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• W1427774344 abstract "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 cli- 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 tempera- ture 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 ±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 Ta 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 Ta biases in the mid-strato- sphere can be attributed to the radiative ozone feedback process." @default.
• W1427774344 created "2016-06-24" @default.
• W1427774344 creator A5022178501 @default.
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• W1427774344 date "2015-03-11" @default.
• W1427774344 modified "2023-10-18" @default.
• W1427774344 title "Understanding the Global Surface-Atmosphere Energy Balance in FGOALS-s2 through an Attribution Analysis of the Global Temperature Biases" @default.
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• W1427774344 doi "https://doi.org/10.3878/aosl20150019" @default.
• W1427774344 hasPublicationYear "2015" @default.
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