摘要:系统评估了美国第二代气候预测系统（CFSv2）对1983～2019年北半球春季逐月南极涛动（AAO）的预测效能及可能成因。结果表明，CFSv2模式对3月、4月和5月AAO空间模态预测效能较好，但是耦合模式仅对3月的AAO年际变化具有较好的预测能力，对4月和5月AAO年际变化的预测能力较差。热带中东太平洋和澳大利亚以东太平洋海温异常有可能是3月AAO年际变化的可预测性来源。一方面，3月厄尔尼诺—南方涛动（ENSO）与AAO之间关系显著，而4、5月两者之间关系减弱。 3月ENSO激发PSA（Pacific–South American）波列传播到南太平洋上，通过影响南太平洋海温异常以及低层气旋性环流异常影响3月AAO的年际变化。另一方面，3月澳大利亚以东太平洋海温异常在副热带急流核心区域激发活跃的Rossby波列，该波列由澳大利亚东部向东南频散到南太平洋中高纬地区，造成该地区位势高度异常，使得副热带地区30°S西风减弱，南半球高纬60°S西风加强，进而影响AAO的变化。CFSv2对3月AAO的预测效能高于4月和5月的主要原因是CFSv2模式能够很好再现3月AAO与ENSO、澳大利亚以东海温之间的关系及其影响机制。
关键词:3月南极涛动/
预测效能/
ENSO/
澳大利亚以东海温/
CFSv2模式
Abstract:The predictive ability of the Climate Forecast System version 2 (CFSv2) for the Antarctic Oscillation (AAO) is evaluated in the three boreal spring months (March, April, and May) of the period 1983–2019. Results show that the CFSv2 model has a good predictive capability for the spatial patterns of the AAO in the three spring months. Specifically, the CFSv2 model can effectively predict the interannual variability of the AAO in March but not in April and May. Results indicate that the tropical central and eastern Pacific sea surface temperature anomalies and the eastern Australia sea surface temperature anomalies are likely to be the predictable sources of the AAO in March. On the one hand, a significant relationship exists between El Ni?o–Southern Oscillation (ENSO) and the AAO in March, and it weakens in April and May. In March, ENSO can excite the Pacific–South American wave train from tropical Pacific to the South Pacific, thereby influencing the interannual variability of the simultaneous AAO by affecting the South Pacific sea surface temperature anomalies and the low-level cyclonic circulation anomalies. On the other hand, the March sea surface temperature anomaly east of Australia triggers an active Rossby wave train in the core area of ??the subtropical jet, which propagates away from eastern Australia toward the southeast and arrives at the mid-high latitudes of the South Pacific. Consequently, the 30°S westerly wind weakens, and the 60°S high latitude in the Southern Hemisphere strengthens and eventually leads to changes in the AAO. CFSv2’s predictive capability for March AAO is higher than that of April and May because this model can reproduce not only the relationship between March AAO and ENSO and the sea surface temperature east of Australia but also the physical processes between them.
Key words:Antarctic Oscillation in March/
Predictive ability/
ENSO/
Sea surface temperature east of Australia/
CFSv2 model
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