This talk focuses on the use of idealized models to study how surface temperature and the hydrologic cycle respond to perturbations in different radiation components at the surface. Simple quantitative driver-response relationships derived from these models are shown to have wide explanatory power: reconciling “paradoxes” in observations of climate variables, understanding certain biases in GCM output, and why the sensitivity of the water cycle is different to greenhouse gases and aerosols. This also allows for the rapid formulation and first-order studies of new climate change scenarios.