Much insight has been gained about the processes contributing to cloud feedbacks in climate models by decomposing them into components attributable to changes in cloud amount, altitude, and optical depth. However, there remains ambiguity regarding the nature of the cloud changes that drive some of these components. For example, how much of the robustly simulated negative optical depth feedback at high latitudes comes from (1) increases in the relative frequency of occurrence of thick clouds at the expense of thin clouds versus (2) increases in the albedo of clouds of a given morphology? Here we bring together two techniques – cloud radiative kernel analysis which separates cloud feedbacks into amount, altitude, and optical depth components – and cloud regime analysis which separates cloud feedbacks into within-regime and between-regime components. Specifically, we match daily cloud fields from several CMIP5 and CMIP6 models to eight cloud regimes determined from ISCCP observations, and perform this detailed breakdown for their climate response in uniform 4 K warming experiments. We demonstrate that together, these complementary techniques provide key insights into cloud feedbacks in models. This aids in interpreting which processes drive the feedback on average, which drive its inter-model spread, and which processes need attention when determining how to correct biases in models.

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. It is supported by the Regional and Global Model Analysis Program of the Office of Science at the DOE. IM Release # LLNL-ABS-825382.