This study evaluates the performance of a newly developed atmospheric chemistry-climate model, BCCAGCM_CUACE2.0 (Beijing Climate Center Atmospheric General Circulation Model_China Meteorological Administration Unified Atmospheric Chemistry Environment) model, for determining past (2010) and future (2050) tropospheric ozone (O-3) levels. The radiative forcing (RF), effective radiative forcing (ERF), and rapid adjustments (RAs, both atmospheric and cloud) due to changes in tropospheric O-3 are then simulated by using the model. The results show that the model reproduces the tropospheric O-3 distribution and the seasonal changes in O-3 surface concentration in 2010 reasonably compared with site observations throughout China. The global annual mean burden of tropospheric O-3 is simulated to have increased by 14.1 DU in 2010 relative to pre-industrial time, particularly in the Northern Hemisphere. Over the same period, tropospheric O-3 burden has increased by 21.1 DU in China, with the largest increase occurring over Southeast China. Although the simulated tropospheric O-3 burden exhibits a declining trend in global mean in the future, it increases over South Asia and Africa, according to the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The global annual mean ERF of tropospheric O-3 is estimated to be 0.25 W m(-2) in 1850-2010, and it is 0.50 W m(-2) over China. The corresponding atmospheric and cloud RAs caused by the increase of tropospheric O-3 are estimated to be 0.02 and 0.03 W m(-2), respectively. Under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, the annual mean tropospheric O-3 ERFs are projected to be 0.29 (0.24), 0.18 (0.32), 0.23 (0.32), and 0.25 (0.01) W m-2 over the globe (China), respectively.

We investigate the climate response to increased concentrations of black carbon (BC), as part of the Precipitation Driver Response Model Intercomparison Project (PDRMIP). A tenfold increase in BC is simulated by nine global coupled-climate models, producing a model median effective radiative forcing of 0.82 (ranging from 0.41 to 2.91) Wm(-2), and a warming of 0.67 (0.16 to 1.66) K globally and 1.24 (0.26 to 4.31) K in the Arctic. A strong positive instantaneous radiative forcing (median of 2.10 Wm(-2) based on five of the models) is countered by negative rapid adjustments (-0.64 Wm(-2) for the same five models), which dampen the total surface temperature signal. Unlike other drivers of climate change, the response of temperature and cloud profiles to the BC forcing is dominated by rapid adjustments. Low-level cloud amounts increase for all models, while higher-level clouds are diminished. The rapid temperature response is particularly strong above 400 h Pa, where increased atmospheric stabilization and reduced cloud cover contrast the response pattern of the other drivers. In conclusion, we find that this substantial increase in BC concentrations does have considerable impacts on important aspects of the climate system. However, some of these effects tend to offset one another, leaving a relatively small median global warming of 0.47 K per Wm(-2)-about 20% lower than the response to a doubling of CO2. Translating the tenfold increase in BC to the present-day impact of anthropogenic BC (given the emissions used in this work) would leave a warming of merely 0.07 K.

The precipitation adjustment and feedback framework is a useful tool for understanding global and regional precipitation changes. However, there is no definitive method for making the decomposition. In this study we highlight important differences which arise in results due to methodological choices. The responses to five different forcing agents (CO2, CH4, SO4, black carbon, and solar insolation) are analyzed using global climate model simulations. Three decomposition methods are compared: using fixed sea surface temperature experiments (fSST), regressing transient climate change after an abrupt forcing (regression), and separating based on timescale using the first year of coupled simulations (YR1). The YR1 method is found to incorporate significant SST-driven feedbacks into the adjustment and is therefore not suitable for making the decomposition. Globally, the regression and fSST methods produce generally consistent results; however, the regression values are dependent on the number of years analyzed and have considerably larger uncertainties. Regionally, there are substantial differences between methods. The pattern of change calculated using regression reverses sign in many regions as the number of years analyzed increases. This makes it difficult to establish what effects are included in the decomposition. The fSST method provides a more clear-cut separation in terms of what physical drivers are included in each component. The fSST results are less affected by methodological choices and exhibit much less variability. We find that the precipitation adjustment is weakly affected by the choice of SST climatology.