A downscaling framework for precipitation nowcasting by merging radar retrievals at different scales and resolutions

Convective rainfall events represent one of the most critical issues in urban areas, where numerical weather prediction models are affected by a large uncertainty related to the short temporal and spatial scales involved, thus making early warning systems ineffective. Conversely, radar-based nowcasting models may be a useful tool to guarantee short-term forecasts, through the extrapolation of most recent properties in observed precipitation fields, for lead times ranging from minutes to few hours.

In this study we develop a procedure for merging relevant information from two radar products with different resolutions and scales: (i) high-resolution observations retrieved by an X-band weather radar in a small domain (the metropolitan area of Cagliari, located in Sardinia, Italy), and (ii) the mosaic data provided by the Italian Civil Protection national radar network (the whole region of Sardinia). Specifically, we here adapt some STEPS procedures to merge the large-scale advection from the latter radar network, and the small-scale statistical properties for the former X-band weather radar. We thus combine the corresponding forecasts preserving the higher resolution scale. In details, for each time step we (i) evaluate the power spectra of the two forecasts (ii) merge the two spectra taking the power of the large (small) frequencies from the high (low) resolution data spectrum and (iii) achieve optimal downscaling by reconstructing the high-resolution nowcast from the blend of the two spectra.