Temporal and Spatial Characteristics of Short-Term Cloud Feedback on Global and Local Interannual Climate Fluctuations from A-Train Observations

Abstract

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 ? 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 ?GG from regressing the global-mean cloud-induced TOA radiation anomaly ?RG with the global-mean surface temperature change ?TGS; 2) the local feedback parameter ?LL from regressing the local ?R with the local surface temperature change ?TS; and 3) the local feedback parameter ?GL from regressing global ?RG with local ?TS. Observations show significant temporal variability in the magnitudes and spatial patterns in ?GG and ?GL, whereas ?LL remains essentially time invariant for different cloud types. The global-mean net ?GG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative ?GG from low clouds and an increased positive ?GG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in ?GL is intrinsically linked to its dependence on global ?RG, and the scaling of ?GL with surface temperature change patterns to obtain global feedback ?GG 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.