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Human communication is a dynamical and interactive process that naturally induces an active flow of interpersonal coordination, and synchrony, along various behavioral dimensions. Assessing and characterizing the temporal dynamics of synchrony during an interaction is essential for fully understanding the human communication mechanisms. In this work, we focus on uncovering the temporal variability patterns of synchrony in visual gesture and vocal behavior in affectively rich interactions. We propose a statistical scheme to robustly quantify the turn-wise interpersonal synchrony. The analysis of the synchrony dynamics measure relies heavily on functional data analysis techniques. Our analysis results reveal that: 1) the dynamical patterns of interpersonal synchrony differ depending on the global emotions of an interaction dyad; 2) there generally exists a tight dynamical emotion-synchrony coupling over the interaction. These observations corroborate that interpersonal behavioral synchrony is a critical manifestation of the underlying affective processes, shedding light toward improved affective interaction modeling and automatic emotion recognition.