Forecaster perspectives on model quality and verification at the Norwegian Meteorological Institute

Successful application of numerical weather prediction (NWP) and emerging data-driven forecast models depends not only on their objective performance but also on how forecasters interpret, trust and communicate their outputs and uncertainties. This study presents insights from a series of verification workshops conducted with operational duty forecasters at the Norwegian Meteorological Institute. The workshops aimed to foster dialogue between model developers and forecasters, improve verification systems, and create evaluation procedures that serve both model development and operational forecasting. The workshops explored how forecasters evaluate model quality, identified parameters and products that are challenging to forecast or evaluate, and explored necessary tools for building trust in model products, including data-driven forecasts. Forecasters emphasized the importance of personal operational experience, peer interaction, and case-based verification in building knowledge about model quality. The findings indicate that forecasters' experience-based verification complements quantitative objective verification and plays an important role in forecasters' decision-making. Forecasters expressed a need for verification systems tailored to operational situations, such as specific events or similar past cases, and highlighted the importance of practical tools that can be used during shifts. They also stressed the need for reliable verification that includes comparisons with traditional NWP models for building trust in data-driven models, particularly for extreme events. Overall, the study highlights the importance of the communication of model strengths and weaknesses and the co-development of tools to support operational forecasting. It provides a basis for further development of verification practices and enhancing collaboration between forecasters and model development.