# Proto-monsoon rainfall and greening in Central Asia due to extreme early Eocene warmth

Niels Meijer, Alexis Licht, Amber Woutersen, Carina Hoorn, Faez

Robin-Champigneul, Alexander Rohrmann, Mattia Tagliavento, Julia

Brugger, Fanni Kelemen, Andrew Schauer, et al.

► To cite this version:

Niels Meijer, Alexis Licht, Amber Woutersen, Carina Hoorn, Faez Robin-Champigneul, et al. Proto-monsoon rainfall and greening in Central Asia due to extreme early Eocene warmth. Nature Geoscience, 2024, 17 (2), pp.158-164. 10.1038/s41561-023-01371-4. hal-04426859

HAL Id: hal-04426859

https://hal.science/hal-04426859v1

Submitted on 30 Jan 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
1

Proto-monsoon rainfall and greening in Central Asia due to extreme early

2

Eocene warmth

3

Niels Meijer¹, Alexis Licht², Amber Woutersen³, Carina Hoorn³, Faez Robin-

4

Champigneul⁴, Alexander Rohrmann⁵, Mattia Tagliavento⁶, Julia Brugger¹, Fanni D.

5

Kelemen⁷, Andrew J. Schauer⁸, Micheal T. Hren⁹, Aijun Sun¹⁰⁻¹², Jens Fiebig⁶,

6

Andreas Mulch¹,⁶, Guillaume Dupont-Nivet¹³,¹⁴

7

1) Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am

8

Main, Germany.

9

2) CNRS, IRD, INRAE, CEREGE, Aix Marseille University, Aix-en-Provence, France.

10

3) Department of Ecosystem and Landscape Dynamics (ELD), Institute for Biodiversity

11

and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, the

12

Netherlands.

13

4) Maastricht University, Faculty of Science and Engineering, Maastricht Science

14

Programme, Maastricht, the Netherlands.

15

5) Institute of Geological Sciences, Freie Universität Berlin, Berlin, Germany

16

6) Goethe University Frankfurt, Institute of Geosciences, Frankfurt am Main, Germany.

17

7) Goethe University Frankfurt, Institute for Atmospheric and Environmental Sciences,

18

Frankfurt am Main, Germany.

19

8) Department of Earth and Space Sciences, University of Washington, Seattle, WA,

20

USA.

21

9) Department of Earth Sciences, University of Connecticut, Storrs, CT, USA

22

10) Key Laboratory of Western China's Environmental Systems (Ministry of

23

Education), College of Earth and Environmental Sciences, Lanzhou University,

24

Lanzhou, China.
25 11) Key Laboratory of Desert and Desertification, Northwest Institute of Eco-
26 Environment

27 and Resources, Chinese Academy of Sciences, Lanzhou, China.

28 12) University of Chinese Academy of Sciences, Beijing, China.

29 13) Géosciences Rennes-UMR CNRS 6118, Univ Rennes, CNRS, Rennes, France.

30 14) GFZ German Research Centre for Geosciences, Potsdam, Germany

31

32 The dry continental interior of Asia has remained arid throughout most of its
33 geological history, yet the future of this unique ecosystem remains unclear.

34 Here, we use palynological and isotopic records to track vegetation and
35 moisture throughout the warm early Eocene (57 to 44 million years ago) as an
36 analogue for extreme atmospheric CO2 scenarios. We show that rainfall
37 temporarily doubled and replaced the regional steppe by forested ecosystems.

38 By reconstructing the season of pedogenic carbonate growth we constrain the
39 soil hydrologic regime and show that most of this rainfall occurred during the
40 summer season. This humid event is therefore attributed to an inland expansion
41 of monsoonal moisture following the massive greenhouse gas release of the
42 Paleocene-Eocene Thermal Maximum (PETM) as identified by a negative carbon
43 isotope excursion. The resulting abrupt greening of the Central Asian steppe-
44 desert would have enabled mammal dispersal and could have played a role in
45 carbon cycle feedbacks by enhancing soil organic carbon burial and silicate
46 weathering. These extreme Eocene proto-monsoons, albeit different from the
47 topography-driven Asian monsoon today, highlight the potential for abrupt
48 shifts in Central Asian rainfall and ecosystems under future global warming.

49
The vast Asian continental interior is home to a unique and diverse steppe-desert biome that has existed for millions of years¹, yet its hydroclimatic future and response to extreme atmospheric CO₂ concentrations (pCO₂) remains poorly understood². Sedimentary archives of past warming events together with climate model simulations provide valuable insights³, especially regarding the Eocene period (56-34 Ma) which was characterized by short-lived hyperthermal events of abrupt warming⁴,⁵. The largest and most pronounced of these is the Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) lasting several 10 ka, during which pCO₂ reached more than 6× the pre-industrial atmospheric CO₂ concentration⁶⁻⁸. Records of such hyperthermal events affecting inland Asia are rare and hard to decipher because we commonly lack unambiguous rainfall proxies with respect to the various regional moisture sources, thereby limiting our understanding of the hydroclimatic response to climate forcing, including future projections under higher pCO₂³.

The scarce precipitation reaching inland Asia today mostly originates from monsoons during summer or the mid-latitude westerlies during winter to spring (Fig. 1 A; Extended Data Fig. 1)⁹,¹⁰. Paleoclimate models and geological records indicate that growth of the Tibetan-Himalayan orogen and retreat of the Paratethys Sea modulated monsoons and westerlies since the Eocene (Fig. 1 A)¹¹⁻¹⁴. Proto-monsoons existed already before significant surface uplift of the Tibetan Plateau, but it remains debated whether these were similar to today¹⁵⁻¹⁷, less intense¹⁸ or only restricted to the tropical low latitudes¹³,¹⁴,¹⁹ except during extreme orbital conditions²⁰,²¹. Eocene paleobotanical data show that summer monsoons transported abundant precipitation to the East Asian coast¹⁷,²², while regional soil respiration derived from carbon isotope ratios (δ¹³C) of pedogenic carbonates suggest that monsoons may have reached
further inland¹⁰. Oxygen isotope ratios (δ¹⁸O) on the other hand, suggest that the mid-latitude westerlies provided winter to springtime precipitation to Central Asia, especially before the Neogene surface uplift of the Tien Shan and Pamir mountains, which block most of this moisture today⁹,¹⁰,²³. However, the isotopic composition of this westerly precipitation is difficult to distinguish from summer monsoonal moisture reaching the continental interior¹⁰.

Key in distinguishing between these different Asian moisture regimes is therefore to identify not only the isotopic composition and amount of precipitation, but also the seasonal timing, which remains difficult to assess from geological records. Here, we address this issue using a novel approach of combining fossil sporomorphs (pollen and spores) and soil organic matter as proxy for precipitation²⁴ together with clumped isotope (Δ₄₇) temperatures of co-occurring pedogenic carbonates which mostly form during the dry season²⁵,²⁶. By comparing these Δ₄₇-derived soil temperatures with seasonal climate model estimates we distinguish whether soil dewatering occurred predominantly during a winter-time dry season after a wet summer monsoon, or during summer drying of westerly-derived soil moisture²⁷,²⁸. Today, the monsoons and westerlies meet along the northeastern margin of the Tibetan Plateau, which includes the continental Xining Basin (China) and is ideally located to track the evolution of these moisture sources (Fig. 1). Previous soil temperature reconstructions throughout the middle Eocene and Oligocene show that the Xining Basin was at low elevation²⁷, while steppe-desert pollen, presence of evaporites and reduced soil respiration indicate aridity¹,²³,²⁹. Dating of this sedimentary record has now been extended to the early Eocene based on magnetostratigraphy and radiometric ages²³,³⁰ allowing us to investigate the Central Asian steppe response to hyperthermal conditions.
100

101

Increased rainfall during a carbon isotope excursion

102

103

Early Eocene hyperthermals were driven by the periodic injection of greenhouse gases into the atmosphere from low-δ¹³C reservoirs. This resulted in negative carbon isotope excursions (CIE) across the globe that have been detected in various terrestrial proxies such as plant waxes (δ¹³Cwax of C29 to C31 *n*-alkanes) or bulk soil organic matter (δ¹³CSOM)⁶. In the Xining Basin, δ¹³C values are relatively high throughout most of the Eocene, but we identify an abrupt and large CIE of -6‰ in δ¹³CSOM and -8‰ in compound specific δ¹³Cwax (Fig. 2). This is significantly larger than the CIEs related to early Eocene hyperthermals which typically attain magnitudes of up to -4‰⁴,⁵, but very similar in both shape and magnitude to continental records of the PETM⁶,³²,³³.

104

105

106

107

108

109

110

111

112

113

The Xining CIE is preceded by alluvial mudflat deposits at the basin margin (Ledu section) and organic-rich gypsum in the basin center (Bingling Shan and Caijia sections) indicating dry conditions. This is corroborated by the predominance of steppe-desert shrubs in the palynological record and high δ¹³C values which today are only found in extremely dry ecosystems²⁴,³⁴ (Fig. 2). The negative CIE starts abruptly in the uppermost gypsum bed and spans ~30 meters into the overlying organic-rich alluvial mudflat deposits³⁰. Steppe-desert pollen decrease during this interval and the vegetation becomes dominated by temperate forests and ferns indicating a shift to wetter conditions. Less water stress experienced by C3 vegetation and the corresponding shift in biome typically results in lower δ¹³C values³⁴,³⁵. If combined with a dramatic drop of atmospheric carbon isotopic composition (δ¹³Catm), such as seen

114

115

116

117

118

119

120

121

122

123
124

during hyperthermals<sup>6,35,36</sup>, these ecological changes could produce the large size of
the CIE observed in the Xining Basin.

