J. Thielen et al., A radar data based short-term rainfall prediction model for urban areas - a simulation using meso-scale meteorological modelling, J HYDROL, 239(1-4), 2000, pp. 97-114
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.
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