We assess the detectability of COVID-like emissions reductions in global atmospheric CO₂ concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO₂ sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions. Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO₂. COVID-driven changes in the simulated interhemispheric CO₂ gradient and column-averaged dry air mole fractions of CO₂ (total column or XCO₂) are eclipsed by large internal variability. Carbon-concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions-driven signal in the atmosphere carbon reservoir and further confound signal detection.