Lessons Learned from the Co-Development and Integration of a Subseasonal Forecast into the Yr weather service

Subseasonal forecasting, which bridges the gap between short-term weather forecasts and seasonal outlooks, covers lead times of 2–6 weeks. Traditionally, these forecasts are presented as anomalies over broad areas due to decreasing skill with lead time. However, this approach significantly limits their usability for laypeople, who are used to highly localized forecasts and often struggle with interpreting anomalies, especially without knowledge of the area's climatology for that time of year. We therefore want to share the development and implementation process of a localized subseasonal (3-week) forecast, presenting actual weather variables, integrated into the existing Yr weather service. Yr is a weather app and website (www.yr.no) and is a collaboration between the Norwegian Meteorological Institute and the Norwegian Broadcasting Corporation (NRK). The subseasonal forecast has been operational since January 2024 and is available for the Nordic countries and the Baltic states. During the development process, we prioritized usability over maximizing forecast skill by engaging in co-production with existing Yr users through diary studies, user tests, and feedback forms. This approach provided valuable insights into presenting subseasonal forecasts that users find understandable and actionable. User feedback suggests that despite the inevitable decline in skill by week 3, localized forecasts presenting actual weather variable values—rather than aggregated anomalies—still provide significant value, as long as forecast uncertainty is clearly communicated. Creating a new forecast product through co-production is time-intensive and highly interactive, involving multiple iterations to test different methods for data dissemination. This process requires continual adjustments to both the design and forecast parameters. We will share our lessons learned by presenting not only the final forecast product but also the intermediate versions that were tested and deemed unfit based on user feedback. Lastly, we will discuss the integration of the subseasonal forecast into the Yr weather service, with a primary focus on obtaining consistency with existing forecast products (e.g. the 10-day forecast). Ensuring coherence across products is essential, as user feedback highlighted that most users base their decisions on combining information from different forecast products on Yr.