An Overview of BCC Climate System Model Development and Application for Climate Change Studies

This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model （BCC_CSM） and its four component models （atmosphere, land surface, ocean, and sea ice）. Two recent versions are described： BCC_CSMI.1 with coarse resolution （approximately 2.8125°× 2.8125°） and BCC_CSMI.I（m） with moderate resolution （approximately 1.125°×1.125°）. Both versions are fully cou- pled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation. Both models well simulate the concentration and temporal evolution of atmospheric CO2 during the 20th century with anthropogenic CO2 emissions prescribed. Simulations using these two versions of the BCC_CSM model have been contributed to the Coupled Model Intercomparison Project phase five （CMIP5） in support of the Intergovernmental Panel on Climate Change （1PCC） Fifth Assessment Report （AR5）. These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections. Simulations of the 20th century climate using BCC-CSMI.1 and BCC_CSMI.I（m） are presented and validated, with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales. Simulations of climate during the last millennium and projections of climate change during the next century are also presented and discussed. Both BCC_CSMI.1 and BCC_CSMI.I（m） perform well when compared with other CMIP5 models. Preliminary analyses in- dicate that the higher resolution in BCC CSMI.I（m） improves the simulation of mean climate relative to BCC_CSMI.1, particularly on regional scales.

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.

A Simulation Study on the Extreme Temperature Events of the 20th Century by Using the BCC_AGCM

Extreme temperature events are simulated by using the Beijing Climate Center Atmospheric General Circulation Model （BCC_AGCM） in this paper. The model has been run for 136 yr with the observed ex- ternal forcing data including solar insolation, greenhouse gases, and monthly sea surface temperature （SST）. The daily maximum and minimum temperatures are simulated by the model, and 16 indices representing various extreme temperature events are calculated based on these two variables. The results show that the maximum of daily maximum temperature （TXX）, maximum of daily minimum （TNX）, minimum of daily maximum （TXN）, minimum of daily minimum （TNN）, warm days （TXg0p）, warm nights （TNg0p）, summer days （SU25）, tropical nights （TR20）, and warm spell duration index （WSDI） have increasing trends during the 20th century in most regions of the world, while the cold days （TX10p）, cold nights （TN10p）, and cold spell duration index （CSDI） have decreasing trends. The probability density function （PDF） of warm/cold days/nights for three periods of 1881-1950, 1951- 1978, and 1979-2003 is examined. It is found that before 1950, the cold day/night has the largest probability, while for the period of 1979-2003, it has the smallest probability. In contrast to the decreasing trend of cold days/nights, the PDF of warm days/nights exhibits an opposite trend. In addition, the frost days （FD） and ice days （ID） have decreasing trends, the growing season has lengthened, and the diurnal temperature range is getting smaller during the 20th century. A comparison of the above extreme temperature indices between the model output and NCEP data （taken as observation） for 1948 2000 indicates that the mean values and the trends of the simulated indices are close to the observations, and overall there is a high correlation between the simulated indices and the observations. But the simulated trends of FD, ID, growing season length, and diurnal temperature range are not consistent with the observations and their correlations are low or even negative. This indicates that the model is incapable to simulate these four indices although it has captured most indices of the extreme temperature events.

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.