Decoupled Asian monsoon intensity and precipitation during glacial-interglacial transitions on the Chinese Loess Plateau

The discrepancies among the variations in global ice volume, cave stalagmite delta O-18 and rainfall reconstructed by cosmogenic Be-10 tremendously restrain our understanding of the evolution of the East Asian summer monsoon (EASM). Here, we present a 430-ka EASM mean annual precipitation record on the Chinese Loess Plateau obtained using branched glycerol dialkyl glycerol tetraethers based on a deep learning neural network; this rainfall record corresponds well with cave-derived delta O-18 data from southern China but differs from precipitation reconstructed by Be-10. Both branched tetraether membrane lipids and cave delta O-18 may be affected by soil moisture and atmospheric temperature when glacial and interglacial conditions alternated and were thus decoupled from atmospheric precipitation; instead, they represent variations in the intensity of the EASM. Furthermore, we demonstrate that the brGDGT-DLNN method can significantly extend the temporal scale record of the EASM and is not restricted by geographic location compared with stalagmite records.

Automated summary

Discrepancies among variations in global ice volume, cave stalagmite delta O-18, and rainfall reconstruction using cosmogenic Be-10 pose challenges to understanding the evolution of the East Asian summer monsoon (EASM). In this study, a 430-ka EASM mean annual precipitation record on the Chinese Loess Plateau was obtained using a deep learning neural network, which is in agreement with cave-derived delta O-18 data but differs from Be-10 precipitation reconstruction. This suggests that branched glycerol dialkyl glycerol tetraethers, along with cave delta O-18, represent variations in EASM intensity and can extend the temporal scale of the EASM record.