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. 2016 Sep 26:7:12929.
doi: 10.1038/ncomms12929.

See-saw relationship of the Holocene East Asian-Australian summer monsoon

Deniz Eroglu  1   2 , Fiona H McRobie  3 , Ibrahim Ozken  1   4 , Thomas Stemler  5 , Karl-Heinz Wyrwoll  3 , Sebastian F M Breitenbach  6 , Norbert Marwan  1 , Jürgen Kurths  1   2   7
Affiliations

See-saw relationship of the Holocene East Asian-Australian summer monsoon

Deniz Eroglu et al. Nat Commun. .

Abstract

The East Asian-Indonesian-Australian summer monsoon (EAIASM) links the Earth's hemispheres and provides a heat source that drives global circulation. At seasonal and inter-seasonal timescales, the summer monsoon of one hemisphere is linked via outflows from the winter monsoon of the opposing hemisphere. Long-term phase relationships between the East Asian summer monsoon (EASM) and the Indonesian-Australian summer monsoon (IASM) are poorly understood, raising questions of long-term adjustments to future greenhouse-triggered climate change and whether these changes could 'lock in' possible IASM and EASM phase relationships in a region dependent on monsoonal rainfall. Here we show that a newly developed nonlinear time series analysis technique allows confident identification of strong versus weak monsoon phases at millennial to sub-centennial timescales. We find a see-saw relationship over the last 9,000 years-with strong and weak monsoons opposingly phased and triggered by solar variations. Our results provide insights into centennial- to millennial-scale relationships within the wider EAIASM regime.

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Figures

Figure 1
Figure 1. Top of atmosphere outgoing long wave radiation during the monsoon months delimiting its extent.
(a) East Asian summer monsoon (EASM) during June, July and August (JJA); and (b) Indonesian–Australian summer monsoon (IASM) during December, January and February (DJF); Dongge Cave (dot) and KNI-51 cave (star).
Figure 2
Figure 2. Determinism of the KNI-51 Cave and Dongge Cave records with comparison to previous studies.
(a) (red) KNI-51 cave and (b) (green) Dongge Cave (DA). The determinism is calculated from the corresponding transformation costs time series and statistical significance is indicated by the two horizontal bands (see Methods section for details). High (low) determinism values correspond to wet (dry) monsoon regimes. The coloured bands (blue indicating wet regimes; brown, dry) provide a comparison of our findings with those of previous, qualitative studies. In the text we provide a detailed discussion of previously unidentified or incorrectly identified wet and dry regimes uncovered by our method. (black) Determinism of the solar activity proxy Δ14C time series. Cross-correlation between the determinism of the solar activity proxy Δ14C time series and KNI-51 time series is r=−0.32, and DA time series is r=0.29 (see Methods section for details).
Figure 3
Figure 3. Determinism of KNI-51 and Dongge Cave highlighting the antiphase relationship.
There is a gap in the data of KNI-51 around ∼4,000 yr BP. Contrary to the general antiphase relation of the two determinism time series of KNI-51 and Dongge Cave proxies, the region around ∼7,000 yr BP shows a in—phased relationship, highlighted with yellow.
Figure 4
Figure 4. Illustration of the transformation cost time series method.
The true time series from which the two time series are sampled is indicated by the dashed line. The initial time series segment (top) is transformed into the final time series segment (bottom) in seven steps. Note that after seven steps the segment is identical to the final target time series. The steps 1, 2, 4, 5, 6 are combinations of the elementary operations (i) time shift and (ii) adjusting the amplitude (first two terms of equation (3)), while in step 3 one event is deleted and therefore the (iii) elementary operation was applied (last term of equation (3)).
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