and tested with real radar data. (C) 2000 Elsevier Science B.V. All rights reserved.