Multi-scale assessment of high-resolution reanalysis precipitation fields over Italy

TL;DR

This paper evaluates the accuracy of nine high-resolution reanalysis datasets in reproducing Italy's complex precipitation patterns, highlighting their strengths and limitations in capturing spatial and temporal variability.

Contribution

It provides a comprehensive multi-scale assessment of various reanalysis products' performance in simulating Italy's precipitation, using wavelet analysis and validation against observations.

Findings

Maximum precipitation misplacement of about 15 km

Overestimation of precipitation in Po Valley and Alps

Underestimation along North-West coast, Apennines, and South Italy

Abstract

This study focuses on the validation of high-resolution regional reanalyses to understand their effectiveness in reproducing precipitation patterns over Italy, a climate change hotspot characterized by coastal sea-land interaction and complex orography. Nine reanalysis products were evaluated, with the ECMWF global reanalysis ERA5 serving as a benchmark. These included both European (COSMO-REA6, CERRA) and Italy-specific (BOLAM, MERIDA, MERIDA-HRES, MOLOCH, SPHERA, VHR-REA\_IT) datasets, using different models and parametrizations. The inter-comparison involved determining the effective resolution of daily precipitation fields using wavelet techniques and assessing intense precipitation statistics through frequency distributions. In-situ observations and observational gridded datasets were used to independently validate reanalysis precipitation fields. The capability of reanalyses to depict daily precipitation patterns was assessed, highlighting a maximum radius of precipitation misplacement of about 15 km, with notably lower skills during summer. An overall overestimation of precipitation was identified in the reanalysis climatological fields over the Po Valley and the Alps, whereas multiple products showed an underestimation of precipitations across the North-West coast, the Apennines, and Southern Italy. Finally, a comparison with a time-consistent observational dataset (UniMi/ISAC-CNR) revealed a non-stable deviation from observations in the annual precipitation cumulate of the reanalysis products analyzed. This should be taken into account when interpreting precipitation trends over Italy.