初边界条件不确定性对AREM模拟一次华南致洪暴雨的影响

利用AREM（advanced regional E-gridη-coordinates model）模式,针对2005年6月21日发生在华南的一次特大致洪暴雨过程,研究了模式初始场和边界场的不确定性对AREM模拟大暴雨过程的影响。研究表明：模式初始场和边界场对模式模拟降水的不同时段影响存在明显差异,初始扰动误差越大模式误差也越大;误差增长先在中小尺度内伴随着湿对流不稳定,且增长极其迅速,接着向大尺度传播,由于对流有效位能的逐渐释放,大气不稳定度降低,误差在大尺度上增长缓慢;在初始场和边界场相同精度的情况下,增加边界场的中尺度信息,尤其是400 km以下尺度的信息,比增加初始场的中尺度信息更能有效抑制误差的增长。

Simulation Sensitivity to Initial and Boundary Condition Uncertainties of a Persistent Heavy Rainfall Event in South China with AREM Model

The advanced regional E-grid η-coordinates model（AREM） is used to simulate the persistent heavy rain in South China during the period of June 20 to 22,2005,which caused a historical flood,and the AREM-simulated precipitation sensitivities to initial and boundary fields are tested.Results show that there are obvious differences between initial and boundary conditions＇ impact on simulated precipitation in the different time periods of simulation.The larger the initial disturbance error is,the larger is the model error.The experiments also reveal that forecast error firstly rapidly grows in the meso-and small scale systems accompanied with unstable moist convection process,then propagates to large scale ones.Because of the gradual release of convective available potential energy,the atmospheric instability reduces,and the error grows slowly in the large scale system.However,in the case that the initial and boundary fields are of the same precision,it is better to add the boundary mesoscale information,especially below 400 km,rather than to add the initial mesoscale information for effectively suppressing the growth of errors.