The impact of space and time averaging on the spatial correlation of rainfall

Nowadays a huge amount of data is available for the statistical characterization of rainfall worldwide, although unfortunately not always with the adequate spatial and temporal resolution required for the very high demanding telecommunication applications. On the basis of the NIMROD radar network composite rain maps, first, this paper investigates separately the impact of space or time integration on the spatial correlation of rainfall r, a key parameter for most Propagation Impairment Mitigation Techniques (PIMTs), as well as for many prediction models such as time-space rain field generators. Analytical formulations are proposed to model the average trend of r with the distance d between two sites as a function of the integration time T or the integration area A, which, in turn, can be used to de-integrate the spatial correlation information estimated respectively from networks of raingauges with long integration time or from radar data with coarse spatial resolution. As an example, the last part of the paper compares the spatial rain decorrelation trends estimated by a database of radar maps collected in Northern Italy with the ones de-integrated from products of meteorological re-analyses (ERA40) or Earth Observation missions (TMPA 3B42).