unseen-awg: spatio-temporal weather generation using analogs and unseen data
Acronym
unseen-awg
Name
unseen-awg: spatio-temporal weather generation using analogs and unseen data
Description
Unseen-awg is a method for generating long, multivariate, and spatiotemporal weather data representative of present-day climate by resampling historical weather datasets. It assures temporal consistency in the generated weather by ensuring that successive sampled days have consistent large-scale atmospheric fields. Long datasets of artificial weather data, such as those simulated with unseen-awg, allow anticipating unseen weather and help prepare for possible weather-related hazards. Unseen-awg simulations can be used to drive impact models across sectors influenced by weather such as water, agriculture, and forestry. To this end, the weather generator allows simulating weather over all of Europe.
Here, we provide simulations with the weather generator, an instance with pre-computed components, and the data necessary for using the provided simulations, generating new ones, and generating new instances of unseen-awg.
Project members received financial support by the Federal Ministry of Research, Technology and Space of Germany and by Sächsische Staatsministerium für Wissenschaft, Kultur und Tourismus in the programme Center of Excellence for AI-research "Center for Scalable Data Analytics and Artificial Intelligence Dresden/Leipzig", project identification number: ScaDS.AI.