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 feedb...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.展开更多
In this paper,we investigate the agegraphic dark energy(ADE) model by including the sign-changeable interaction between ADE and dark matter in non-flat universe.The interaction Q can change its sign from Q < 0 to Q...In this paper,we investigate the agegraphic dark energy(ADE) model by including the sign-changeable interaction between ADE and dark matter in non-flat universe.The interaction Q can change its sign from Q < 0 to Q > 0 as the universe expands.This indicates that at first dark matter decays to ADE,and then ADE decays to dark matter.We study the dynamical behavior of the model by using the phase-plane analysis.It is shown numerically that the coupling constant β plays an important role in the evolution of the universe.The equation of state(Eo S) of ADE with the sign-changeable interaction is more likely to cross the phantom divide w_d =-1 from top to bottom with the increasing of the |β|.Whereas in ADE model with usual interaction,wd can cross the phantom divide from bottom to top.We also find that our model is consistent with the observational data.展开更多
基金jointly supported by the Special Fund for Public Welfare Industry(Meteorology)(Grant No.GYHY201406001)Science Foundation of the Chinese Academy of Sciences(Grant No.XDA11010402)the National Natural Science Foundation of China(Grant No.91437105)
文摘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.
基金Supported by National Nature Science Foundation of China under Grant No.51405181Natural Science Foundation for Youths of Jiangsu Province under Grant No.BK20130407Colleges and Universities Natural Science Fundation of Jiangsu Province under Grant No.13KJB460001
文摘In this paper,we investigate the agegraphic dark energy(ADE) model by including the sign-changeable interaction between ADE and dark matter in non-flat universe.The interaction Q can change its sign from Q < 0 to Q > 0 as the universe expands.This indicates that at first dark matter decays to ADE,and then ADE decays to dark matter.We study the dynamical behavior of the model by using the phase-plane analysis.It is shown numerically that the coupling constant β plays an important role in the evolution of the universe.The equation of state(Eo S) of ADE with the sign-changeable interaction is more likely to cross the phantom divide w_d =-1 from top to bottom with the increasing of the |β|.Whereas in ADE model with usual interaction,wd can cross the phantom divide from bottom to top.We also find that our model is consistent with the observational data.
