Year: 2025
Type: data-paper
Abstract: A stochastic weather generator provides data by capturing statistical properties of observed weather patterns, enabling the simulation of realistic time series beyond the historic record. Such simulated weather data can be valuable in many fields (e.g., agriculture and energy), where multiple variables (e.g., temperature and precipitation) influence the production processes. Here, we present a new European simulated dataset for temperature, precipitation and wind speed, generated by the MYRIAD-Stochastic vIne-copula Model (MYRIAD-SIM). MYRIAD-SIM captures both spatiotemporal and multivariate dependencies with the use of conditional vine copulas, a statistical tool. The statistical properties of the MYRIAD-SIM data closely resembles ERA5-Land data while maintaining sufficient variability to explore possible alternative scenarios. The simulated data can facilitate new insights in, for example, compound climate event research, by providing multivariate weather events across different conditions.
Source: Scientific Data
Authors: Judith N. Claassen, Elco E. Koks, Marleen C. de Ruiter, Philip J. Ward, Wiebke S. Jäger
Institutions: Vrije Universiteit Amsterdam, Deltares
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,490
Awards: Multi-hazard and sYstemic framework for enhancing Risk-Informed mAnagement and Decision-making in the E.U., Multi-hazard, Disaster risk management, Climate action, resilient societies, G6720926869, Multi-hazard Infrastructure Risk Assessment for Climate Adaptation, G8207596269, When the total is different from the sum of its parts: improving our understanding of consecutive disasters caused by natural hazards and disease outbreaks
OpenAlex ID: W4415807548