126

127

Organic matter recorded in soils provides a natural average of the aboveground
biomass and can be used to reconstruct the amount of rainfall when corrected for
changes in δ¹³C_atm (Fig. 2 and Extended Data Fig. 2)²⁴. Even when assuming an
extreme change of δ¹³C_atm such as observed during the PETM⁶,³⁵, reconstructed mean
annual precipitation (MAP) values suggest at least a doubling of MAP in the Xining
Basin during the CIE (~574 mm/year) compared to the evaporites below (~177
mm/year). Using the δ¹³C_atm value of lower magnitude Eocene hyperthermals would
result in an even larger increase in MAP (~984 mm/year) and using the early Eocene
baseline value would imply an unrealistic MAP of >4000 mm/year (Supplementary
Data 4). Throughout the remainder of the Eocene Xining record, δ¹³C_SOM values
remain relatively high²⁹ indicating aridity which fits the predominant redbeds,
evaporites and steppe-desert shrubs observed in the record¹,²³. The CIE in the Xining
Basin is thus a unique window where both palynological assemblages and δ¹³C values
show a significant greening of the otherwise arid Asian interior. In the following, we will
use soil carbonates to test whether this greening was driven by increased westerly
moisture or monsoons (Fig. 1).

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

## Clumped isotope evidence for summer rainfall

145

146

147

Well-developed pedogenic carbonate nodules are rare in the Xining Basin record but
were identified in three horizons of the Ledu section. In consequence, the carbonate
component of the alluvial mudrocks was assessed as well using Scanning Electron
148 Microscopy (SEM), X-Ray Diffraction (XRD; Fig. 2; Extended Data Fig. 3) and both
149 optical and cathodoluminescence (CL) microscopy (Extended Data Fig. 4). The strata
150 between 50 Ma and 45 Ma contain mostly calcian dolomite (6-20%), while the intervals
151 above and below are dominated by calcite (1-14%). This calcite is mostly dull
152 luminescent micrite and is interpreted as vadose-grown cement with no evidence of
153 phreatic overprinting (Extended Data Fig. 4 A and B). These cements precipitate either
154 from rising shallow groundwater or percolating soil water and are similar to pedogenic
155 carbonates³⁷. In contrast, the calcian dolomite may have formed either by syn-
156 sedimentary precipitation from saline brines or late diagenetic replacement of calcite
157 cements³⁸. Hence, we focus our isotope investigations solely on the vadose-grown
158 calcite and micritic pedogenic nodules (Extended Data Fig. 4 C) to avoid diagenetic
159 overprinting.

160 Clumped isotope thermometry measures the relative abundance of calcite-derived
161 CO2 isotopologues of mass 47 compared to the predicted stochastic distribution (Δ47).
162 Since the bonding between the heavy isotopes (¹³C-¹⁸O) is temperature-dependent,
163 this measurement allows reconstructing soil temperatures at the time of carbonate
164 growth without prior knowledge of the isotopic composition of the soil water³⁹. Most
165 Holocene pedogenic carbonates provide Δ47 temperatures that are warmer than mean
166 annual temperatures (MAT) because intense soil dewatering and carbonate formation
167 is typically biased towards the summer season²⁵,²⁶. So far, the only location where soil
168 Δ47 temperatures have systematically yielded winter temperatures is the monsoonal
169 tropical domain, where winters are dry and warm enough for the accumulation of
170 pedogenic carbonates while summers are typically too wet²⁸. Colder-than-MAT Δ47
171 temperatures can thus be interpreted as a signature for a summer rainy season,
172

especially during Eocene times when winter temperatures were overall warmer,
facilitating carbonate growth in the winter²⁸.

174

175

Overall, the pedogenic and vadose-grown carbonates in the Xining strata show a wide
spread of Δ47 temperatures ranging from 9 ±3 °C to 38 ±4°C (Fig. 2). This range could
be due to high evaporative demand throughout the year, resulting in soil drying shortly
after erratic rainfall events under variable temperature conditions²⁶. In contrast, the Δ47
temperatures during the wetter CIE interval (Fig. 2) are remarkably stable at 20±3°C
and surprisingly low, especially given the hyperthermal conditions. When compared
with simulated temperatures in the Xining Basin from the various climate models of
the Deep-Time Model Intercomparison Project (DeepMIP)⁴⁰ these simulated
temperatures indicate that carbonate growth during the CIE was biased towards the
colder winter months (Fig. 3 A). Especially when considering that the soil temperature
might have been 1-4°C warmer than the simulated surface air because of ground
heating effects⁴¹.

176

177

178

179

180

181

182

183

184

185

186

187

188

The Δ47 temperatures during the CIE therefore suggest that soil drying in the Xining
Basin occurred during the winter season, while the increased rainfall recorded in the
palynological assemblage and δ13C values must have occurred mostly during the
summer. This is similar to the modern monsoonal setting in which pedogenic
carbonates near Xining are formed during the fall and after the wet season⁴².

189

190

191

192

193

Reconstructed soil water δ¹⁸O (-6 ± 1.5‰; Extended Data Fig. 5 and 6) is similar to
coeval records of both summer monsoonal and westerly moisture in the region¹⁰, but
the cold Δ₄₇ temperatures in combination with increased MAP indicate an
intensification of summer monsoons deep within the Asian continent shifting the timing

194

195

196
of carbonate formation to the winter season. Cold $\Delta_{47}$ temperatures are not unique to the CIE and reappear episodically in the Xining Basin ~10 million years later and persist into the Oligocene (Fig. 3 A), possibly due to the combined effects of global cooling and an increased role for summer monsoonal moisture$^{27}$. However, the palynological records show that the region remained extremely dry throughout the late Eocene to Oligocene$^{1}$ and unlike the intensified monsoon seen during the CIE (Fig. 2).

204

## Proto-monsoon intensification in hyperthermal conditions

206

The simulated temperatures fit well with global proxy compilations$^{43}$ and the climate models show mutual agreement$^{40}$ (Fig 3 A), however, differences between models are large for simulated precipitation$^{3}$ (Fig. 3 B). The ‘drier’ models show aridity in the Xining Basin throughout the year (e.g. COSMOS and IPSL), while the ‘wetter’ models reveal a summer rainy season (e.g. CESM and HadCM3) not unlike pre-industrial conditions (Extended Data Fig. 1). Simulated MAP is relatively low and ranges from 25 to 469 mm/year (Fig. 3 B), which fits with the inland evaporative basins in the region$^{44}$ and our proxy estimates for the Paleocene and Eocene background conditions in the Xining Basin. However, even the ‘wetter’ simulations are lower than our reconstructed MAP of 574 mm/year for the intensified monsoon during the CIE.

217

The distribution of monsoonal domains$^{45}$ in the simulations shows that the East Asian monsoon was less prevalent in the Eocene compared to today (Fig. 4; Extended Data Fig. 7) and that southern Asia was influenced by the Intertropical Convergence Zone (ITCZ) as suggested by paleobotanical data$^{19}$. Intriguingly, some of the Eocene
simulations also show a monsoonal domain along the East Asian coast (CESM, COSMOS and GFDL), in particular in the 6x and 9x pCO₂ simulations, which would have resembled the early Eocene atmosphere⁸ (Fig. 4; Extended Data Fig. 7). This East Asian proto-monsoon agrees well with paleobotanical compilations showing a humid coast line¹⁷,²², but none of the DeepMIP models reproduce monsoons extending far into the continental interior to reach the Xining Basin.

Other modeling studies have shown that Eocene monsoons can be triggered in extreme orbital settings with amplified northern hemisphere heating²⁰,²¹. The PETM and other hyperthermal events correspond to high eccentricity⁷ and these unique conditions combined with extreme greenhouse warming likely conspired to intensify the proto-monsoons to reach the continental interior of Asia. The shape, large magnitude and thickness of the Xining CIE, and its occurrence within a long reversed polarity zone correlated with chron C24r (57.1 Ma to 53.9 Ma) allow us to attribute the CIE to the PETM (56 Ma), which also fits within the radiometric age constraints (Fig. 2; Extended Data Fig. 8). Alternatively, it could be ETM2 (54 Ma) but this hyperthermal is considerably smaller in size, shorter and consists of two excursions (H1 and H2) that have been observed in both marine and terrestrial records⁴,⁵,³² but are absent in the Xining Basin. Furthermore, negative CIEs with a shape and size similar to the Xining CIE have been observed in the continental Nanyang and Fushun Basins in eastern China and are also linked to reduced water stress during the PETM³⁶. As the largest hyperthermal, the PETM is therefore the most likely driver for this unique event of monsoon intensification and greening in Central Asia.
Finally, we note that the Eocene proto-monsoons were significantly different from the modern-day East Asian monsoon, which is mostly driven by interaction between the subtropical jet stream and the high topography of the Tibetan Plateau¹². Eocene proto-monsoons occur even in the DeepMIP simulations with no Tibetan Plateau at all (Fig. 4) and are driven by a distinct low atmospheric pressure anomaly developing during summer over the vast and flat Asian continent (Extended Data Fig. 9). This suggests that the proto-monsoons were similar to a large sea breeze driven by land-sea thermal contrasts¹⁸ and explains their sensitivity to hyperthermal conditions. Global cooling after the early Eocene reduced regional thermal contrasts, dampening the ability of proto-monsoons to episodically expand inland and could explain the overall aridification trend of Central Asia throughout the Eocene and culminating at the Eocene-Oligocene Transition (EOT; 33.9 Ma)²⁷,²⁹,⁴⁶. Only until the subsequent surface uplift and northward expansion of the Tibetan Plateau during the Neogene would the modern-day East Asian monsoon have returned to the Xining Basin and the Asian interior¹¹⁻¹⁴.

