AbstractObservations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability within the A-Train era (July 2002–June 2017). Short-term cloud feedbacks by cloud type are investigated both globally and locally by three different definitions in the literature: 1) the global-mean cloud feedback parameter λGG from regressing the global-mean cloud-induced TOA radiation anomaly ΔRG with the global-mean surface temperature change ΔTGS; 2) the local feedback parameter λLL from regressing the local ΔR with the local surface temperature change ΔTS; and 3) the local feedback parameter λGL from regressing global ΔRG with local ΔTS. Observations show significant temporal variability in the magnitudes and spatial patterns in λGG and λGL, whereas λLL remains essentially time invariant for different cloud types. The global-mean net λGG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative λGG from low clouds and an increased positive λGG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in λGL is intrinsically linked to its dependence on global ΔRG, and the scaling of λGL with surface temperature change patterns to obtain global feedback λGG does not hold. Despite the shortness of the A-Train record, statistically robust signals can be obtained for different cloud types and regions of interest.