Cloud and Precipitation Observations, Modeling, And Prediction in Svalbard

The Arctic climate is changing rapidly with Svalbard experiencing some of the fastest warming globally. This means increasing precipitation and more frequent extreme events, causing severe consequences for ecosystems, infrastructure and society. Despite the risks, significant knowledge gaps remain regarding cloud and precipitation processes, particularly in spatial variability, observational uncertainties and model representations. This project aims to improve the understanding and prediction of clouds and precipitation in Svalbard by facilitating collaboration between observational, modelling and forecasting experts. The project will integrate remote sensing and in-situ datasets from Ny-Ålesund and Longyearbyen, and deploy additional instruments, including a micro rain radar, a disdrometer, and a total sky imager in Longyearbyen to enhance observational coverage in Longyearbyen. Advanced satellite data from EarthCARE will be explored to complement ground-based measurements. Observational data will be used to evaluate and improve weather prediction models HARMONIE-AROME and ICON-LEM while also data-driven modelling approaches will be explored. By fostering data-sharing and collaboration, the project will improve process understanding, strengthen forecasting capabilities, and contribute to climate monitoring in Svalbard and the broader Arctic. The involvement of weather forecasters will help ensure that research findings are directly applicable to operational forecasting, particularly at Svalbard Airport. The project will also support higher education by involving MSc and PhD students in research activities.