Dynamics-Oriented Diagnostics for the Madden–Julian Oscillation

JOURNAL OF CLIMATE(2018)

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摘要
Realistic simulations of the Madden-Julian oscillation (MJO) by global climate models (GCMs) remain a great challenge. To evaluate GCM simulations of the MJO, the U.S. CLIVAR MJO Working Group developed a standardized set of diagnostics, providing a comprehensive assessment of statistical properties of the MJO. Here, a suite of complementary diagnostics has been developed that provides discrimination and assessment of MJO simulations based on the perception that the MJO propagation has characteristic dynamic and thermodynamic structures. The new dynamics-oriented diagnostics help to evaluate whether a model produces eastward-propagating MJOs for the right reasons. The diagnostics include 1) the horizontal structure of boundary layer moisture convergence (BLMC) that moistens the lower troposphere to the east of a convection center, 2) the preluding eastward propagation of BLMC that leads the propagation of MJO precipitation by about 5 days, 3) the horizontal structure of 850-hPa zonal wind and its equatorial asymmetry (Kelvin easterly versus Rossby westerly intensity), 4) the equatorial vertical-longitudinal structure of the equivalent potential temperature and convective instability index that reflects the premoistening and predestabilization processes, 5) the equatorial vertical-longitudinal distribution of diabatic heating that reflects the multicloud structure of the MJO, 6) the upper-level divergence that reflects the influence of stratiform cloud heating, and 7) the MJO available potential energy generation that reflects the amplification and propagation of an MJO. The models that simulate better three-dimensional dynamic and thermodynamic structures of MJOs generally reproduce better eastward propagations. This evaluation identifies a number of shortcomings in representing dynamical and heating processes relevant to the MJO simulation and reveals potential sources of the shortcomings.
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关键词
Dynamics,Madden-Julian oscillation,Diagnostics,Model evaluation,performance,Intraseasonal variability
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