Abstract ID: 3.12216 | Accepted as Poster | Poster | TBA | TBA

Climate change is increasingly influencing environmental and socio-economic systems, necessitating accurate meteorological datasets to assess regional climate variability and related risks. Due to their key role for water storage and supply, accurate precipitation records for Alpine regions are crucial for understanding ongoing trends in precipitation regime as well as for modelling hydrological processes. However, transboundary river basins often suffer from data fragmentation due to inconsistencies in data collection, processing, and harmonization across regional and national providers. The mountainous nature of the territory poses an additional challenge for the retrieval of accurate precipitation fields, due to the general reduction of station data availability in high-elevation areas and systematic errors due to rain-gauge under-catch, especially for snowfall. In this framework, we developed a high-resolution (1-km) gridded dataset of daily precipitation spanning 1990–2023 for an extended area centered on the Adige River catchment starting from approximately 700 rain gauges from multiple data providers in Italy and surrounding countries. The Adige River catchment, located in the south-eastern Alps, represents an important Italian region providing water to multiple sectors and over a wide downstream area. The interpolation method based on a two-step procedure incorporating orographic influences was selected by comparing the performance of different approaches and tuned to minimize the interpolation errors. To estimate and address the underestimation of precipitation in the high-mountain portions of the basin, a first test for exploiting available snow height measurements and quantifying the magnitude of potential corrections was carried out. Specifically, we investigated and discussed the benefits and challenges of using of snow measurement sites as virtual rain gauges, through deriving the water equivalent of new snow, in mountain locations to get a more reliable representation of precipitation fields at high elevation. The final dataset was evaluated against existing large-scale precipitation products covering the area, showing the improved spatial representation offered by the enhanced data density and grid resolution. This research is conducted within the framework of the RETURN Extended Partnership (European Union Next-GenerationEU, National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022,