Our study thus reveals a prominent role for Eocene proto-monsoons in occasionally greening the otherwise dry Asian interior under hyperthermal conditions. The PETM, but also other hyperthermals such as the Middle Eocene Climatic Optimum (MECO) are associated with major mammal dispersals in and out of Asia⁴⁷,⁴⁸ and future work should consider the role of proto-monsoons in shifting biomes⁴⁹ and opening dispersal corridors within continental Asia. Replacing the steppe-desert by forested ecosystems could have also played a major role in buffering the massive carbon release during hyperthermals by enhancing soil organic carbon burial and silicate weathering⁵⁰. Finally, our work provides paleoclimate evidence highlighting the abrupt and non-linear
response of Asian monsoons to extreme greenhouse warmth. Although the Eocene
Asian paleogeography and hydroclimate were markedly different from today, the
mechanisms leading to abrupt greening of the Asian interior should be further tested
and simulated because of their significance for predicting future rainfall patterns.

275

276 Acknowledgments

This study was funded by an ERC consolidator grant (MAGIC 649081 to GDN) and
through the VeWA consortium by the LOEWE programme of the Hessen Ministry of
Higher Education, Research and the Arts, Germany. We thank Rainer Petschick for
help with the XRD analyses as well as Jeremy McCormack and Amelia Davies for
suggestions on the formation of dolomite. We acknowledge Roy Erkens and the
following students from Maastricht University for their help in exploring the
palynological samples: Henry del Marmol, Lucas Sauerschnig, Kaatje de Jong, Amaia
Villagrasa, Lael Licht, Henry de Schrevel, and Benedetto Diana. We also acknowledge
Hanna van den Hill (University of Amsterdam) and Julia Gravendeyk (University of
Bonn) for extensive sporomorph documentation. We thank Hanno Meyer for kindly
providing organic stable isotope analyses and Armelle Ballian, Sven Hofmann and
Simon Anderson for assistance with stable and clumped isotope analyses. We also
thank Christina Günter and Uwe Altenberger for their help with the SEM and CL. We
are grateful to Natasha Barbolini, Xiang-Jun Liu, Xiaohui Wu, Zhipeng Wu, Meimei
Xiao and Yang Zhang for their support with collecting the samples. We also
acknowledge the efforts of the DeepMIP community and are thankful for the available
climate model simulation data.

294
295 **Author contributions**

296 N.M., A.L. and G.D.-N. designed the study. N.M., A.L., A.W., A.R., A.S. and G.D.-N.

297 conducted the field work and collected the samples. N.M. performed the XRD and

298 petrographic analyses. A.W., F.R.-C. and C.H. prepared and analysed the

299 palynological samples. A.R. and M.T.H. performed the *n*-alkane analyses. N.M., A.L.,

300 A.J.S. and A.M. conducted the stable isotope analyses. N.M., M.T. and J.F. performed

301 the clumped isotope analyses. J.B. and F.D.K. analysed and plotted the climate model

302 simulation data. N.M. wrote the manuscript with major input from A.L., G.D.-N. and

303 A.M. All co-authors contributed to interpreting the data and writing the manuscript.

304

305 **Competing Interests Statement**

306 The authors declare no competing interests.

307

308 **Figures**
<figure><img src="image_2.png" /><figcaption>Fig. 1. Geological setting showing hypothesized Eocene hydroclimates in Asia including a subtropical arid belt, westerly or monsoonal domain. A) Paleogeographic map of Asia at 50 Ma (million years ago)³¹ showing the location of the Xining Basin. Blue arrows show potential moisture sources. Histograms reflect the seasonal distribution of this rainfall based on modern-day observations in monsoonal Xining and westerly-dominated Tashkent (https://www.ncei.noaa.gov/products/wmo-climate-normals). Climate model simulations indicate a similar seasonal distribution of rainfall in these domains during the Eocene⁹,²⁰. Inset shows present-day geographical location. B) Geological map of the Xining Basin (modified from ref³⁰) showing the</figcaption></figure>

309

310

311

312

313

314

315

316

317

318
319 locations of the studied sections and palynological sampling. C) Lithostratigraphy of the Caijia, Bingling Shan and Ledu key sections²³,³⁰.

<figure><img src="image_3.png" /></figure>
Fig. 2. Paleo-environmental reconstruction showing temperate forests replacing steppe shrubs during a negative carbon isotope excursion (CIE). The CIE is indicated by the brown shaded vertical bar. Data include: A) palynological data classified in Plant Functional Types, B) reconstructed Mean Annual Precipitation (MAP) using late Paleocene, PETM and early Eocene δ¹³C_atm and δ¹³C_SOM values (root mean square error of ±422 mm/year of the MAP proxy is shown)²⁴, C) δ¹³C values of both soil organic matter and n-alkanes, D) Δ₄₇ temperatures of vadose-grown carbonates (with solid and dashed lines indicating 68% and 95% confidence intervals respectively based on at least 13 replicates), one sample produced an unrealistically low temperature of -1.3°C and is considered an outlier, E) X-Ray Diffraction (XRD) derived mineral content, F) age constraints²³,³⁰ based on radiometric ages (stars) and magnetic polarities (black ticks), lithostratigraphy showing stratigraphic positions of palynological samples with red marks.
<figure><img src="image_4.png" /><figcaption>Fig. 3. Proxy comparison with simulated surface air temperature (A) and precipitation (B) in the Eocene Xining Basin. Averaged values were derived from a box of 1.875° latitude by 2.5° longitude centred at the paleolocation of the Xining Basin (102.5°N, 39.5°E). Simulations are derived from the DeepMIP climate model ensemble (colors indicate each model) under an early Eocene paleogeography with no Tibetan Plateau and a Paratethys Sea lowstand, preindustrial orbital configuration and 3x, 6x or 9x preindustrial pCO₂ when available (solid, dashed and dotted lines respectively)⁴⁰. The histogram in A) shows the number of measured Δ₄₇ temperatures in 5°C bins. CIE temperatures of ~20°C are best explained by soil dewatering and carbonate formation</figcaption></figure>
345

during the colder winter months. Simulated precipitation in B) varies from dry
throughout the year to summer wet similar to the present-day monsoons.

346

<figure><img src="image_5.png" /></figure>

347

348

349

350

351

352

353

354

355

356

357

358

Fig. 4. Distribution of monsoonal domains in climate model simulations. Upper panel shows a pre-industrial control simulation (CESM) and two early Eocene simulations with 6x pCO₂ (GFDL and INM). Lower panel shows different pCO₂ scenarios (3x, 6x and 9x) of the CESM model. Additional simulations are shown in Extended Data Fig. 7. Summer (MJJAS) minus winter precipitation (NDJFM) is used as a metric and regions where this difference is >2.5 mm/day are considered monsoonal⁴⁵. Red dot indicates the location of the Xining Basin. All Eocene simulations show an ITCZ (Intertropical Convergence Zone) monsoon near the equator. CESM and GFDL show a proto-monsoonal domain along the East Asian coast, but none of the models simulate monsoons extending far into the Asian interior.
359 References

360 1. Barbolini, N., Woutersen, A., Dupont-Nivet, G., Silvestro, D., Tardif, D., Meijer, N., Chang, C., H.-X. Zhang, A. Licht, Rydin, C., Koutsondendris, A., Han, F., Rohrmann, A., Liu, X.-J., Zhang, Y., Donnadieu, Y., Fluteau, F., Ladant, J.-B., Le Hir, G., Hoorn, C. (2020). Cenozoic evolution of the steppe-desert biome in Central Asia. Science Advances, 6(41), eabb8227. https://doi.org/10.1126/sciadv.abb8227

366 2. Li, C., Fu, B., Wang, S., Stringer, L. C., Wang, Y., Li, Z., Liu, Y. & Zhou, W. (2021). Drivers and impacts of changes in China's drylands. Nature Reviews Earth & Environment, 2(12), 858-873. https://doi.org/10.1038/s43017-021-00226-z

370 3. Cramwinckel, M. J., Burls, N. J., Fahad, A. A., Knapp, S., West, C. K., Reichgelt, T., Greenwood, D. R., Chan, W.-L., Donnadieu, Y., Hutchinson, D. K., de Boer, A. M., Ladant, J.-B., Morozova, P. A., Niezgodzki, I., Knorr, G., Steinig, S., Zhang, Z., Zhu, J., Feng, R., Lunt, D. J., Abe-Ouchi, A. & Inglis, G. N. (2023). Global and zonal-mean hydrological response to early Eocene warmth. Paleoceanography and Paleoclimatology, e2022PA004542. https://doi.org/10.1029/2022PA004542

376 4. Westerhold, T., Marwan, N., Drury, A. J., Liebrand, D., Agnini, C., Anagnostou, E., Barnet, J. S. K., Bohaty, S. M., De Vleeschouwer, D., Florindo, F., Frederichs, T., Hodell, D. A., Holbourn, A. E., Kroon, D., Lauretano, V., Littler, K., Lourens, L. J., Lyle, M., Pälike, H., Röhl, U., Tian, J., Wilkens, R. H., Wilson, P. A., Zachos, J. C. (2020). An astronomically dated record of Earth's climate and its predictability over the last 66 million years. Science, 369(6509), 1383-1387. https://doi.org/10.1126/science.aba6853
384

5. Abels, H. A., Lauretano, V., Van Yperen, A. E., Hopman, T., Zachos, J. C., Lourens, L. J., Gingerich, P. D. & Bowen, G. J. (2016). Environmental impact and magnitude of paleosol carbonate carbon isotope excursions marking five early Eocene hyperthermals in the Bighorn Basin, Wyoming. Climate of the Past, 12(5), 1151-1163. https://doi.org/10.5194/cp-12-1151-2016, 2016

385

386

387

388

389

6. McInerney, F. A., & Wing, S. L. (2011). The Paleocene-Eocene Thermal Maximum: A perturbation of carbon cycle, climate, and biosphere with implications for the future. Annual Review of Earth and Planetary Sciences, 39, 489-516. https://doi.org/10.1146/annurev-earth-040610-133431

