The semi-arid Sahel ecoregion is an established hotspot of land-atmosphere coupling. Ocean-land-atmosphere interactions received considerable attention by modeling studies in response to the devastating 1970s-90s Sahel drought, which models suggest was driven by sea-surface temperature (SST) anomalies and amplified by local vegetation-atmosphere feedbacks. Vegetation affects the atmosphere through biophysical feedbacks by altering the albedo, roughness, and transpiration and thereby modifying exchanges of energy, momentum, and moisture with the atmosphere. The current understanding of these potentially competing processes is primarily based on modeling studies, with biophysical feedbacks serving as a key uncertainty source in regional climate change projections among Earth System Models (ESMs). In order to reduce this uncertainty, it is critical to rigorously evaluate the representation of vegetation feedbacks in ESMs against an observational benchmark in order to diagnose systematic biases and their sources. However, it is challenging to successfully isolate vegetation’s feedbacks on the atmosphere, since the atmospheric control on vegetation growth dominates the atmospheric feedback response to vegetation anomalies and the atmosphere is simultaneously influenced by oceanic and terrestrial anomalies. In response to this challenge, a model-validated multivariate statistical method, Stepwise Generalized Equilibrium Feedback Assessment (SGEFA), is developed, which extracts the forcing of a slowly-evolving environmental variable [e.g. SST or leaf area index (LAI)] on the rapidly-evolving atmosphere. By applying SGEFA to observational and remotely-sensed data, an observational benchmark is established for Sahel vegetation feedbacks. In this work, the simulated responses in key atmospheric variables, including evapotranspiration, albedo, wind speed, vertical motion, temperature, stability, and rainfall, to Sahel LAI anomalies are statistically assessed in Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs through SGEFA. The dominant mechanism, such as albedo feedback, moisture recycling, or momentum feedback, in each ESM is evaluated against the observed benchmark. SGEFA facilitates a systematic assessment of model biases in land-atmosphere interactions.