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Seasonal variability of convectively coupled equatorial waves (CCEWs) in recent high-top CMIP5 models

机译:近期高顶CMIP5型号的定性耦合赤道波(CCEWS)的季节变化

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Tropical weather system is controlled by periodic atmospheric disturbances ranging from daily to subseasonal time scales. One of the most prominent atmospheric disturbances in the tropics is convectively coupled equatorial waves (CCEWs). CCEWs are excited by latent heating due to a large-scale convective system and have a significant influence on weather system. They include atmospheric equatorial Kelvin wave, Mixed Rossby Gravity (MRG) wave, Equatorial Rossby (ER) wave and Tropical Depression (TD-type) wave. In this study, we will evaluate the seasonal variability of CCEWs activity in nine high-top CMIP5 models, including their spatial distribution in the troposphere. Our results indicate that seasonal variability of Kelvin waves is well represented in MPI-ESM-LR and MPI-ESM-MR, with maximum activity occurring during boreal spring. The seasonal variability of MRG waves is well represented in CanESM2, HadGEM2-CC, IPSL-CM5A-LR and IPSL-CM5A-MR, with maximum activity observed during boreal summer. On the other hand, ER waves are well captured by IPSL-CM5A-LR and IPSL-CM5A-MR and maximize during boreal fall; while TD-type waves, with maximum activity observed during boreal summer, are well observed in CanESM2, HadGEM2-CC, IPSL-CM5A-LR and IPSL-CM5A-MR. Our results indicate that the skill of CMIP5 models in representing seasonal variability of CCEWs highly depends on the convective parameterization and the spatial or vertical resolution used by each model.
机译:热带天气系统由周期性的大气扰动来控制,从日常到最大的时间尺度。热带地区中最突出的大气紊乱之一是对流的逆波(CCEW)。由于大规模的对流系统,CCEWS潜在潜伏,并对天气系统产生重大影响。它们包括大气赤道开尔文波,混合罗斯比重力(MRG)波,赤道罗斯比(ER)波和热带凹陷(TD型)波。在这项研究中,我们将评估九个高顶CMIP5模型中CCEWS活动的季节变化,包括它们在对流层中的空间分布。我们的研究结果表明,北京 - ESM-LR和MPI-ESM-MR的季节性可变性在MPI-ESM-LR和MPI-ESM-MR中具有很好的代表,在北方春天期间发生了最大活动。 MRG波的季节变异性在CANESM2,HADGEM2-CC,IPSL-CM5A-LR和IPSL-CM5A-MR中表示,在北方夏季期间观察到最大活性。另一方面,ER波通过IPSL-CM5A-LR和IPSL-CM5A-MR良好捕获,并在北部秋季期间最大化;虽然TD型波,在北夏季观察到最大活性,但在CANESM2,HADGEM2-CC,IPSL-CM5A-LR和IPSL-CM5A-MR中观察到良好。我们的结果表明,CMIP5模型的技能在代表CCEWS的季节变异性上高度取决于每种模型使用的对流参数化和空间或垂直分辨率。

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