EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A snow reanalysis for Italy: IT-SNOW 

Francesco Avanzi1 and the IT-SNOW team*
Francesco Avanzi and the IT-SNOW team
  • 1CIMA Research Foundation, Savona, Italy
  • *A full list of authors appears at the end of the abstract

Quantifying the amount of snow deposited across the landscape at any given time is the main goal of snow hydrology. Yet, answering this apparently simple question is still elusive -- particularly in complex and high-elevation terrains where data are sparse. To contribute to the advancement of snow hydrology in Mediterranean regions, we present the first serially complete and multi-year snow reanalysis for Italy (IT-SNOW). IT-SNOW covers the period from September 2010 to August 2021, with future updates envisaged on a regular basis. This reanalysis is the output of a real-time snow and glacier monitoring chain – S3M Italy -- developed for the Italian Civil Protection Department by CIMA Research Foundation. Spatial resolution is 500 m, with input data coming from thousands of weather stations across the Italian territory. By assimilating blended snow-covered area maps from Sentinel-2, MODIS, and the Eumetsat H-SAF products, as well as interpolated snow-depth maps from in-situ data, IT-SNOW optimally combines dynamic modeling and data towards reconciled estimates of snow amount and water equivalent at various scales. IT-SNOW was validated using Sentinel-1-based maps of snow depth and in-situ snow data in the Alps and the Apennines, with little bias compared to the former and typical Root Mean Square Errors of 30 to 60 cm and 90 to 300 mm for snow depth and Snow Water Equivalent, respectively. A comparison at 102 gauge stations showed a strong (0.87) correlation between peak SWE in IT-SNOW and measured annual streamflow, with snow being 22% of annual streamflow on average. IT-SNOW is freely available at the following DOI: and we encourage users to validate and provide critical feedback for future releases.  

IT-SNOW team:

Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, Luca Ferraris

How to cite: Avanzi, F. and the IT-SNOW team: A snow reanalysis for Italy: IT-SNOW , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1361,, 2023.