Rotated Principal component analysis (PCA) is applied to the combined vertical profiles of apparent heat source Q1 and apparent moisture sink Q2 from both disturbed and undisturbed periods of the Australian summer monsoon season. The data represent the heating and drying within two radiosonde arrays afforded by the Australian Monsoon Experiment (AMEX), The aim here is to identify dominant modes of variability in combined vertical profiles of Q1 and Q2. Rotation of the principal components (PCs)-done to assure stable, physically meaningful components-yields several PCs, deemed here to be statistically significant. The variation of individual Q1 and Q2 profiles from the mean profile can be expressed as linear combinations of the PCs; therefore, determination of the relative importance of each PC (through examination of its score) during differing convective conditions provides insight into their physical meaning. For instance, the contribution of PC 1 (that mode of variability that explains the max... Abstract Rotated Principal component analysis (PCA) is applied to the combined vertical profiles of apparent heat source Q1 and apparent moisture sink Q2 from both disturbed and undisturbed periods of the Australian summer monsoon season. The data represent the heating and drying within two radiosonde arrays afforded by the Australian Monsoon Experiment (AMEX), The aim here is to identify dominant modes of variability in combined vertical profiles of Q1 and Q2. Rotation of the principal components (PCs)-done to assure stable, physically meaningful components-yields several PCs, deemed here to be statistically significant. The variation of individual Q1 and Q2 profiles from the mean profile can be expressed as linear combinations of the PCs; therefore, determination of the relative importance of each PC (through examination of its score) during differing convective conditions provides insight into their physical meaning. For instance, the contribution of PC 1 (that mode of variability that explains the max...