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doi.orgTowards quantitative reconstruction of past monsoon precipitation based on tetraether membrane lipids in Chinese loessAbstract. Variations in the oxygen isotope composition (δ18O) of cave speleothems and numerous proxy records from loess–paleosol sequences have revealed past variations in East Asian monsoon (EAM) intensity. However, challenges persist in reconstructing precipitation changes quantitatively. Here, we use the positive relationship between the degree of cyclization (DC) of branched glycerol dialkyl glycerol tetraethers (brGDGTs) in modern surface soils from the Chinese Loess Plateau (CLP) and mean annual precipitation (MAP) to quantify past monsoon precipitation changes on the CLP. We present a new ∼ 130 000-year-long DC-based MAP record for the Yuanbao section on the western edge of the CLP, which closely tracks the orbital- and millennial-scale variations in available records of both speleothem δ18O and the hydrogen isotope composition of plant waxes (δ2Hwax) from the same section. Combing our new data with existing brGDGT records from other CLP sites reveals a spatial gradient in MAP that is most pronounced during glacials, when the western CLP experiences more arid conditions and receives up to ∼ 250 mm less precipitation than in the southeast, whereas MAP is ∼ 850 mm across the CLP during the Holocene optimum. Furthermore, the DC records show that precipitation amount on the CLP varies at both the precession scale and the obliquity scale, as opposed to the primarily precession-scale variations in speleothem δ18O and δ2Hwax at Yuanbao and the 100 kyr cycle in other loess proxies, such as magnetic susceptibility, which rather indicates the relative intensity of the EAM. At the precession scale, the DC record is in phase with δ2Hwax from the same section and the speleothem δ18O record, which supports the hypothesis that monsoon precipitation is driven by Northern Hemisphere summer insolation.

For the International Day of Women and Girls in Science, I won't be at the AI Summit (where there seems to be quite the gender imbalance, from what I've read) but at the 52nd meetup of Paris Women in Machine Learning and Data Science, listening to Christel Gérardin, Sophie Donnet and Noor Bhatnagar meetup.com/paris-women-in-mach

Oh and also, making STEM more inclusive is something you have to think about more than once a year.

Meetup52. Paris Women in Machine Learning & Data Science @Probabl, Tue, Feb 11, 2025, 7:00 PM | MeetupThe Women in Machine Learning & Data Science (WiMLDS) Meetup aims to inspire, educate, regardless of gender, and support women and gender minorities in the field. **We are