Multi-scale Analysis of Radar Reflectivity Maps

This study focuses on the modelling of spatial variability of rain by a multifractal approach. We consider the framework of Universal Multifractals. The data are radar reflectivity maps from the AMMA campaign (Analyse Multidisciplinaire de la Mousson Africaine, Djougou, Benin, 2006) and Meteo France's operational network (Rennes, France, 2007-2008). Since rain-no rain intermittency has been shown to bias the parameter estimates, we perform our analysis only on non-intermittent square fields. The fundamental parameters are found to be close to α=1.7 and C1=0.15, regardless of the dataset. It is not possible to conclude about the non-stationarity parameter H, because its estimations are significantly different in the two cases (0.23 and 0). However, some discussion about data quality indicates that the first value is more likely to be correct, meaning that rain fields would be non-stationary. Then, simulations have been used to estimate the bias due to rain intermittence. This effect is to underestimate α and this explains the difference between the estimated α and the values usually found in the literature (1.3-1.5). Finally, these results are compared to those determined by analysis of non-intermittent temporal series of disdrometer rain rates, corresponding to AMMA campaign data. We show the similarity between the estimated values and propose some explanations.