基于多模式的青藏高原前冬降水预测性能评估

Evaluation of multi-model precipitation simulation over the Tibetan Plateau in early winter

基于目前主流气候业务模式系统(BCC_CSM 1.1、ECMWF_System 5、NCEP_CFSv 2、TCC_MRI-CGCM 3),从确定性预报角度评估多种模式对青藏高原前冬降水的预测性能。结果表明:多模式均能体现出青藏高原前冬(11—12月)降水空间分布型,但对降水量级存在普遍高估的现象,其中,来自BCC的模式能反映出降水全区一致型和南北反向型主模态的时空演变特征,EC模式高估第一模态的主导作用。多模式对降水历史回报以正技巧为主,BCC模式的预报技巧最优,TCC仅对青藏高原北部预测较好。从可预报性来源的角度分析发现,赤道中东太平洋海温指数(Ni?o 3.4)和印度洋偶极子(IOD)正位相对提升模式预测技巧具有很好的指示性;BCC模式能预测出2018年高原前冬降水异常趋势,在于其对影响青藏高原降水异常的关键环流型具有一定预测能力。

The prediction performance of four seasonal prediction model systems(BCC_CSM 1.1,ECMWF_System 5,CFSv 2,and TCC_MRI-CGCM 3)was evaluated from a deterministic perspective.Focusing on the spatial distribution and temporal variation of precipitation climatology in early winter,BCC_CSM 1.1 exhibited the best prediction performance among the models.Additionally,TCC_MRI-CGCM 3 performed well in capturing the interannual variability of precipitation,followed by BCC_CSM 1.1.All models effectively simulated regional-uniform precipitation,with BCC_CSM 1.1 exhibiting the highest time correlation coefficient and TCC_MRI-CGCM 3 showing the highest pattern correlation coefficient.Although all models could reproduce the north-south reverse mode,BCC_CSM 1.1 outperformed the other models in terms of reproducing the spatial pattern and interannual variation,given the model’s strong prediction capability for the Eurasian(EU)teleconnection pattern and western Pacific subtropical high,as well as accurate simulations of the physical processes of El Niño-Southern Oscillation(ENSO)and Indian Ocean dipole(IOD)that impact early winter Tibetan Plateau precipitation.