Understanding the Global Surface-Atmosphere Energy Balance in FGOALS-s2 through an Attribution Analysis of the Global Temperature Biases

Based on an attribution analysis of the global mean temperature biases in the Flexible Global Ocean- AtmOsphere-Land System model, spectral version 2 （FGOALS-s2） through a coupled atmosphere-surface ch- mate feedback-response analysis method （CFRAM）, the model＇s global surface-atmosphere energy balance in boreal winter and summer is examined. Within the en- ergy-balance-based CFRAM system, the model temperature biases are attributed to energy perturbations resulting from model biases in individual radiative and non-radia- tive processes in the atmosphere and at the surface. The results show that, although the global mean surface tem- perature （Ts） bias is only 0.38 K in January and 1.70 K in July, and the atmospheric temperature （Ta） biases from the troposphere to the stratosphere are only around ＋3 K at most, the temperature biases due to model biases in rep- resenting the individual radiative and non-radiative proc- esses are considerably large （over -4-10 K at most）. Spe- cifically, the global cold radiative Ts bias, mainly due to the overestimated surface albedo, is compensated for by the global warm non-radiative Ts bias that is mainly due to the overestimated downward surface heat fluxes. The model biases in non-radiative processes in the lower tro- posphere （up to 5-15 K） are relatively much larger than in upper levels, which are mainly responsible for the warm Ta biases there. In contrast, the global mean cold ira biases in the mid-to-upper troposphere are mainly dominated by radiative processes. The warm/cold Ta biases in the lower/upper stratosphere are dominated by non-radiative processes, while the warm ira biases in the mid-strato- sphere can be attributed to the radiative ozone feedback process.