390

391

392

393

7. Zeebe, R. E., & Lourens, L. J. (2019). Solar System chaos and the Paleocene-Eocene boundary age constrained by geology and astronomy. Science, 365(6456), 926-929. https://doi.org/10.1126/science.aax0612

394

395

396

8. Rae, J. W., Zhang, Y. G., Liu, X., Foster, G. L., Stoll, H. M., & Whiteford, R. D. (2021). Atmospheric CO2 over the past 66 million years from marine archives. Annual Review of Earth and Planetary Sciences, 49, 609-641. https://doi.org/10.1146/annurev-earth-082420-063026

397

398

399

400

9. Bougeois, L., Dupont-Nivet, G., de Rafélis, M., Tindall, J. C., Proust, J. N., Reichart, G. J., de Nooijer, L. J., Guo, Z. & Ormukov, C. (2018). Asian monsoons and aridification response to Paleogene sea retreat and Neogene westerly shielding indicated by seasonality in Paratethys oysters. Earth and Planetary Science Letters, 485, 99-110. https://doi.org/10.1016/j.epsl.2017.12.036

401

402

403

404

405

406

10. Caves Rugenstein, J. K., & Chamberlain, C. P. (2018). The evolution of hydroclimate in Asia over the Cenozoic: A stable-isotope perspective. Earth-

407
408

Science

Reviews,

185,

1129-1156.

409

https://doi.org/10.1016/j.earscirev.2018.09.003

410

11. An, Z., Kutzbach, J. E., Prell, W. L., & Porter, S. C. (2001). Evolution of Asian monsoons and phased uplift of the Himalaya–Tibetan plateau since Late Miocene times. Nature, 411(6833), 62. https://doi.org/10.1038/35075035

411

412

413

12. Molnar, P., Boos, W.R., Battisti, D.S. (2010). Orographic controls on climate and paleoclimate of Asia: thermal and mechanical roles for the Tibetan Plateau. Annu. Rev. Earth Planet. Sci.38. https://doi.org/10.1146/annurev-earth-040809-152456.

414

415

416

417

13. Sun, X., & Wang, P. (2005). How old is the Asian monsoon system?— Palaeobotanical records from China. Palaeogeography, Palaeoclimatology, Palaeoecology, 222(3-4), 181-222. https://doi.org/10.1016/j.palaeo.2005.03.005

418

419

420

421

14. Wu, F., Fang, X., Yang, Y., Dupont-Nivet, G., Nie, J., Fluteau, F., Zhang, T. & Han, W. (2022). Reorganization of Asian climate in relation to Tibetan Plateau uplift. Nature Reviews Earth & Environment, 3(10), 684-700. https://doi.org/10.1038/s43017-022-00331-7(Wu et al. 2022)

422

423

424

425

15. Huber, M., & Goldner, A. (2012). Eocene monsoons. Journal of Asian Earth Sciences, 44, 3-23. https://doi.org/10.1016/j.jseaes.2011.09.014

426

427

16. Licht, A., Van Cappelle, M., Abels, H.A., Ladant, J.B., Trabucho-Alexandre, J., France-Lanord, C., Donnadieu, Y., Vandenberghe, J., Rigaudier, T., Lécuyer, C., Terry Jr., D., Adriaens, R., Boura, A., Guo, Z., Aung Naing, Soe, Quade, J., Dupont-Nivet, G., Jaeger, J.-J., (2014). Asian monsoons in a late Eocene greenhouse world. Nature 513 (7519), 501–506. https://doi.org/10.1038/nature13704

428

429

430

431

432
433

17. Quan, C., Liu, Z., Utescher, T., Jin, J., Shu, J., Li, Y., Liu, Y.S.C. (2014).

434

Revisiting the Paleogene climate pattern of East Asia: a synthetic review. Earth-

435

Sci. Rev.139, 213-230. https://doi.org/10.1016/j.earscirev.2014.09.005.

436

18. Farnsworth, A., Lunt, D. J., Robinson, S. A., Valdes, P. J., Roberts, W. H., Clift,

437

P. D., et al. (2019). Past East Asian monsoon evolution controlled by

438

paleogeography, not CO2. Science Advances, 5(10), eaax1697.

439

https://doi.org/10.1126/sciadv.aax1697

440

19. Spicer, R. A., Yang, J., Herman, A. B., Kodrul, T., Maslova, N., Spicer, T. E.,

441

Aleksandrova, G. & Jin, J. (2016). Asian Eocene monsoons as revealed by leaf

442

architectural signatures. Earth and Planetary Science Letters, 449, 61-68.

443

https://doi.org/10.1016/j.epsl.2016.05.036

444

20. Zhang, Z., Flatøy, F., Wang, H., Bethke, I., Bentsen, M., & Guo, Z. (2012). Early

445

Eocene Asian climate dominated by desert and steppe with limited monsoons.

446

Journal of Asian Earth Sciences, 44, 24-35.

447

https://doi.org/10.1016/j.jseaes.2011.05.013

448

21. Tardif, D., Toumoulin, A., Fluteau, F., Donnadieu, Y., Le Hir, G., Barbolini, N.,

449

Licht, A., Ladant, J.-B., Sepulchre, P., Viovy, N., Hoorn, C. & Dupont-Nivet, G.

450

(2021). Orbital variations as a major driver of climate and biome distribution

451

during the greenhouse to icehouse transition. Science Advances, 7(43),

452

eabh2819. https://doi.org/10.1126/sciadv.abh2819

453

22. Li, Q., Utescher, T., Liu, Y. C., Ferguson, D., Jia, H., & Quan, C. (2022).

454

Monsoonal climate of East Asia in Eocene times inferred from an analysis of

455

plant functional types. Palaeogeography, Palaeoclimatology, Palaeoecology,

456

601, 111138. https://doi.org/10.1016/j.palaeo.2022.111138.
457

23. Meijer, N., Dupont-Nivet, G., Abels, H. A., Kaya, M. Y., Licht, A., Xiao, M., Zhang, Y., Roperch, P., Poujol, M., Lai, Z., & Guo, Z. (2019). Central Asian moisture modulated by proto-Paratethys Sea incursions since the early Eocene. *Earth and Planetary Science Letters*, 510, 73–84.
https://doi.org/10.1016/j.epsl.2018.12.031

458

459

460

461

462

24. Stein, R. A., Sheldon, N. D., & Smith, S. Y. (2021). Soil carbon isotope values and paleoprecipitation reconstruction. *Paleoceanography* and *Paleoclimatology*, 36(4), e2020PA004158.
https://doi.org/10.1029/2020PA004158

463

464

465

466

25. Breecker, D. O., Sharp, Z. D., & McFadden, L. D. (2009). Seasonal bias in the formation and stable isotopic composition of pedogenic carbonate in modern soils from central New Mexico, USA. The Geological Society of America Bulletin, 121(3–4), 630–640. https://doi.org/10.1130/b26413.1

467

468

469

470

26. Kelson, J. R., Huntington, K. W., Breecker, D. O., Burgener, L. K., Gallagher, T. M., Hoke, G. D., & Petersen, S. V. (2020). A proxy for all seasons? A synthesis of clumped isotope data from Holocene soil carbonates. *Quaternary Science Reviews*, 234, 106259.
https://doi.org/10.1016/j.quascirev.2020.106259

471

472

473

474

475

27. Page, M., Licht, A., Dupont-Nivet, G., Meijer, N., Barbolini, N., Hoorn, C., et al. (2019). Synchronous cooling and decline in monsoonal rainfall in northeastern Tibet during the fall into the Oligocene icehouse. *Geology*, 47(3), 203–206.
https://doi.org/10.1130/g45480.1

476

477

478

479

28. Licht, A., Kelson, J., Bergel, S., Schauer, A., Petersen, S. V., Capirala, A., Huntington, K. W., Dupont-Nivet, G., Win, Z. & Aung, D. W. (2022). Dynamics of pedogenic carbonate growth in the tropical domain of Myanmar.

480

481
482

Geochemistry, Geophysics, Geosystems, 23(7), e2021GC009929.

483

https://doi.org/10.1029/2021GC009929

484

29. Licht, A., Dupont-Nivet, G., Meijer, N., Rugenstein, J. C., Schauer, A., Fiebig, J., et al. (2020). Decline of soil respiration in northeastern Tibet through the transition into the Oligocene icehouse. Palaeogeography, Palaeoclimatology, Palaeoecology, 560, 110016. https://doi.org/10.1016/j.palaeo.2020.110016

485

486

487

488

30. Meijer, N., Dupont-Nivet, G., Licht, A., Roperch, P., Rohrmann, A., Sun, A., Lu, S., Woutersen, A., & Nowaczyk, N. (2023). Early Eocene magnetostratigraphy and tectonic evolution of the Xining Basin, NE Tibet. Basin Research. https://doi.org/10.1111/bre.12720

489

490

491

492

31. Aminov, J., Dupont-Nivet, G., Ruiz, D., & Gailleton, B. (2023). Paleogeographic reconstructions using QGIS: Introducing Terra Antiqua plugin and its application to 30 and 50 Ma maps. Earth-Science Reviews, 104401. https://doi.org/10.1016/j.earscirev.2023.104401

493

494

495

496

32. Chen, Z., Ding, Z., Tang, Z., Wang, X., & Yang, S. (2014). Early Eocene carbon isotope excursions: Evidence from the terrestrial coal seam in the Fushun Basin, Northeast China. Geophysical Research Letters, 41(10), 3559-3564. https://doi.org/10.1002/2014GL059808

497

498

499

500

33. Chen, Z., Wang, X., Hu, J., Yang, S., Zhu, M., Dong, X., Tang, Z., Peng, P. & Ding, Z. (2014). Structure of the carbon isotope excursion in a high-resolution lacustrine Paleocene–Eocene Thermal Maximum record from central China. Earth and Planetary Science Letters, 408, 331-340. https://doi.org/10.1016/j.epsl.2014.10.027

501

502

503

504

505

34. Kohn, M. J. (2010). Carbon isotope compositions of terrestrial C3 plants as indicators of (paleo) ecology and (paleo) climate. Proceedings of the National

506
507

Academy of Sciences, 107(46), 19691-19695.

