SnowWarp: An open science and open data tool for daily monitoring of snow dynamics

Snow cover is a key hydrological variable, critical to understanding water cycles and informing management decisions around resource extraction and recreational activities. Remote sensing open-access data and cloud -based computing platforms are two innovative tools for snow cover estimation. In this paper, we present SnowWarp, a processing framework that uses Google Earth Engine and the R programming languages to combine Landsat 30 m with MODIS 500 m satellite imagery and produce daily-30-m spatial resolution snow cover data anywhere globally. SnowWarp was applied in an alpine catchment in Northern Italy from 2000-2019 and validated using hy-drometeorological datasets. Strong correlations between snow cover and ground data were found with corre-lations in terms of R up to-0.84 for temperature,-0.17 for precipitation, 0.74 for snow depth, and-0.43 for streamflow. The SnowWarp tool is an open-source framework enabling users to map fine spatial and temporal dynamics of snow cover to the ecosystem and hydrological monitoring.