scholarly journals The Beijing Climate Center Climate System Model (BCC-CSM): Main Progress from CMIP5 to CMIP6

2018 ◽  
Author(s):  
Tongwen Wu ◽  
Yixiong Lu ◽  
Yongjie Fang ◽  
Xiaoge Xin ◽  
Laurent Li ◽  
...  

Abstract. Main progresses of Beijing Climate Center (BCC) climate system model from the phase five of the Coupled Model Intercomparison Project (CMIP5) to its phase six (CMIP6) are presented, in terms of physical parameterizations and models performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, and BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include (a) energy budget at top of the atmosphere, (b) surface air temperature, precipitation, and atmospheric circulation for global and East Asia regions, (c) sea ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC), and (d) climate variations at different time scales such as global warming trend in the 20th century, stratospheric quasi-biennial oscillation (QBO), Madden-Julian Oscillation (MJO) and diurnal cycle of precipitation. Compared to BCC CMIP5 models, BCC CMIP6 models show significant improvements in many aspects including: tropospheric air temperature and circulation at global and regional scale in East Asia, climate variability at different time scales such as QBO, MJO, diurnal cycle of precipitation, and long-term trend of surface air temperature.

2019 ◽  
Vol 12 (4) ◽  
pp. 1573-1600 ◽  
Author(s):  
Tongwen Wu ◽  
Yixiong Lu ◽  
Yongjie Fang ◽  
Xiaoge Xin ◽  
Laurent Li ◽  
...  

Abstract. The main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMIP6) are presented, in terms of physical parameterizations and model performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, whereas BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include the following: (a) the energy budget at top-of-atmosphere; (b) surface air temperature, precipitation, and atmospheric circulation for the global and East Asia regions; (c) the sea surface temperature (SST) in the tropical Pacific; (d) sea-ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC); and (e) climate variations at different timescales, such as the global warming trend in the 20th century, the stratospheric quasi-biennial oscillation (QBO), the Madden–Julian Oscillation (MJO), and the diurnal cycle of precipitation. Compared with BCC-CSM1.1m, BCC-CSM2-MR shows significant improvements in many aspects including the tropospheric air temperature and circulation at global and regional scales in East Asia and climate variability at different timescales, such as the QBO, the MJO, the diurnal cycle of precipitation, interannual variations of SST in the equatorial Pacific, and the long-term trend of surface air temperature.


2021 ◽  
Vol 14 (5) ◽  
pp. 2977-3006
Author(s):  
Tongwen Wu ◽  
Rucong Yu ◽  
Yixiong Lu ◽  
Weihua Jie ◽  
Yongjie Fang ◽  
...  

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model (T266 in the atmosphere and 1/4∘ latitude × 1/4∘ longitude in the ocean). Its development is on the basis of the medium-resolution version BCC-CSM2-MR (T106 in the atmosphere and 1∘ latitude × 1∘ longitude in the ocean) which is the baseline for BCC participation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamical core and physical processes. BCC-CSM2-HR is evaluated for historical climate simulations from 1950 to 2014, performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. Observed global warming trends of surface air temperature from 1950 to 2014 are well captured by both BCC-CSM2-MR and BCC-CSM2-HR. Present-day basic atmospheric mean states during the period from 1995 to 2014 are then evaluated at global scale, followed by an assessment on climate variabilities in the tropics including the tropical cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR represents the global energy balance well and can realistically reproduce the main patterns of atmospheric temperature and wind, precipitation, land surface air temperature, and sea surface temperature (SST). It also improves the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of the double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, almost disappears in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, and the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observations than their counterparts in BCC-CSM2-MR. Some imperfections are, however, noted in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold SST biases and the insufficient number of tropical cyclones in the North Atlantic.


Author(s):  
Xinyao Rong ◽  
Jian Li ◽  
Haoming Chen ◽  
Jingzhi Su ◽  
Lijuan Hua ◽  
...  

AbstractThis 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.


2005 ◽  
Vol 18 (17) ◽  
pp. 3552-3570 ◽  
Author(s):  
Hugues Goosse ◽  
Marika M. Holland

Abstract Several mechanisms have been proposed to explain natural climate variability in the Arctic. These include processes related to the influence of the North Atlantic Oscillation/Arctic Oscillation (NAO/AO), anticyclonic/cyclonic regimes, changes in the oceanic and atmospheric North Atlantic–Arctic exchange, and changes in the Atlantic meridional overturning circulation. After a brief critical review, the influence and interrelation of the above processes in a long climate integration of the Community Climate System Model, version 2 (CCSM2) are examined. The analysis is based on the time series of surface air temperature integrated northward of 70°N, which serves as a useful proxy for general Arctic climate conditions. This gives a large-scale view of the evolution of Arctic climate. It is found that changes in oceanic exchange and heat transport in the Barents Sea dominate in forcing the Arctic surface air temperature variability in CCSM2. Changes in atmospheric circulation are consistent with a wind forcing of this variability, while changes in the deep overturning circulation in the Atlantic are more weakly related in CCSM2. Over some time periods, the NAO/AO is significantly related to these changes in Arctic climate conditions. However, this is not robust over longer time scales.


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