Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output. Land–atmosphere (L–A) interactions are crucial for understanding convective processes, climate feedbacks, droughts, heatwaves, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development. A key goal of the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is to parameterize and characterize the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. Incorporating L–A metrics, especially LoCo metrics, into climate model diagnostic process streams is critical, but data storage constraints typically prevent routine archival of the hourly data needed for these calculations. This study outlines a reasonable data request to adequately characterize sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyze, and better understand L–A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behavior. Higher-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in L–A coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models. The study highlights the complexity of the L–A system, showing the many interaction pathways between individual component parts. Sub-daily data are required to accurately capture the long-term signal of L–A coupling characterized by statistically based L–A metrics. Sub-daily output of fields at the L–A interface must be saved as part of the routine diagnostic output from long simulations. The data request includes hourly 3D atmospheric profiles of potential temperature, humidity, and three-dimensional winds; hourly 3D soil profiles of moisture content and temperature; and hourly 2D fields of surface pressure, BL height, precipitation, sensible heat flux, evapotranspiration, and other relevant variables. The data request is divided into three categories based on the analyses that would be enabled and by the work required by model developers. Request A focuses on standard model output of surface fields saved at higher-frequency intervals, Request B focuses on the archival of variables in the lowest 300 mb of the troposphere, and Request C requires in-code modifications to calculate average properties within and above the BL. These data requests aim to improve the accuracy and understanding of L–A coupling in climate models.Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output. Land–atmosphere (L–A) interactions are crucial for understanding convective processes, climate feedbacks, droughts, heatwaves, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development. A key goal of the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is to parameterize and characterize the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. Incorporating L–A metrics, especially LoCo metrics, into climate model diagnostic process streams is critical, but data storage constraints typically prevent routine archival of the hourly data needed for these calculations. This study outlines a reasonable data request to adequately characterize sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyze, and better understand L–A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behavior. Higher-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in L–A coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models. The study highlights the complexity of the L–A system, showing the many interaction pathways between individual component parts. Sub-daily data are required to accurately capture the long-term signal of L–A coupling characterized by statistically based L–A metrics. Sub-daily output of fields at the L–A interface must be saved as part of the routine diagnostic output from long simulations. The data request includes hourly 3D atmospheric profiles of potential temperature, humidity, and three-dimensional winds; hourly 3D soil profiles of moisture content and temperature; and hourly 2D fields of surface pressure, BL height, precipitation, sensible heat flux, evapotranspiration, and other relevant variables. The data request is divided into three categories based on the analyses that would be enabled and by the work required by model developers. Request A focuses on standard model output of surface fields saved at higher-frequency intervals, Request B focuses on the archival of variables in the lowest 300 mb of the troposphere, and Request C requires in-code modifications to calculate average properties within and above the BL. These data requests aim to improve the accuracy and understanding of L–A coupling in climate models.