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Climate engineering (CE) deployment would alter prevailing relationships between Earth system variables, making indicators and metrics used so far in the climate change assessment context less appropriate to assess CE measures. Achieving a comprehensive CE assessment requires a systematic and transparent reevaluation of the indicator selection process from Earth system variables. Here, we provide a first step towards such a systematic assessment of changes in correlations between Earth system variables following simulated deployment of different CE methods. We therefore analyze changes in the correlation structure of a broad set of Earth system variables for two conventional climate change scenarios without CE and with three idealized CE model experiments: (i) solar radiation management, (ii) large-scale afforestation, and (iii) ocean alkalinity enhancement. First, we investigate how the three CE scenarios alter prevailing correlations between Earth system variables when compared to an intermediate-high and a business-as-usual future climate change scenario. Second, we contrast the indicators identified for the non-CE climate change scenarios and the indicators identified when all five scenarios are considered. Finally, we use the identified indicator sets for an evaluation of the five climate change scenarios. We find that the additional indicators provide valuable information for the assessment of the CE measures, and their application hence allows for a more comprehensive and a comparative assessment of the mitigation and CE deployment scenarios.