In order to avoid contamination of time varying external forcing to cloud feedback calculations and test the closure of radiative kernel method for quantifying radiative feedbacks based on short-term climate variations, we extend our previous work (Zhang et al., 2018) by analyzing radiative feedbacks at the top of atmosphere (TOA) based on global climate model simulations with fixed external forcing. Clear-sky radiation closure tests show that the radiative kernel method can reconstruct the global pattern and seasonal cycle of TOA radiation budget within the uncertainty of 10% or less. All-sky radiation feedback closure tests show that the combined Kernel-Gregory approach can properly decompose the zonal-mean total radiative feedback into individual feedbacks (i.e., Planck, lapse rate, water vapor, surface albedo and cloud feedbacks). For the global-mean non-cloud feedbacks, our results show a good agreement with the feedbacks derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the Community Earth System Model Large Ensemble (CESM-LE) model simulations. With respect to the cloud feedback, both shortwave and longwave global-mean cloud feedbacks are nearly zero, which are different from previous studies. While the shortwave cloud feedback in our calculations is consistent with CMIP5 ensemble mean, the longwave cloud feedback is closer to CESM-LE results. Relative to the tropics (30°S–30°N), the lapse rate feedback is the largest contributor to Arctic (60–90°N) amplification among all feedbacks, followed by surface albedo feedback and Planck feedback deviation from its global mean. Interestingly, except for the surface albedo feedback, other feedbacks are almost the same for Arctic and Antarctic (60–90°S). The comparison of radiaitive feedbacks calculated from available CMIP6 models to these new results will also be discussed at the meeting.

Zhang, R., et al. (2018). Local radiative feedbacks over the Arctic based on observed short-term climate variations. Geophysical Research Letters, 45, 5761–5770. https://doi.org/10.1029/2018GL077852