Discrete cascade disaggregation of climate models for high resolution rainfall estimation in urban environment

Extreme rainfalls have strong consequences in urban area. Their knowledge is required to properly handle storm water management systems and avoid urban flooding as well as optimize depollution capabilities. Hence improving understanding of future rainfall extreme in a changing climate is of paramount interest to adapt the cities and increase their resilience.      

In this paper future rainfall extremes are quantified through the universal multifractal (UM) framework. This is a parsimonious framework that has been widely used to characterize and simulate geophysical, extremely variable fields, such as rainfall, across wide range of scales. It has also been used for statistical downscaling of geophysical fields.

Here, we apply this formalism to analyse output data from Regional Climate Models CNRM-CM5 and SMHI-RCA4 over the European-Mediterranean domain EUR-11 of the CORDEX Project. We first use the multifractal analysis techniques to characterize the scaling behaviour of future rainfall .  The three UM parameters are then assessed. The notion of maximum observable singularity is then used to quantify extremes across the available scales  (12.5 km and 1 hour resolution at maximum)

Finally, initial work using discrete cascades, to generate realistic rainfall series at higher resolution with very light parametrization will be presented. Basically the underlying cascade process retrieved on the available scales is continued down to the scales required for urban hydrology applications. Both spatial and temporal downscaling are carried out, allowing to get new insights on how to model seasonal effects using multifractal formalism.