The resilience of the Air Traffic Management (ATM) system to disturbances is required to maintain high operation performance. Before it can be improved, the resilience of the ATM system must be quantified. The measurement of resilience requires knowledge of a system reference state. This thesis proposes a novel methodology to detect disruptions without a pre-specified reference state and to quantify airspace resilience to disturbances. The method utilises residual-based anomaly detection to model a reference state based on historical values and detect deviations from it. The method has been tested in assessing the resilience of arrival time (airspace state)to high winds (disturbance) in 9 airports worldwide for a year. The results have shown that the method is capable of detecting disruptions as well as airports experiencing high wind conditions tend to be more resilient to them.