Soil moisture is crucial for the water cycle since it is the frontline of drought. Satellite, model, and in-situ data help identify soil moisture stress but challenged by data uncertainties. This study evaluates trends and data coherence of common active/passive microwave sensors and model-based soil moisture data against in-situ stations across Europe from 2007 to 2022. Data reliability is increasing but combining data types improves soil moisture monitoring capabilities.

This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.

Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.

We need seasonal predictions of temperature and precipitation to prepare hydrological outlooks. Since the skill is limited, statistical correction and combination of outputs from multiple models are necessary. We use the forecasts of past situations from the EUROSIP multi-model system for 6 case studies in Western Europe and the Mediterranean Region. We identify skill for spring temperature in most areas and winter precipitation in Sweden and Greece. Sample size for training appears crucial.

This study shows the possibility to improve the weather forecast at the very short range (0–3 h) using lightning and/or radar reflectivity observations. We consider two challenging events that occurred over Italy, named Serrano and Livorno, characterized by moderate and exceptional rainfall, respectively. The improvement given to the forecast by using the lightning and/or radar reflectivity observations is considerable. The best performance is obtained when using both data.