The CMIP6 Historical Simulation Datasets Produced by the Climate System Model CAMS-CSM

This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6).The model description,experiment design and model outputs are presented.Three members’historical experiments are conducted by CAMS-CSM,with two members starting from different initial conditions,and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions.The outputs of the historical experiments are also validated using observational data.It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities,including the surface air temperature,precipitation,and the equatorial thermocline.The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM.There are still some biases in the model that need further improvement.This paper can help the users to better understand the performance and the datasets of CAMS-CSM.

Climate Sensitivity and Feedbacks of BCC-CSM to Idealized CO2 Forcing from CMIP5 to CMIP6

Climate sensitivity represents the response of climate system to doubled CO2 concentration relative to the preindustrial level, which is one of the sources of uncertainty in climate projections. It is unclear how the climate sensitivity and feedbacks will change as a model system is upgraded from the Coupled Model Intercomparison Project Phase 5(CMIP5) to CMIP6. In this paper, we address this issue by comparing two versions of the Beijing Climate Center Climate System Model(BCC-CSM) participating in CMIP6 and CMIP5, i.e., BCC-CSM2-MR and BCC-CSM1.1 m,which have the same horizontal resolution but different physical parameterizations. The results show that the equilibrium climate sensitivity(ECS) of BCC-CSM slightly increases from CMIP5(2.94 K) to CMIP6(3.04 K). The small changes in the ECS result from compensation between decreased effective radiative forcing(ERF) and the increased net feedback. In contrast, the transient climate response(TCR) evidently decreases from 2.19 to 1.40 K, nearly the lower bound of the CMIP6 multimodel spread. The low TCR in BCC-CSM2-MR is mainly caused by the small ERF overly even though the ocean heat uptake(OHU) efficiency is substantially improved from that in BCC-CSM1.1 m.Cloud shortwave feedback(λSWCL) is found to be the major cause of the increased net feedback in BCC-CSM2-MR,mainly over the Southern Ocean. The strong positive λSWCL in BCC-CSM2-MR is coincidently related to the weakened sea ice-albedo feedback in the same region. This result is caused by reduced sea ice coverage simulated during the preindustrial cold season, which leads to reduced melting per 1-K global warming. As a result, in BCCCSM2-MR, reduced surface heat flux and strengthened static stability of the planetary boundary layer cause a decrease in low-level clouds and an increase in incident shortwave radiation. This study reveals the important compensation between λSWCL and sea ice-albedo feedback in the Southern Ocean.

The Annual Modes of Tropical Precipitation Simulated by the LASG/IAP Coupled Ocean-Atmosphere Model FGOALS_s1.1

This paper evaluates the performance of a coupled general circulation model FGOALS_s1.1 developed by LASG/IAP in simulating the annual modes of tropical precipitation.To understand the impacts of air-sea coupling on the annual modes,the result of an off-line simulation of the atmospheric component of FGOALS_s1.1,i.e.,LASG/IAP atmospheric general circulation model SAMIL,is also analyzed.FGOALS_s1.1 can reasonably reproduce major characteristics of the annual mean precipitation.Nonetheless,the coupled model shows overestimation of precipitation over the equatorial Pacific and tropical South Pacific,and underestimation of precipitation over the northern equatorial Pacific.The monsoon mode simulated by FGOALS_s1.1 shows an equatorial anti-symmetric structure,which is consistent with the observation.The bias of the coupled model in simulating monsoon mode resembles that of SAMIL,especially over the subtropics.The main deficiency of FGOALS_s1.1 is its failure in simulating the spring-fall asymmetric mode.This is attributed to the false phase of sea surface temperature anomaly(SSTA) annual cycle over the equatorial central-eastern Pacific and Indian Ocean,which leads to the bias of the Walker circulation over the equatorial Pacific and the anti-Walker circulation over the Indian Ocean in boreal spring and fall.In addition,the domains of the western North Pacific monsoon and Indian monsoon simulated by the coupled model are smaller than the observation.The study suggests that the bias of the fully coupled oceanatmosphere model can only be partly attributed to the bias of the atmospheric component.The performance of FGOALS_s1.1 in simulating the annual cycle of equatorial SST deserves further improvement.

Multi-Scheme Corrected Dynamic–Analogue Prediction of Summer Precipitation in Northeastern China Based on BCC_CSM

Based on summer precipitation hindcasts for 1991–2013 produced by the Beijing Climate Center Climate System Model(BCC_CSM), the relationship between precipitation prediction error in northeastern China(NEC) and global sea surface temperature is analyzed, and dynamic–analogue prediction is carried out to improve the summer precipitation prediction skill of BCC_CSM, through taking care of model historical analogue prediction error in the real-time output. Seven correction schemes such as the systematic bias correction, pure statistical correction, dynamic–analogue correction, and so on, are designed and compared. Independent hindcast results show that the 5-yr average anomaly correlation coefficient(ACC) of summer precipitation is respectively improved from –0.13/0.15 to 0.16/0.24 for 2009–13/1991–95 when using the equally weighted dynamic–analogue correction in the BCC_CSM prediction,which takes the arithmetical mean of the correction based on regional average error and that on grid point error. In addition, probabilistic prediction using the results from the multiple correction schemes is also performed and it leads to further improved 5-yr average prediction accuracy.