508

https://doi.org/10.1073/pnas.100493310

509

35. Diefendorf, A. F., Mueller, K. E., Wing, S. L., Koch, P. L., & Freeman, K. H.

510

(2010). Global patterns in leaf 13C discrimination and implications for studies of past and future climate. Proceedings of the National Academy of Sciences, 107(13), 5738-5743. https://doi.org/10.1073/pnas.0910513107

511

512

513

36. Chen, Z., Dong, X., Wang, X., Tang, Z., Yang, S., Zhu, M., & Ding, Z. (2020).

514

Spatial change of precipitation in response to the Paleocene-Eocene thermal Maximum warming in China. Global and Planetary Change, 194, 103313.
https://doi.org/10.1016/j.gloplacha.2020.103313

515

516

517

37. Beckner, J. R., & Mozley, P. S. (1998). Origin and spatial distribution of early

518

vadose and phreatic calcite cements in the Zia Formation, Albuquerque Basin, New Mexico, USA. Carbonate Cementation in Sandstones: Distribution Patterns and Geochemical Evolution, 27-51.
https://doi.org/10.1002/9781444304893.ch2

519

520

521

522

38. Warren, J. (2000). Dolomite: occurrence, evolution and economically important

523

associations. Earth-Science Reviews, 52(1-3), 1-81.
https://doi.org/10.1016/S0012-8252(00)00022-2

524

525

39. Eiler, J. M. (2007). "Clumped-isotope" geochemistry—The study of naturally-

526

occurring, multiply-substituted isotopologues. Earth and planetary science letters, 262(3-4), 309-327. https://doi.org/10.1016/j.epsl.2007.08.020

527

528

40. Lunt, D. J., Bragg, F., Chan, W. L., Hutchinson, D. K., Ladant, J. B., Morozova,

529

P., Niezgodzki, I., Steinig, S., Zhang, Z., Zhu, J., Abe-Ouchi, A., Anagnostou, E., de Boer, A. M., Coxall, H. K., Donnadieu, Y., Foster, G., Inglis, G. N., Knorr, G., Langebroek, P. M., Lear, C. H., Lohmann, G., Poulsen, C. J., Sepulchre, P.,

530

531
532

Tierney, J. E., Valdes, P. J., Volodin, E. M., Dunkley Jones, T., Hollis, C. J., Huber, M. & Otto-Bliesner, B. L. (2021). DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data. Climate of the Past, 17(1), 203-227. https://doi.org/10.5194/cp-17-203-2021

533

534

535

536

537

41. Molnar, P. (2022). Differences between soil and air temperatures: Implications for geological reconstructions of past climate. Geosphere, 18(2), 800-824. https://doi.org/10.1130/GES02448.1

538

539

540

42. Hough, B. G., Garzione, C. N., Wang, Z., Lease, R. O., Burbank, D. W., & Yuan, D. (2011). Stable isotope evidence for topographic growth and basin segmentation: Implications for the evolution of the NE Tibetan Plateau. Bulletin, 123(1-2), 168-185. https://doi.org/10.1130/B30090.1

541

542

543

544

43. Inglis, G. N., Bragg, F., Burls, N. J., Cramwinckel, M. J., Evans, D., Foster, G. L., Huber, M., Lunt, D. J., Siler, N., Steinig, S., Tierney, J. E., Wilkinson, R., Anagnostou, E., de Boer, A. M., Dunkley Jones, T., Edgar, K. M., Hollis, C. J., Hutchinson, D. K. & Pancost, R. D. (2020). Global mean surface temperature and climate sensitivity of the early Eocene Climatic Optimum (EECO), Paleocene–Eocene Thermal Maximum (PETM), and latest Paleocene. Climate of the Past, 16(5), 1953-1968. https://doi.org/10.5194/cp-16-1953-2020

545

546

547

548

549

550

551

44. Gu, C., & Renaut, R. W. (1994). The effect of Tibetan uplift on the formation and preservation of Tertiary lacustrine source-rocks in eastern China. Journal of Paleolimnology, 11, 31-40. https://doi.org/10.1007/BF00683269

552

553

554

45. Wang, B., Kim, H. J., Kikuchi, K., & Kitoh, A. (2011). Diagnostic metrics for evaluation of annual and diurnal cycles. Climate dynamics, 37, 941-955. https://doi.org/10.1007/s00382-010-0877-0

555

556
557

558

559

560

46. Dupont-Nivet, G., Krijgsman, W., Langereis, C. G., Abels, H. A., Dai, S., & Fang, X. (2007). Tibetan plateau aridification linked to global cooling at the Eocene–Oligocene transition. *Nature*, **445**(7128), 635-638.
https://doi.org/10.1038/nature05516

561

562

563

564

47. Bowen, G. J., Clyde, W. C., Koch, P. L., Ting, S., Alroy, J., Tsubamoto, T., Wang, Y. & Wang, Y. (2002). Mammalian dispersal at the Paleocene/Eocene boundary. *Science*, **295**(5562), 2062-2065.
https://doi.org/10.1126/science.1068700

565

566

567

568

569

570

48. Chaimanee, Y., Chavasseau, O., Beard, K. C., Kyaw, A. A., Soe, A. N., Sein, C., Lazzari, V., Marivaux, L., Marandat, B., Swe, M., Rugbumrung, M., Lwin, T., Valentin, X., Thein, Z. M. M. & Jaeger, J. J. (2012). Late Middle Eocene primate from Myanmar and the initial anthropoid colonization of Africa. *Proceedings of the National Academy of Sciences*, **109**(26), 10293-10297.
https://doi.org/10.1073/pnas.1200644109

571

572

573

574

575

576

49. Robin-Champigneul, F., Gravendyck, J., Huasheng, H., Woutersen, A., Pocknall, D., Meijer, N., Dupont-Nivet, G., Erkens, R. H. J., Hoorn, C. (2023) Northward expansion of the southern-temperate podocarp forest during the early Eocene: Palynological evidence from the NE Tibetan Plateau (China). *Review of Paleobotany and Palynology*, **104914**.
https://doi.org/10.1016/j.revpalbo.2023.104914

577

578

579

580

50. Fang, X., Galy, A., Yang, Y., Zhang, W., Ye, C., & Song, C. (2019). Paleogene global cooling–induced temperature feedback on chemical weathering, as recorded in the northern Tibetan Plateau. *Geology*, **47**(10), 992-996.
https://doi.org/10.1130/G46422.1

581
582 Methods

583

584 *Sampling*

585

586 Rock samples were collected after digging trenches of at least ~0.5 meter deep in the

587 Bingling Shan (BS), Caijia (CJ) and Ledu (LD) sections covering the early to middle

588 Eocene²³,³⁰. In addition, three horizons with pedogenic carbonate nodules were

589 identified and sampled at the Ledu section. Samples for plant wax analyses were

590 collected using gloves and wrapped in aluminum foil to prevent contamination.

591 Palynological samples were collected from the Bingling Shan and Caijia sections as

592 well as the East Xining (EX), Xiejia (XJ) and Dazhai (DZ) sections²³,³⁰.

593

594 *Composite section and age model*

595

596 The individual sections were combined into one composite section using litho- and

597 magnetostratigraphic correlations³⁰. First, we assembled the core of the composite

598 section by stitching the Honggou Fm of the Caijia section (CJ) and the Qijiachuan Fm

599 of the Ledu section (LD) together at the liver-brown to red mudrock transition observed

600 in both locations (transition from Qijiachuan to Honggou Fm; blue dashed line Fig. 2

601 in ref³⁰). We assume this to be a chronostratigraphic marker and define it as the 0

602 meter-level in the composite log. The stratigraphic positions of these sections can be

603 converted to the composite stratigraphic position as follows:

604

605 Comp m level = CJ [44.5m to 280m] - 44.5

606 Comp m level = LD [entire section] - 15
607

608

609

610

611

612

613

614

615

616

Caijia:

617

Comp m level = (CJ[2m to 44.5m] - 44.5) * (1 - 5.9 / 42.5)

618

= CJ[0 to 2m] - 38.6

619

Bingling Shan:

620

Comp m level = ((BS[5.2m to 43m] - 79.6) + ((BS[5.2m to 43m] - 43) / -37.8) * 8.05)

621

= BS[43m and higher] - 79.6

622

623

624

625

626

627

628

629

630

631

Based on our observation of the large negative CIE, we propose to revise the age model of ref³⁰. The previous age model is reliable down to chron C22n and constrained by the radiometric age of a tuff²³. However, chron C23n below is very short and does not fit the pattern of the geomagnetic polarity timescale³⁰. Hence, we infer an unconformity at the base of C23n which also corresponds to the lithological shift from calcareous to dolomitic mudrocks (Fig. 2). The negative CIE occurs within a long reversed polarity zone on top of a short normal zone. This polarity pattern fits well with C25n and C24r and is within the radiometric age constraints of 53.7±3.3 Ma recorded in a carbonate bed just below the CIE (Fig. 2)³⁰. The PETM and ETM2 occur in C24r
and could correlate with the CIE in the Xining Basin as discussed in the main text.
Throughout the manuscript we use the geomagnetic polarity timescale of ref⁴ for correlating our paleo-environmental data with the Cenozoic Global Reference benthic foraminifera carbon and oxygen Isotope Dataset (CENOGRID).

