Stream processing has emerged as the major paradigm to tackle the digital information flood. Within stream processing, complex event processing (CEP) represents a pattern-based approach that enables automated situation detection and real-time monitoring. One deficit of CEP applications is the negligence of the evolution of situations, as only two states are differentiated with regard to the occurrence of situations: detected and not detected. This behavior might lead to critical situations due to a decreased comprehensibility for operators. On the other side situation awareness (SAW) is a recognized psychological model describing the characteristics and mechanisms of operators responsible for complex systems. In this paper, we combine the technological method CEP with the human factors identified in SAW to determine the missing links. In order to bridge the gap, this paper presents an extension of the state-of-the-art situation lifecycle to support SAW to its full extent. Furthermore, requirements for situation-aware CEP applications are derived and a methodology to develop such applications is proposed.