Typically, a climate change risk assessment focuses on individual sectors or hazards. However, interdependencies between climate risks manifest themselves via functional, physical, geographical, economic, policy and social mechanisms. These can occur over a range of spatial or temporal scales and with different strengths of coupling. Three case studies are used to demonstrate how interdependencies can significantly alter the nature and magnitude of risk, and, consequently, investment priorities for adaptation. The three examples explore interdependencies that arise from (1) climate loading dependence; (2) mediation of two climate impacts by physical processes operating over large spatial extents; and, (3) multiple risks that are influenced by shared climatic and socio-economic drivers. Drawing upon learning from these case studies, and other work, a framework for the analysis and consideration of interdependencies in climate change risk assessment has been developed. This is an iterative learning loop that involves defining the system, scoping interaction mechanisms, applying appropriate modelling tools, identifying vulnerabilities and opportunities, and assessing the performance of adaptation interventions.