Abstract
The prediction skill for the East Asian winter monsoon (EAWM) has been analyzed, using the observations and different climate models that participate in the APEC Climate Center (APCC) multi-model ensemble (MME) seasonal forecast. The authors first examined the characteristics of the existing EAWM indices to find a suitable index for the APCC seasonal forecast system. This examination revealed that the selected index shows reasonable prediction skill of EAWM intensity and well-represents the characteristics of wintertime temperature anomalies associated with the EAWM, especially for the extreme cold winters. Although most models capture the main characteristics of the seasonal mean circulation over East Asia reasonably well, they still suffer from difficulty in predicting the interannual variability (IAV) of the EAWM. Fortunately, the POAMA has reasonable skill in capturing the timing and strength of the EAWM IAV and reproduces the EAWM-related circulation anomalies well. The better performance of the POAMA may be attributed to the better skill in simulating the high-latitude forcing including the Siberian High (SH) and Artic Oscillation (AO) and the strong links of the ENSO to the EAWM, compared to other models.
Highlights
The East Asian winter monsoon (EAWM) is one of the most active climate systems in the northern hemisphere during the boreal winter and is driven by the thermal contrast between the coldAsian continent and the neighboring warm oceans [1]
Among the forecast models used in this study, only the POAMA describes the spatial pattern of EAWM-related circulation anomalies considerably well, there are some apparent biases over the Maritime Continents (MC) and the tropical eastern Indian Ocean (IO)
The present study provides a comprehensive assessment of the EAWM interannual variability (IAV) by the seasonal prediction models participating in the APEC Climate Center (APCC) multi-model ensemble (MME) seasonal forecast
Summary
The East Asian winter monsoon (EAWM) is one of the most active climate systems in the northern hemisphere during the boreal winter and is driven by the thermal contrast between the cold. Assessed the climatology and interannual variations of the EAWM in the latest climate system models for Coupled Model Intercomparison Project phase 5 (CMIP5) models They pointed out that models still suffer from biases in surface temperature and northeasterly anomalies over East Asia that are attributed to the ability of models in capturing the EAWM-related tropical-extratropical interactions. With the recent progress in the participation of climate models in the APCC MME seasonal prediction, a comprehensive assessment for the prediction skill of EAWM variability was provided using the hindcast for 1983–2010, with a focus on interannual timescale. We initially examined the characteristics of existing EAWM indices to find a suitable index in APCC seasonal forecast system and explored the prediction skill of EAWM variability.
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