Solar reflective roofs (also called white or cool roofs) are a common urban heat mitigation strategy. By reflecting more sunlight than regular roofs, white roofs experience lower surface temperatures and provide cooling comforts to the urban environment. The effectiveness of white roofs, quantified by the surface temperature difference between white roofs and regular roofs ΔTs, is known to vary spatially. However, a theoretical framework that enables diagnosis of key controlling factors for the effectiveness remains elusive. A common perception is that ΔTs is mainly determined by the solar radiation that reaches the roof surface. In places with more solar radiation, painting the roof white is thought to be more effective. In this study, we develop a theoretical framework based on the surface energy balance equation, combined with global simulations generated by an improved Earth System Model (CESM2), to understand the key factors controlling the spatial variability of white roof effectiveness. We demonstrate that the spatial variability of ΔTs, when normalized by the albedo difference between white roofs and regular roofs (Δα), is also controlled by an energy distribution factor that encodes the efficiencies of surface energy balance components in dissipating heat. The roof properties like thermal admittance and water holding capacity, as well as the meteorological conditions like precipitation, wind speed should also be considered for evaluating the local effectiveness of white roofs. The proposed framework can be employed for quick assessments of white roof impacts and help scientists and urban designers determine where we should paint the roof white to maximize the cooling benefits.