Tuesday, 14 January 2020
Hall B1 (Boston Convention and Exhibition Center)
Predictability of Asian summer monsoon indices characterizing horizontal and vertical zonal wind shear is investigated using 1-month-lead hindcast datasets from seven coupled global circulation models (CGCMs) participating in the operational multimodel ensemble (MME) seasonal prediction system of the Asia–Paciﬁc Economic Cooperation Climate Center (APCC) for the 1983–2010 period. The summer monsoon indices analyzed in this study represent the South Asian summer monsoon (SASM), western North Paciﬁc summer monsoon(WNPSM), and the newly deﬁned northeastern Asian summer monsoon(NEASM). For the WNPSM and NEASM indices, we also analyze the prediction skill of the index components separately. The study demonstrates that the operational APCC MME system reliably predicts most of the summer monsoon indices and their components, with correlation coefﬁcients exceeding the 99% conﬁdence level. Analysis of the ocean sources of the prediction skill of the indices reveals that the strong relationships of most of the monsoon indices and their components with sea surface temperature (SST) are not conﬁned to the equatorial Paciﬁc but rather are dispersed throughout the World Ocean, with the leading role played by the north Indian Ocean SST anomalies. This conclusion is supported by the analysis of correlations between the monsoon indices and the tropical SST indices. The correlations between the SST anomalies and all the summer monsoon indices in the MME predictions are stronger than those in the observations. However, overestimation of the role of the ENSO-related SST anomalies in the seasonal model hindcasts results in some predictability deterioration of the SASM and NEASM indices.
Acknowledgment: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2018-01213.
Reference: Park, H., V.N. Kryjov, and J. Ahn, 2018: One-Month-Lead Predictability of Asian Summer Monsoon Indices Based on the Zonal Winds by the APCC Multimodel Ensemble. J. Climate, 31, 8945–8960, https://doi.org/10.1175/JCLI-D-17-0816.1
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