We studied temporal trends and variability of snow depth and snow water equivalent (SWE) in six regions of the Italian Alps. We applied different statistical analyses to a dataset of homogeneous and continuous measurements of snow depth and SWE, temporally spanning from 1967 to 2020, and discussed the results with meteo-climatic data. Our results quantify the decrease of SWE in the study area, confirming the impacts of climate modifications on the cryosphere in the Alps.

Historical climatological data extending beyond instrumental records are needed. Blue intensity data (BI) from Southern Rhaetian Alps European larches enhances the strength of dendroclimatology in reconstructing past climate at high resolution and results a better proxy than total ring width data. BI processing permits to reconstruct summer temperatures on a regional scale, and also contribute to extend the reconstruction to the Mediterranean basin and northern Europe with excellent correlation.

We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.

Flood risk is an increasing threat to urban communities and their strategical assets worldwide. Non-structural practices, such as emergency management plans, can be effective in order to decrease the flood risk in strongly urbanized areas. Mobile phone data provide reliable estimates of the spatiotemporal variability in people exposed to flooding, thus enhancing the preparedness of stakeholders involved in flood risk management. Further, practical advantages emerge with respect to crowdsourcing.

We present and compare 11 years of snow data measured by an automatic weather station and corroborated by data from field campaigns on the Forni Glacier in Italy. The methodology we present is interesting for remote locations such as glaciers or high alpine regions, as it makes it possible to estimate the total snow water equivalent (SWE) using a relatively inexpensive, low-power, low-maintenance, and reliable instrument such as the sonic ranger.