Computing and Partitioning Cloud Feedbacks using Cloud 1 Property Histograms . 2 Part II : Attribution to Changes in Cloud Amount , Altitude , and 3 Optical Depth

8 Cloud radiative kernels and histograms of cloud fraction, both as functions of cloud top 9 pressure and optical depth, are used to quantify cloud amount, altitude, and optical depth 10 feedbacks. The analysis is applied to doubled CO2 simulations from eleven global climate 11 models in the Cloud Feedback Model Intercomparison Project. 12 Global, annual, and ensemble mean longwave (LW) and shortwave (SW) cloud feedbacks 13 are positive, with the latter nearly twice as as large as the former. The robust increase 14 in cloud top altitude is the dominant contributor to the positive LW cloud feedback. The 15 negative impact of reductions in cloud amount offsets more than half of the positive impact of 16 rising clouds on LW cloud feedback, but the magnitude of compensation varies considerably 17 across models. In contrast, robust reductions in cloud amount make a large and virtually 18 unopposed positive contribution to SW cloud feedback, though the inter-model spread is 19 greater than for any other individual feedback component. Overall reductions in cloud 20 amount have twice as large an impact on SW fluxes as on LW fluxes such that the net cloud 21 amount feedback is moderately positive, with no models exhibiting a negative value. As 22 a consequence of large but partially offsetting effects of cloud amount reductions on LW 23 and SW feedbacks, both the mean and inter-model spread in net cloud amount feedback 24 are smaller than those of the net cloud altitude feedback. Finally, we find that the large 25 negative cloud feedback at high latitudes results from robust increases in cloud optical depth, 26 not from increases in total cloud amount as is commonly assumed. 27