636

637 XRD

638

639 X-ray diffractometry (XRD) analyses were performed on 27 mudrock samples and 5 carbonate beds throughout the stratigraphy to assess the mineralogy and the carbonate type. Powdered rock samples were measured using a PANALYTICAL X'Pert Bragg-Brentano diffractometer using a copper beam powered by 30 mA and 40 KV generator current. The characteristic diffraction maxima of the mineral phases were determined using the MacDiff software (http://mill2.chem.ucl.ac.uk/ccp/web-mirrors/krumm/html/software/macdiff.html). Intensities were converted to 1° divergence characteristics and weighted by reference intensity ratios (RIR) to semiquantitatively calculate the relative abundance of each mineral phase. The identified mineral phases are (Extended Data Fig. 3): mixed-layer illite-smectite (main diffraction maxima position: 10.4 Å, RIR value: 0.52), illite/muscovite (10.0 Å, 0.43), chlorite (14.0 Å, 1.00), analcime (3.43 Å, 1.41), quartz (4.26 Å and 3.34 Å, 3.03) K-feldspar (3.25 Å, 0.60), albite (3.20 Å, 0.64), calcite (3.04 Å, 2.20) and calcian dolomite (2.91 Å, 2.51). The mol% of MgCO₃ in the calcian dolomite was estimated using the relative position of the 104 peak (d in Å) compared to calcite (3.035 Å) and stoichiometric dolomite (2.885 Å):

655

656

$$ \text{Mol\% MgCO}_3 = \frac{3.035 - d}{3.035 - 2.885} \times 50\% $$
657 *Compound-specific lipid biomarkers and stable isotopes*

658 Plant waxes were extracted from 25 mudrock and gypsiferous mudrock samples at
659 the Organic Surface Geochemistry Lab (OSGLab) at the German Research Centre for
660 Geosciences (GFZ) in Potsdam. Samples were crushed and then powdered using a
661 shatterbox with an agate grinding chamber. Soluble organic matter was extracted
662 using a Dionex accelerated solvent extractor (ASE 350) with a
663 dichloromethane/methanol mixture of 9:1 at 100°C and 1500 psi. Total extracts of
664 three 18-minute cycles were captured in 250 ml bottles, later concentrated to 4 ml in
665 a Turbovap, and then separated on silica gel using a solid phase extraction (SPE) as
666 described in ref⁵¹. The C₂₇, C₂₈, C₂₉, C₃₀, C₃₁, C₃₂, and C₃₃ *n*-alkanes were identified
667 and quantified using a gas chromatograph with a coupled flame ionization and mass-
668 selective detector (GC-FID/MSD Agilent 7890A GC, 5975C MSD) flushed with helium
669 carrier gas. Temperatures in the GC oven were programmed to increase at a rate of
670 12°C/min starting from 70°C to 320°C at which temperatures were held constant for
671 21 min. The PTV injector had a split ratio of 5:1 at an initial temperature of 70°C. The
672 *n*-alkane FID-peak areas were compared with a previously added 5α-androstane
673 standard from which *n*-alkane concentrations were calculated. The *n*-alkane
674 concentrations are reported as µg/gram dry sediment. In addition the average chain-
675 length (ACL) and the carbon preference index (CPI) were calculated.

676

677 For all samples compound specific stable isotope values were measured using a GC-
678 Isolink coupled to a Thermo Scientific MAT 253 isotope ratio mass spectrometer
679 (IRMS) at the Stable Isotope and Organic Molecular Biogeochemistry Laboratory at
680 the University of Connecticut. The *n*-alkane fractions were dried and concentrated to
681 200 µg/µl per compound in hexane for δ²Hwax measurements. Each sample was
measured in at least duplicate and in most samples triplicate analysis. The injector of the GC was operated in splitless mode at 300°C and the oven was held at 70°C for 2 minutes. The oven was heated at 15°C/min until 150°C, then heated with 5°C/min to 320°C. The final temperature was held for 10 minutes. The column effluent was transferred into an isotope ratio mass spectrometer after conversion to H₂ in a high-temperature oven at 1420°C. Stable isotopes are reported in delta notation in permil (‰). The standard deviation for each sample was better than 3‰ and the δ²Hwax are reported in Vienna Standard Mean Ocean Water scale (VSMOW). δ¹³Cwax values were measured using the same fractions used for δ²Hwax. The *n*-alkane fractions were concentrated to 60 µg/µl in hexane for δ¹³Cwax measurements. The same instrumental setup (GC-IRMS) and temperature programming was used as for the δ²Hwax measurements, only the oxidation oven was run at a lower temperature of 960°C. Duplicates were measured for each sample and a CO₂ gas with known isotopic composition was used as reference gas and δ¹³Cwax values are reported in Vienna Pee Dee Belemnite scale (VPDB). The analytical precision of each sample had a typical standard deviation of 0.5‰. Isotopic compositions were standardized using a suite of *n*-alkanes in a standard mixture.

Bulk organic stable isotopes were measured on 113 mudrock and gypsiferous mudrock samples. These samples were decarbonated twice with 6N HCl and washed with 18 M-Ohm water several times for acid removal; carbon content and organic matter δ¹³C values were then measured. Samples from the Ledu section were measured using a Costech ECS 4010 Elemental Analyzer coupled to a Thermo
707 Scientific MAT 253 gas source IRMS at the University of Washington. Samples from
708 the Caijia section were measured using a Flash Elemental Analyzer 1112 connected
709 to a Thermo Scientific MAT 253 IRMS at the Goethe University-Senckenberg BiK-F
710 Stable Isotope Facility in Frankfurt. Samples from the Bingling Shan section were
711 measured using a Flash Elemental Analyzer 2000 coupled to a Thermo Scientific
712 Delta-V IRMS at the Alfred-Wegener Institute Isotope Laboratory (AWI) in Potsdam.
713 Measured δ¹³C values (all relative to VPDB) were corrected using in-house reference
714 materials and long-term repeatability was below 0.2‰. International reference
715 materials USGS 24 and IAEA-CH-7 were analyzed along with the samples to check
716 for accuracy.

717

718 Carbonate stable isotopes were measured on 51 calcite-bearing mudrocks and 3
719 pedogenic carbonate nodules. The calcite-bearing mudrocks were reacted with 105
720 % orthophosphoric acid and carbonate δ¹⁸O and δ¹³C values were then measured.
721 Samples from the Ledu section were measured using a Thermo Scientific Kiel III
722 Carbonate Device coupled to a Thermo Scientific Delta Plus IRMS at University of
723 Washington. Samples from the Caijia section were measured with a Thermo Scientific
724 GasBench II interfaced with a Thermo Scientific MAT 253 IRMS at the Goethe
725 University-Senckenberg BiK-F Stable Isotope Facility. Measured carbon and oxygen
726 isotopic compositions were corrected using in-house reference materials as well as
727 NBS18 and NBS19 carbonate reference materials. Long-term repeatability was below
728 0.03‰ for δ¹³C and below 0.06‰ for δ¹⁸O. All δ¹³C and δ¹⁸O values are expressed
729 relative to VPDB.

730
731 Clumped isotopes were analyzed on 16 of these calcite-bearing mudrocks and on the
732 3 pedogenic nodules at the Goethe University-Senckenberg BiK-F Stable Isotope
733 Facility, using a Thermo Scientific Kiel IV Carbonate Device paired with a Thermo
734 Scientific MAT 253 Plus IRMS. The Kiel IV was modified from its original configuration
735 with the addition of two water traps and a different heating-cooling system on the
736 purification trap. Depending on the carbonate content, 110 to 2500 µg of sample was
737 reacted with 105% orthophosphoric acid at 70°C for 5 minutes starting from the last
738 acid drop. In each sequence, half of the analyses were reserved for measurement of
739 the ETH carbonate standards⁵², with ETH 1 and 2 measured in equal numbers as ETH
740 3, and with ETH 4 less frequently. Data were corrected for negative background using
741 intensities measured on the 47.5 Faraday cup during acquisition, scaled by a factor
742 that minimizes the slope between ETH 1 and 2. Baseline corrected data were
743 projected into the Intercarb Carbon-Dioxide Equilibrium Scale (I-CDES)⁵² using the
744 “independent” approach in the python package D47crunch⁵³. The resulting Δ₄₇ values
745 were converted into temperature using the calibration of ref⁵⁴. Each sample was
746 measured in 13 to 18 replicates and the errors are reported as both 68% and 95%
747 confidence intervals (1SE and 2SE respectively). Long-term repeatability of both
748 samples and ETH standards was 0.035‰.

749

750 The δ¹⁸O values of the soil water (δ¹⁸Oₗwater) are reconstructed using the Δ₄₇-derived
751 temperatures and the equation of ref⁵⁵. These values are compared with modern-day
752 δ¹⁸Oₗwater values of the summer monsoon and wintertime westerlies⁵⁶ (Extended Data
753 Fig. 5).

754
755 *Palynology*

756

757 The palynological samples were prepared by Palynological Laboratory Services
758 (Anglesey, UK) using standard palynological techniques (HCL, HF, sieving at 10µm),
759 the University of Amsterdam (Amsterdam, the Netherlands; HCL, sieving at 212µm,
760 20% pyrophosphate, acetolysis, bromoform treatment), and at the Sediment
761 Laboratory of the Vrije Universiteit (Amsterdam, the Netherlands; following methods
762 of ref⁵⁷ and described in ref⁵⁸). Plant Functional Types (PFTs) were assigned using
763 the Nearest Living Relatives (NLR) approach applied by ref⁵⁹.

