As we navigate the global challenges of climate and environmental extremes, operationalizing AI/ML in weather forecasting and decision support emerges as pivotal. This session will explore how the integration of AI/ML technologies are enhancing resilience and scalability in weather-related services. We encourage submissions that discuss overcoming social and technical hurdles in AI implementation, focusing on trust-building, operational stability, and scalable solutions across cloud and high-performance computing infrastructures. Contributions should also highlight successful case studies and cautionary tales in operationalizing AI tools, emphasizing their impact on fostering resilient communities and thriving ecosystems.
Key areas of interest include:
1. Cluster to Cloud: Technologies and platforms for accelerating research to production.
2. Verification and Validation: Building trust in AI through rigorous processes.
3. Quantifying and Communicating Uncertainty: Techniques
             for enhancing model output interpretation.
4. Model Confidence: Ensuring robustness of ML models in changing climates.
5. Success and Cautionary Tales: Real-world examples of AI deployment in weather products.
6. Operationalizing AI applications for R2O

Conveners: Thanh Vo, NOAA/NESDIS/OSAAP Affiliate and ISS, Inc., Martin Yapur, Kyle Hilburn, Christina Kumler, Tiago Quintino