Abstract

The discrepancies among the variations in global ice volume, cave stalagmite δ18O and rainfall reconstructed by cosmogenic 10Be 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 δ18O data from southern China but differs from precipitation reconstructed by 10Be. Both branched tetraether membrane lipids and cave δ18O 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.

In considering Asian monsoon intensity and precipitation during glacial-interglacial transitions in Chinese Loess Plateau, a new study finds that brGDGT-DLNN method can significantly extend the temporal scale record of the EASM and is not restricted by geographic location compared with stalagmite records.

Details

Title
Decoupled Asian monsoon intensity and precipitation during glacial-interglacial transitions on the Chinese Loess Plateau
Author
Zheng, Yukun 1   VIAFID ORCID Logo  ; Liu, Hongyan 1   VIAFID ORCID Logo  ; Yang, Huan 2   VIAFID ORCID Logo  ; Wang, Hongya 1 ; Zhao, Wenjie 1 ; Zhang, Zeyu 1 ; Huang, Miao 3 ; Liu, Weihang 4 

 Peking University, College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface Processes, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 China University of Geosciences, Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, Wuhan, China (GRID:grid.503241.1) (ISNI:0000 0004 1760 9015) 
 China University of Geosciences, State Key Laboratory of Biogeology and Environmental Geology, School of Earth Sciences, Wuhan, China (GRID:grid.503241.1) (ISNI:0000 0004 1760 9015) 
 Beijing Normal University, Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2714219181
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.