Influence of small scale rainfall variability on standard comparison tools between radar and rain gauge data

Rain gauges and weather radars do not measure rainfall at the same scale; roughly 20 cm for the former and 1 km for the latter. This significant scale gap is not taken into account by standard comparison tools (e.g. cumulative depth curves, normalized bias, RMSE) despite the fact that rainfall is recognized to exhibit extreme variability at all scales. In this paper we suggest to revisit the debate of the representativeness of point measurement by explicitly modelling small scale rainfall variability with the help of Universal Multifractals. First the downscaling process is validated with the help of a dense networks of 16 disdrometers (in Lausanne, Switzerland), and one of 16 rain gauges (Bradford, United Kingdom) both located within a 1 km2 area. Second this downscaling process is used to evaluate the impact of small scale (i.e. sub-radar pixel) rainfall variability on the standard indicators. This is done with rainfall data from the Seine-Saint-Denis County (France). Although not explaining all the observed differences, it appears that this impact is significant which suggests changing some usual practice.