Abstract. Monitoring the terrestrial carbon cycle for responses to disturbances, caused for example by extreme climate events and insect outbreaks, has the potential to provide early warnings about ecosystem change. However, our capability to detect these carbon balance responses by atmospheric CO₂ monitoring remains unknown despite sub-ppm comparability of many well-calibrated CO₂ measurement sites. Here, this study explores how accurately atmospheric CO₂ and transport models can detect imposed carbon flux anomalies against a background terrestrial flux. Air mass back trajectories from three CO₂ monitoring stations in the central U.S. Rocky Mountains for one year (2008) were computationally simulated. To simulate reduced CO₂ uptake, a constant +0.2 µmol C m⁻¹ s⁻² anomaly was added to all surface fluxes within perturbation domains of varying size. A spatially and temporally uniform 10°×10° +0.2 µmol C m⁻² s⁻¹ flux anomaly (+6 Tg C m⁻¹) was detectable above a comprehensive model-data mismatch detection threshold in a large majority of months at each site, but only when the perturbation was located in the central Mountain West. The intensity of the perturbation and its area were important to detection, but the effect of area declined exponentially with increasing source-to-station distance. To further evaluate response, a more realistic spatiotemporally varying drought extracted from a dynamic global vegetation model with a monthly varying perturbation area (1°×1° to 5°×5°) and higher peak intensity (+0.8 µmol C m⁻² s⁻¹) was applied. Detectability of excess CO₂ from this experiment by the nearest CO₂ site (Utah) was similar to detectability of the largest (10°×10°) uniform perturbation. These experiments demonstrate disturbance and drought related carbon-cycle perturbations do create a discernible impact on the composite signal of atmospheric CO₂ if sufficiently proximal to a measurement station.