HyPrecip: Hyper-resolution multi-dimensional precipitation information for analysis and modelling: urban and rural applications

Hyper-resolution spatial and temporal precipitation information is essential in many unresolved hydro-environmental research problems.

Examples are scale problems in regional to local-scale variation of climate involved in urban flooding, plant-soil-water processes, and building infrastructure lifetime and safety.

Lack of such data prevents a better understanding of these fundamental processes necessary in many engineering and environmental applications.

In this context, we propose an AI-assisted approach to assimilate rainfall information from multiple state-of-the-art technologies based on the new generation of X-band weather radars for fundamental research.

These radars complement traditional large-scale radar observations, satellite products, and gauge measurement with possibilities to study downscaling effects in many significant climatic and environmental research problems.

We also introduce emerging technologies such as micro rain radar and disdrometer that complement and possibly improve conventional measurement methods to achieve a hitherto unprecedented possibility to improve our physical understanding of basic hydro-environmental processes at a range of scales.

The proposal will have at its disposal three X-band polarimetric radars covering a major part of Skåne, C-band radar network covering entire Sweden, micro rain radar, disdrometers, satellite product, and a dense rain gauge network covering Skåne region.