This method generates probabilistic solar power forecasts of up to 30 min using artificial intelligence and fish eye images of the sky. We investigated the impact of parameters describing the variability of the solar power on the forecast performance and divided the solar power to its direct and diffuse components. The method achieves overall good performance, while variability parameters and dividing the solar power don't show any performance gain. However, training time can be decreased.

We consider possible influence on severe weather occurrence by aurorally excited atmospheric gravity waves generated by solar wind coupling to the magnetosphere-ionosphere-atmosphere system. The results indicate that these gravity waves contribute to the release of instabilities in frontal zones of extratropical cyclones leading to convection and heavy precipitation. It is observed that severe snowstorms and flash floods tend to occur following arrivals of solar wind high-speed streams.

We presents the Basque Country Impact Weather Catalogue, recording detailed information on adverse weather events and their environmental impacts. It includes context, hazard/risk, and impact sections, utilizing data from Euskalmet, Emergency, Media, Insurance, etc. Standardized information enables qualitative and quantitative analysis feasibility for events spanning the 21st century. The paper details catalogue design, structure, and implementation steps.

This study examines floods in the Basque Autonomous Community from 2000 to 2021, assessing damages, weather conditions, and other factors. It uses data from the Spanish Insurance Compensation Consortium and the AWS network, analyzing diverse datasets to extract indicators. Visual analytics are used for analysis and characterization.