BCC-CSM2-MR模式对中国陆面过程模拟能力评估

Evaluating the Performance of BCC-CSM2-MR Model in Simulating the Land Surface Processes in China

利用BCC-CSM2-MR模式(北京气候中心-气候系统模式第二版本-中等分辨率)参与CMIP6(第六次国际耦合模式比较计划)的历史试验模拟数据,与GLDAS(全球陆地资料同化系统)数据集和站点观测资料进行比较,系统评估了BCC-CSM2-MR模式对中国地区地表温度、上层(0~10 cm)土壤湿度、地表能量平衡分量等陆面变量的模拟能力,并进一步探讨了引起模式偏差的原因.结果表明:模式可以较好地模拟出各陆面变量的空间分布形势及变率,但在强度上还存在不同程度的偏差.与GLDAS数据相比,除对东南地区夏季地表温度有所高估外,模式在全年大部分时间低估了中国大部分区域的地表温度,尤其对青藏高原地区冬春季地表温度的低估显著,进一步误差分析发现,模式对东南地区夏季降水的低估导致了对向下短波辐射的高估,进而造成了对地表温度的高估,而模式对青藏高原地区地表反照率的高估导致了对向下净短波辐射的低估,最终引起了对地表温度的低估,尤其在冬春季更加明显.另外,模式在所有季节均明显低估了东南地区的上层土壤湿度,而高估了青藏高原地区冬春季的上层土壤湿度,这主要由于模式对降水的模拟偏差所致,而模式对青藏高原地区冬春季上层土壤湿度和10 m风速的高估又共同引起了对地表向上潜热通量的高估.

This study compares the CMIP6(Coupled Model Intercomparison Project Phase 6)historical experiment results of BCC-CSM2-MR(Beijing Climate Center-Climate System Model-Medium Reslution)with GLDAS(Global Land Data Assimilation System)dataset and site-observed data to systematically evaluate the performance of BCC-CSM2-MR in simulating the land surface variables,such as surface soil temperature,upper soil moisture and surface energy balance components in China.And the causes of the model biases are also deeply discussed.The spatial correlation coefficient,temporal correlation coefficient,Taylor score and root mean square error between the observed data and GLDAS data and the model data are calculated to quantitatively analyze the simulation ability of BCC-CSM2-MR to land surface variables.The results show that the model can well simulate the spatial distribution and variability of land surface variables,but the model biases in quantity are still obvious.The spatial correlation coefficient and Taylor score between the simulated land surface soil temperature,upward net long wave radiation flux and surface upward latent heat flux by BCC-CSM2-MR and GLDAS are above 0.8 in each season,and it shows that the simulation performance of above variables is relatively great.Compared with GLDAS data,the model overestimates the summer surface soil temperature over southeastern China,but it tends to underestimate the surface soil temperature over most China in all seasons with much larger underestimation over the Qinghai-Xizang plateau in winter and spring.From the model error analysis,it can be concluded that the precipitation underestimated by the model leads to the overestimated surface downward short-wave radiation over southeastern China in summer,which leads to the overestimated surface soil temperature there.The surface albedo overestimated by the model results in the underestimated surface net downward short-wave radiation over the Qinghai-Xizang plateau,which further leads to the underestimated surface soil temperature,obviously in winter and spring.In addition,the model seriously underestimates(overestimates)the upper soil moisture over southeastern China in all seasons(Qinghai-Xizang plateau in winter and spring),and the simulation effect of the characteristics of time evolution of deep soil time is better than that of upper soil,this is mainly resulted from the biases in the modeled precipitation.Meanwhile,the overestimation of upper soil moisture and 10m wind speed leads to the overestimated surface upward latent heat flux over Qinghai-Xizang Plateau in the winter and spring.After the model evaluation,it can be found that the simulation performance of BCC-CSM2-MR to land surface variables still needs to be improved and the causes of the model biases are complicated.