As society becomes increasingly reliant on space-based technologies and space weather forecasting to support critical infrastructure and exploration initiatives, confidence in predictive models is more important than ever. Models play a central role in understanding and predicting space weather across the coupled sun-to-mud system, yet establishing confidence in these models remains a key challenge, as diverse and often hybrid modeling approaches require comprehensive validation.

This session invites contributions on validation and capability assessment of space weather models through established frameworks, including event-based analyses, multi-instrument comparisons, data-driven evaluation methods, and evaluation of data-assimilative models against independent observations. We welcome assessments of modeling capabilities of physical phenomena across all heliophysics domains, validations focused on essential space environment quantities linked to impacts or passed between domains, and studies connecting model performance to physical realism, uncertainty, and predictive capability. Contributions supporting the research-to-operations-to-research (R2O2R) pipeline are especially encouraged.

• SH - SPA-Solar and Heliospheric Physics
• SM - SPA-Magnetospheric Physics