Quantitative computed tomography (CT)-based characterization of bronchial metrics is increasingly being used to investigate chronic obstructive pulmonary disease (COPD)-related phenotypes. Automated methods for airway measurements benefit large multi-site studies by reducing cost and subjectivity errors. Critical challenges for CT-based analysis of airway morphology are related to location of lumen and wall transitions in the presence of varying scales and intensity-contrasts from proximal to distal sites. This paper introduces locally adaptive half-max methods to locate airway lumen and wall transitions and compute cross-sectional lumen area and wall-thickness. Also, the method uses a consistency analysis of wall-thickness to avoid adjoining-structure-artifacts. Experimental results show that computed bronchial measures at individual anatomic airway tree locations are repeat CT scan reproducible with intra-class correlation coefficient (ICC) values exceeding 0.9 and 0.8 for lumen-area and wall-thickness, respectively. Observed ICC values for derived morphologic measures, e.g., lumen-area compactness ($\text{ICC} > 0.67$) and tapering ($\text{ICC} > 0.47$) are relatively lower.