Climate risk analytics involves assessments of how the risk from various hazards such as heat, precipitation, wind, drought, fire, flood, etc. evolve in a changing climate. Translating information from global climate models into climate information at regional and local scales, also referred to as downscaling, is a critical piece of these assessments. Focusing on different types of hazards, I’ll highlight the cloud-based computational pipelines used to quantify climate risk and that incorporate data from many different sources as well as simulations from complex geophysical models, highlighting the role that the different types of downscaling play.