We examined inter- and intra-individual covariations of mood and alcohol consumption in a sample of 171 light, medium, and heavy alcohol consumers aged 21 and over who reported daily about drinking and mood for a period of up to 2 years. The sample was recruited by advertisements in local newspapers and referral from former respondents in Northern Vermont, USA, between July 1997 and September 2000. Participants reported daily alcohol consumption and mood via interactive voice response (IVR) technology. Within-subject correlations were calculated for each individual separately and analyzed via cluster analysis. The cluster solution was subsequently used as a categorical Level-2 predictor in hierarchical linear modeling of daily alcohol consumption. Cluster analyses of the within-subject correlations revealed four clusters: (1) emotion-inhibited drinking (drinking combined with reduced emotional arousal, n=12); (2) "positive emotion drinking" (drinking in combination with positive mood, n=69); (3) "stress drinking" (drinking combined with negative mood, n=12); and (4) "non-emotional drinking" (no relationship between alcohol consumption and mood, n=78). Hierarchical linear modeling (HLM) analyses revealed that a significant amount of random variance of the Level-1 mood slopes (38% and 40%) was accounted for by the clusters, demonstrating the predictive power of cluster membership on individual drinking patterns. Although Cluster 3 members (stress drinking) did not report significantly higher levels of alcohol consumption, they were more likely to report current and lifetime dependence symptoms. The results point to the existence of stable, but diverse drinking patterns among non-clinical alcohol consumers with potentially different implications for development into alcohol abuse and dependence.