MJO Propagation Processes and Mean Biases in the SubX and S2S Reforecasts
MJO Propagation Processes and Mean Biases in the SubX and S2S Reforecasts
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DOI：
10.1029/2019jd031139
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发表时间：
2019-08-27
影响因子：
4.4
通讯作者：
Pegion, Kathy
中科院分区：
文献类型：
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作者：
Kim, Hyemi;Janiga, Matthew A.;Pegion, Kathy
马登-朱利安振荡（MJO）是全球亚季节可预测性的主要来源;然而，许多动力预报系统很难预测MJO通过海洋大陆的传播。更好地理解与MJO传播相关的模拟物理过程中的偏差是改善MJO预测的关键。在这项研究中，MJO预测技能，传播过程，和平均状态偏差进行评估，从模型参与的亚季节性实验（SubX）和亚季节性季节性（S2 S）预测项目的再预测。SubX和S2 S重新预测显示，基于与先前研究一致的实时多变量MJO指数，MJO预测技能可达4.5周。然而，仔细检查这些模型的MJO传播通过海洋大陆的代表性表明，他们未能预测的MJO对流，相关的环流，和水分平流过程超过10天，大多数模型低估了MJO振幅。在MJO传播的偏差可以部分地与以下的平均偏差在整个印度太平洋：干燥的低对流层，过量的地面降水，更频繁地发生轻降水率，并过渡到更强的降水率在较低的湿度比在观测。这表明，深对流发生太频繁的模式，并没有得到充分的抑制时，对流层湿度低，这可能是由于代表夹带。
The Madden-Julian oscillation (MJO) is the leading source of global subseasonal predictability; however, many dynamical forecasting systems struggle to predict MJO propagation through the Maritime Continent. Better understanding the biases in simulated physical processes associated with MJO propagation is the key to improve MJO prediction. In this study, MJO prediction skill, propagation processes, and mean state biases are evaluated in reforecasts from models participating in the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) prediction projects. SubX and S2S reforecasts show MJO prediction skill out to 4.5 weeks based on the Real-time Multivariate MJO index consistent with previous studies. However, a closer examination of these models' representation of MJO propagation through the Maritime Continent reveals that they fail to predict the MJO convection, associated circulations, and moisture advection processes beyond 10 days with most of models underestimating MJO amplitude. The biases in the MJO propagation can be partly associated with the following mean biases across the Indo-Pacific: a drier low troposphere, excess surface precipitation, more frequent occurrence of light precipitation rates, and a transition to stronger precipitation rates at lower humidity than in observations. This indicates that deep convection occurs too frequently in models and is not sufficiently inhibited when tropospheric moisture is low, which is likely due to the representation of entrainment.