764

765 *MAP reconstruction*

766

767 We use an empirical relationship which can be used to reconstruct Mean Annual
768 Precipitation (MAP) using the δ¹³C*SOM* values of top soils (O- and A-horizons)²⁴. The
769 organic matter in deeper horizons might be affected by decomposition resulting in
770 fractionation to higher δ¹³C*SOM* values⁶⁰, which would lead to an underestimation of the
771 MAP. The alluvial mudflat deposits of the Xining Basin show clear evidence of
772 pedogenesis such as vertic slickensides, mudcracks, mottling, blocky peds, and clay
773 coatings in thin sections, but no obvious horizonation due to overprinting of stacked
774 paleosols. It is therefore impossible to preselect only O- and A-horizons. Nevertheless
775 we argue that the bulk δ¹³C*SOM* values and the CIE are not strongly affected by
776 degradation because we observe no clear relationship between δ¹³C*SOM* and total
777 organic content (Extended Data Fig. 2) and the δ¹³C*SOM* values of alluvial mudflats are
778 indistinguishable from laterally equivalent gypsum beds which have a high quality of
779 organic preservation⁵⁹. In addition, an even larger CIE is observed in the *n*-alkanes
780 (δ¹³C<sub>wax</sub>) which are less affected by degradation⁶¹. If this difference in CIE is caused
781 by the decomposition of bulk organic matter, the actual CIE and precipitation changes
782 could be even larger and our MAP reconstructions should be considered as a minimum
783 estimate.

784

785 Before using the paleoprecipitation proxy, we correct the δ¹³C<sub>SOM</sub> values to account
786 for the different CO₂ δ¹³C values (δ¹³C<sub>atm</sub>) of the Paleocene/Eocene atmosphere
787 compared to the pre-industrial value of -6.5‰ that is implicit in the empirical relation²⁴.

788 We apply a -1.5‰ correction to the δ¹³C<sub>SOM</sub> values to correct for the baseline
789 Paleocene (δ¹³C<sub>atm</sub> = -5.0‰)<sup>62</sup>, a +3.1‰ correction for the PETM assuming a lowering
790 of 4.6‰ (δ¹³C<sub>atm</sub> = -9.6‰) through the injection of ¹³C-depleted carbon<sup>35,62</sup> and a -
791 1.0‰ correction for the early Eocene baseline (δ¹³C<sub>atm</sub> = -5.5‰)<sup>62</sup>. Other early Eocene
792 hyperthermals corresponded to smaller isotope excursions than the PETM and we use
793 a lowering of 3.0‰ (δ¹³C<sub>atm</sub> = -8.5‰) to illustrate the effect on the MAP reconstruction.

794 The MAP is then calculated using the following equation²⁴:

795

796 MAP (mm/year) = exp( (δ¹³C<sub>SOM</sub> + 11.94) / -2.04 )

797

798 *Carbonate characterization*

799 We have characterized the carbonates of the Xining strata following the methods of
800 ref²⁷. Thin sections were prepared for six representative mudrock samples and three
801 carbonate nodules. These were examined using cathodoluminescence (CL) and
802 plane- and cross-polarized microscopy to examine the origin and possible diagenesis
803 of the carbonates. The samples were examined at the University of Potsdam using an
804 Olympus BXFM-F polarizing microscope equipped with a lumic hot-cathode electron
source and an Olympus XC10 digital color camera. In addition, seven powdered samples were mounted on a stub and carbon coated. These were further examined at the University of Potsdam using a JEOL JSM-6510 Scanning Electron Microscope (SEM) coupled to an Oxford Instruments INCAx-act Energy Dispersive X-ray Spectrometer (EDS) to assess their mineralogy.

The calcite is a dull luminescent micrite and is observed throughout the clayey matrix (Extended Data Fig. 4 A, B). Some brighter specks of microspar are observed as well but no detrital carbonate grains nor blocky sparite in cracks, veins or vugs which would have been typical for phreatic cements³⁷,⁶³. These observations are very similar to ref²⁷ and we follow their interpretation of an early diagenetic cement forming in the vadose zone from either shallow groundwater or percolating soil water³⁷,⁶³. The δ¹⁸Ocarb values are consistent with coeval pedogenic carbonates in the region¹⁰ and the δ¹³Ccarb are very low (~-9‰ in Caijia and ~-11‰ in Ledu) as is expected during the negative CIE (Extended Data Fig. 5). The stable isotope values do show some positive linear relation (Extended Data Fig. 6) indicating the effects of evaporation⁶⁴. This suggests that the carbonates formed relatively close to the surface of the paleosol. The calcite occurs in a specific stratigraphic interval in multiple locations of the basin (Fig. 2), which suggests a primary origin rather than precipitation/reprecipitation during modern-day weathering which would have affected all mudrocks. In addition, Eocene climatic events such as the EOT have been recorded in these calcite cements with no indication for overprinting²⁷.

In addition to the calcareous mudrocks, three horizons with pedogenic nodules were observed in the Ledu section. Most of these nodules are entirely composed of micrite and floating detrital grains (Extended Data Fig. 4 C), but some contain vugs filled with
sparite indicating a phreatic overprint. These were carefully avoided when powdering
the samples for isotopic analyses. The nodules occurring in the coarse sandstone (at
53.3 Ma) show features of a mixed origin. The floating grains show an isopachous rim
of microspar / sparite while the rest of the matrix is filled with micrite (Extended Data
Fig. S4 D). This indicates an initial vadose origin for the micrite which is overprinted
by phreatic cements filling circum-granular cracks³⁷.

Dolomite occurs as rhombic crystals within the mudrock matrix (Extended Data Fig. 4 E and F), but also as massive cm-scale beds interbedding lacustrine mudrocks (Extended Data Fig. 4 G) and as cm-scale burrows (Extended Data Fig. 4 H). The SEM-EDS analysis revealed that the dolomites are non-ferroan but calcian dolomite with an XRD peak at ~2.91 Å (Extended Data Fig. 3) and MgCO₃ contents ranging from 44 to 46%. No dolomite has been reported from the mountain ranges surrounding the Xining Basin⁶⁵ and a detrital origin is therefore unlikely. Instead, the dolomite could have formed either by diagenetic replacement of calcite or syn-sedimentary / early-diagenetic precipitation from saline brines on a mudflat ³⁸,⁶⁶⁻⁶⁸. We note that the dolomite co-occurs in a specific stratigraphic interval with analcime, which typically forms in saline brines⁶⁹, and with increased concentrations of hematite⁷⁰ indicative of dry conditions⁷¹. This suggests a paleo-environmental control on the formation of calcian dolomite, but we cannot rule out the role of diagenetic replacement.

848

849 *DeepMIP climate model simulations*

850

851 We use the DeepMIP climate model ensemble⁴⁰ to compare our proxy

reconstructions with simulated early Eocene precipitation and temperature
853 estimates. The paleolocation of the Xining Basin was reconstructed using the
854 hotspot reference frame ref⁷² at 55 Ma

855 (https://www.odsn.de/odsn/services/paleomap/paleomap.html). This resulted in a
856 paleolocation (102.5°N, 39.5°E) which fits well in relation to paleotopographic
857 features such as the Hangay Dome and Qinling belt that are observed on the
858 paleogeographic map used in the DeepMIP simulations⁷³.

859

860 **Data availability**

861 Palynology counts, TOC and bulk organic δ¹³C, *n*-alkane δ¹³C and δ²H, XRD bulk
862 mineralogy and carbonate δ¹³C, δ¹⁸O and Δ₄₇ are available at
863 https://doi.org/10.1594/PANGAEA.962894. The DeepMIP preindustrial and Eocene
864 climate model simulations are available by following the instructions at
865 https://www.deepmip.org/data-eocene/. The weather station data from Xining and
866 Tashkent is available at https://www.ncei.noaa.gov/products/wmo-climate-normals.

867

868 **Methods references**

869 51. Rohrmann, A., Sachse, D., Mulch, A., Pingel, H., Tofelde, S., Alonso, R. N., & 870 Strecker, M. R. (2016). Miocene orographic uplift forces rapid hydrological 871 change in the southern central Andes. Scientific reports, 6(1), 35678. 872 https://doi.org/10.1038/srep35678

873 52. Bernasconi, S., Daëron, M., Bergmann, K., Bonifacie, M., Meckler, A. N., Affek, 874 H., et al. (2021). InterCarb: A community effort to improve inter-laboratory 875 standardization of the carbonate clumped isotope thermometer using 876 carbonate standards.
877

878

879

53. Daëron, M. (2021). Full propagation of analytical uncertainties in Δ47 measurements. Geochemistry, Geophysics, Geosystems, 22(5), e2020GC009592. https://doi.org/10.1029/2020GC009592

880

881

882

883

54. Anderson, N. T., Kelson, J. R., Kele, S., Daëron, M., Bonifacie, M., Horita, J., et al. (2021). A unified clumped isotope thermometer calibration (0.5–1100°C) using carbonate-based standardization. Geophysical Research Letters, 48(7), e2020GL092069. https://doi.org/10.1029/2020gl092069

884

885

886

55. Kim, S. T., & O'Neil, J. R. (1997). Equilibrium and nonequilibrium oxygen isotope effects in synthetic carbonates. Geochimica et cosmochimica acta, 61(16), 3461-3475. https://doi.org/10.1016/S0016-7037(97)00169-5

887

888

889

56. Araguás-Araguás, L., Froehlich, K., & Rozanski, K. (1998). Stable isotope composition of precipitation over Southeast Asia. Journal of Geophysical Research, 103(D22), 28721-28742. https://doi.org/10.1029/98jd02582

890

57. Horowitz, A. (1992). Palynology of arid lands. Elsevier Science, 568 p.

891

892

893

58. Dupont-Nivet, G., Hoorn, C., & Konert, M. (2008). Tibetan uplift prior to the Eocene-Oligocene climate transition: Evidence from pollen analysis of the Xining Basin. Geology, 36(12), 987-990. https://doi.org/10.1130/G25063A.1

894

895

896

897

59. Hoorn, C., Straathof, J., Abels, H. A., Xu, Y., Utescher, T., & Dupont-Nivet, G. (2012). A late Eocene palynological record of climate change and Tibetan plateau uplift (Xining Basin, China). Palaeogeography, Palaeoclimatology, Palaeoecology, 344, 16-38. https://doi.org/10.1016/j.palaeo.2012.05.011

898

899

900

60. Wynn, J. G. (2007). Carbon isotope fractionation during decomposition of organic matter in soils and paleosols: implications for paleoecological interpretations of paleosols. Palaeogeography, Palaeoclimatology,
901

Palaeoecology,

251(3-4),

437-448.

