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Chen Li, Jing-Jia Luo, and Shuanglin Li


The impacts of different types of El Niño–Southern Oscillation (ENSO) on the interannual negative correlation (seesaw) between the Somali cross-equatorial flow (CEF) and the Maritime Continent (MC) CEF during boreal summer (June–August) are investigated using the ECMWF twentieth-century reanalysis (ERA-20C) dataset and numerical experiments with a global atmospheric model [the Met Office Unified Model global atmosphere, version 6 (UM-GA6)]. The results suggest that ENSO plays a prominent role in governing the CEF-seesaw relation. A high positive correlation (0.86) exists between the MC CEF and Niño-3.4 index and also in the case of eastern Pacific (EP) El Niño, central Pacific (CP) El Niño, EP La Niña, and CP La Niña events. In contrast, a negative correlation (−0.35) exists between the Somali CEF and Niño-3.4 index, and this negative relation is significant only in the EP El Niño years. Further, the variation of the MC CEF is highly correlated with the local north–south sea surface temperature (SST) gradient, while the variation of the Somali CEF displays little relation with the local SST gradient. The Somali CEF may be remotely influenced by ENSO. The model results confirm that the EP El Niño plays a major role in causing the weakened Somali CEF via modifying the Walker cell. However, the impact of the EP El Niño on the Somali CEF differs with different seasonal background. It is also found that the interannual CEF seesaw displays a multidecadal change before and after the 1950s, which is linked with the multidecadal strengthening of the intensity of the EP ENSO.

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Chen Li, Jing-Jia Luo, Shuanglin Li, Harry Hendon, Oscar Alves, and Craig MacLachlan


Predictive skills of the Somali cross-equatorial flow (CEF) and the Maritime Continent (MC) CEF during boreal summer are assessed using three ensemble seasonal forecasting systems, including the coarse-resolution Predictive Ocean Atmospheric Model for Australia (POAMA, version 2), the intermediate-resolution Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F), and the high-resolution seasonal prediction version of the Australian Community Climate and Earth System Simulator (ACCESS-S1) model. Retrospective prediction results suggest that prediction of the Somali CEF is more challenging than that of the MC CEF. While both the individual models and the multimodel ensemble (MME) mean show useful skill (with the anomaly correlation coefficient being above 0.5) in predicting the MC CEF up to 5-month lead, only ACCESS-S1 and the MME can skillfully predict the Somali CEF up to 2-month lead. Encouragingly, the CEF seesaw index (defined as the difference of the two CEFs as a measure of the negative phase relation between them) can be skillfully predicted up to 4–5 months ahead by SINTEX-F, ACCESS-S1, and the MME. Among the three models, the high-resolution ACCESS-S1 model generally shows the highest skill in predicting the individual CEFs, the CEF seesaw, as well as the CEF seesaw index–related precipitation anomaly pattern in Asia and northern Australia. Consistent with the strong influence of ENSO on the CEFs, the skill in predicting the CEFs depends on the model’s ability in predicting not only the eastern Pacific SST anomaly but also the anomalous Walker circulation that brings ENSO’s influence to bear on the CEFs.

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