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Mountain environments are extremely influenced by climate change but are also often affected by the lack of long and high-quality meteorological data, especially in glaciated areas, which limits the ability to investigate the acting processes at local scale. For this reason, we checked a method to reconstruct high-resolution spatial distribution and temporal evolution of precipitation. The study area is centred on the Forni Glacier area (Central Italian Alps), where an automatic weather station is present since 2005. We set up a model based on monthly homogenised precipitation series and we spatialised climatologies and anomalies on a 30-arc-second-resolution DEM, using Local Weighted Linear Regression (LWLR) and Regression Kriging (RK) of precipitation versus elevation, in order to test the most suitable approach for this complex terrain area. The comparison shows that LWLR has a better reconstruction ability for winter while RK slightly prevails during summer. The results of precipitation spatialisation were compared with station observations and with data collected at the weather station on Forni Glacier, which were not used to calibrate the model. A very good agreement between observed and modelled precipitation records was pointed out for most station sites. The agreement is lower, but encouraging, for Forni Glacier station data.

High-Resolution Monthly Precipitation Fields (1913–2015) over a Complex Mountain Area Centred on the Forni Valley (Central Italian Alps)