902

https://doi.org/10.1016/j.palaeo.2007.04.009

903

61. Diefendorf, A. F., & Freimuth, E. J. (2017). Extracting the most from terrestrial

904

plant-derived n-alkyl lipids and their carbon isotopes from the sedimentary

905

record: A review. Organic Geochemistry,

103,

1-21.

906

https://doi.org/10.1016/j.orggeochem.2016.10.016

907

62. Tipple, B. J., Meyers, S. R., & Pagani, M. (2010). Carbon isotope ratio of

908

Cenozoic CO2: A comparative evaluation of available geochemical proxies.

909

Paleoceanography, 25(3). https://doi.org/10.1029/2009PA001851

910

63. Mack, G. H., Cole, D. R., & Treviño, L. (2000). The distribution and

911

discrimination of shallow, authigenic carbonate in the Pliocene–Pleistocene

912

Palomas Basin, southern Rio Grande rift. Geological Society of America

913

Bulletin, 112(5), 643-656.

https://doi.org/10.1130/0016-

914

7606(2000)112<643:TDADOS>2.0.CO;2

915

64. Quade, J., Rech, J. A., Latorre, C., Betancourt, J. L., Gleeson, E., & Kalin, M.

916

T. (2007). Soils at the hyperarid margin: the isotopic composition of soil

917

carbonate from the Atacama Desert, Northern Chile. Geochimica et

918

Cosmochimica Acta, 71(15), 3772-3795.

919

https://doi.org/10.1016/j.gca.2007.02.016

920

65. Bureau of Geological and Mineral Resources of Qinghai Province (BGMRQP).

921

(1965). Regional geological survey reports of Ledu sheet (1:200000), Qinghai

922

Province, P.R. China (in Chinese).

923

66. Last, W. M. (1990). Lacustrine dolomite—an overview of modern, Holocene,

924

and Pleistocene occurrences. Earth-Science Reviews, 27(3), 221-263.

925

https://doi.org/10.1016/0012-8252(90)90004-F
926

67. Peterson, M. N. A., Bien, G. S., & Berner, R. A. (1963). Radiocarbon studies of recent dolomite from Deep Spring Lake, California. Journal of Geophysical Research, 68(24), 6493-6505. https://doi.org/10.1029/JZ068i024p06493

927

928

929

68. Wolfbauer, C. A., & Surdam, R. C. (1974). Origin of nonmarine dolomite in Eocene Lake Gosiute, Green River Basin, Wyoming. Geological Society of America Bulletin, 85(11), 1733-1740. https://doi.org/10.1130/0016-7606(1974)85<1733:OONDIE>2.0.CO;2

930

931

932

933

69. Remy, R. R., & Ferrell, R. E. (1989). Distribution and origin of analcime in marginal lacustrine mudstones of the Green River Formation, south-central Uinta Basin, Utah. Clays and Clay minerals, 37, 419-432. https://doi.org/10.1346/CCMN.1989.0370505

934

935

936

937

70. Fang, X., Zan, J., Appel, E., Lu, Y., Song, C., Dai, S., & Tuo, S. (2015). An Eocene–Miocene continuous rock magnetic record from the sediments in the Xining Basin, NW China: Indication for Cenozoic persistent drying driven by global cooling and Tibetan Plateau uplift. Geophysical Journal International, 201(1), 78–89. https://doi.org/10.1093/gji/ggv002

938

939

940

941

942

71. Lepre, C. J., & Olsen, P. E. (2021). Hematite reconstruction of Late Triassic hydroclimate over the Colorado Plateau. Proceedings of the National Academy of Sciences, 118(7), e2004343118. https://doi.org/10.1073/pnas.2004343118

943

944

945

72. Müller, R. D., Royer, J. Y., & Lawver, L. A. (1993). Revised plate motions relative to the hotspots from combined Atlantic and Indian Ocean hotspot tracks. Geology, 21(3), 275-278. https://doi.org/10.1130/0091-7613(1993)021<0275:RPMRTT>2.3.CO;2

946

947

948

949

73. Herold, N., Buzan, J., Seton, M., Goldner, A., Green, J. A. M., Müller, R. D., Markwick, P. & Huber, M. (2014). A suite of early Eocene (~ 55 Ma) climate

950
951

model boundary conditions. Geoscientific Model Development, 7(5), 2077-2090. https://doi.org/10.5194/gmd-7-2077-2014

952

953

74. Laskar, J., Fienga, A., Gastineau, M., & Manche, H. (2011). La2010: a new orbital solution for the long-term motion of the Earth. Astronomy & Astrophysics, 532, A89. https://doi.org/10.1051/0004-6361/201116836

954

955

956

957

Extended Data

<figure><img src="image_6.png" /></figure>

958

959

Extended Data Fig. 1. Pre-industrial control simulations and weather station data from

960

the Xining Basin. Weather station precipitation data

961

(https://www.ncei.noaa.gov/products/wmo-climate-normals) and pre-industrial control
simulations of A) temperature and B) precipitation in the Xining Basin using the DeepMIP climate model ensemble.

<figure><img src="image_7.png" /></figure>

Extended Data Fig. 2. Soil organic matter δ¹³C versus Total Organic Content (TOC).
<figure><img src="image_8.png" /></figure>

966

Extended Data Fig. 3. XRD diffractograms showing the dominant peaks and bulk mineralogy of selected samples including: a dolomite bed (CjC9, as shown on Extended Data Fig. 4G; composite position: -37.1 m), a calcareous mudrock (16Cj237.5; composite position: 193 m), a calcareous mudrock from the CIE interval (18Ld-16; composite position: -31m) and a dolomitic mudrock (15Cj79; composite position: 54 m). The samples 16Cj237.5 and 18Ld-16 were used for stable and clumped isotope analyses.

968

969

970

971

972

973
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

974

975

976

977

Extended Data Fig. 4. Microscope and field photographs. A) and B) Cross-polarized and cathodoluminescence image of a mudrock sample with vadose-grown calcite cement (18LD-15; Ledu section; -15 meter-level) showing silt-sized matrix with
dispersed organic matter, dull luminescent micrite and some luminescent microsparite and sparite. Plane-polarized images of pedogenic nodules showing: C) Micrite matrix with floating detrital grains in 18LD+4nodB (Ledu section; 12.3 meter-level). D) Floating detrital grains with isopachous microsparite to sparite rim and micritic matrix in 18LDconglonod (Ledu section; -60 meter-level). Massive red dolomitic mudrock samples showing rhombohedral dolomite crystals in E) plane-polarized light (15CJ-111_75; Caijia section 131.25 meter-level) and F) SEM (15CJ-112_5; Caijia section; 132 meter-level). G) Greenish lacustrine mudrocks interbedded with massive dolomite beds (Caijia section; 75 meter-level), hammer for scale. H) Dolomite-filled burrow (Caijia section; 93 meter-level).

<figure><img src="image_17.png" /></figure>
Extended Data Fig. 5. Carbonate and plant wax stable isotopes. Stable isotope record (δ¹⁸Ocarb and δ¹³Ccarb) of the vadose-grown and pedogenic carbonates and δ²Hwax values of plant waxes. δ¹⁸O values of the soil water (δ18Owater) are reconstructed using the Δ₄₇-derived temperatures. Modern-day δ¹⁸Owater values of the summer monsoon and wintertime westerlies are shown⁵⁷.

<figure><img src="image_18.png" /></figure>

Extended Data Fig. 6. Carbonate stable isotope biplot. Stable isotope biplot of the studied calcites.
<figure><img src="image_19.png" /></figure>

Extended Data Fig. 7. Monsoonal domains in DeepMIP climate model simulations.

Distribution of monsoonal domains in the pre-industrial control and 3x pCO₂ Eocene

DeepMIP simulations. Summer (MJJAS) minus winter precipitation (NDJFM) is used
1001 as a metric and regions where this difference is > 2.5 mm/day are considered
1002 monsoonal<sup>44</sup>. Red dot indicates the location of the Xining Basin.

<figure><img src="image_20.png" /></figure>

1003 Extended Data Fig. 8. Timing of Xining CIE compared with CENOGRID and
1004 astronomical solutions. CENOGRID showing the evolution of benthic foraminifera
1005 stable isotope values⁴. The δ¹⁸O values show peak warmth of the EECO and the δ¹³C
1006 values show several hyperthermal events characterized by negative CIE's. The
1007 astronomical solutions⁷⁶ show the evolution of the eccentricity of Earth's orbit. The
1008 radiometric ages bracketing the CIE in the Xining Basin are indicated.
1009
<figure><img src="image_21.png" /></figure>

1010

1011 Extended Data Fig. 9. Summer sea-level atmospheric pressure anomalies in DeepMIP
1012 climate model simulations. Sea-level atmospheric pressure anomalies during summer
1013 (JJA) in the 6x pCO₂ Eocene and the pre-industrial control simulations of the DeepMIP
1014 ensemble. Red dot indicates the location of the Xining Basin.

1015