Abstract
<jats:p>Land–atmosphere interactions play a critical role in subseasonal-to-seasonal (S2S) predictability by linking soil moisture memory, surface exchanges of heat and moisture, and atmospheric processes such as cloud formation and precipitation. This effort aims to identify, prioritize, and implement a concise set of process-oriented and operational metrics that can be used to evaluate how well Earth system models represent land–atmosphere coupling and its influence on S2S forecast skill. Building on discussions, the Process-Oriented Metrics Sub-Group synthesizes existing land–atmosphere coupling metrics and develops a short, prioritized list that is applicable to initialized reforecast datasets, AMIP simulations, and selected case studies across multiple modeling centers. For each metric, the group identifies the required variables, data characteristics, and, where available, appropriate observational benchmarks. These metrics will be used to assess land surface initialization, validate key land–atmosphere coupling processes, and quantify their impacts on prediction skill. The resulting synthesis report or paper will provide recommendations for improving process understanding, strengthening operational S2S forecast systems, and guiding future research and development. Ultimately, this work will demonstrate how targeted land–atmosphere metrics can support model evaluation, forecast improvement, and applications-oriented decision-making.</jats:p>