Orbital- and millennial-scale Asian winter monsoon variability across the Pliocene–Pleistocene glacial intensification

Domain: earth_science
Published: 2024-04-19
Editorial outcome: minor_revision

Abstract
Intensification of northern hemisphere glaciation (iNHG), ~2.7 million years ago (Ma), led to establishment of the Pleistocene to present-day bipolar icehouse state. Here we document evolution of orbital- and millennial-scale Asian winter monsoon (AWM) variability across the iNHG using a palaeomagnetically dated centennial-resolution grain size record between 3.6 and 1.9 Ma from a previously undescribed loess-palaeosol/red clay section on the central Chinese Loess Plateau. We find that the late Pliocene–early Pleistocene AWM was characterized by combined 41-kyr and ~100-kyr cycles, in response to ice volume and atmospheric CO2 forcing. Northern hemisphere ice sheet expansion, which was accompanied by an atmospheric CO2 concentration decline, substantially increased glacial AWM intensity and its orbitally oscillating amplitudes across the iNHG. Superposed on orbital variability, we find that millennial AWM intensity fluctuations persisted during both the warmer (higher-CO2) late Pliocene and colder (lower-CO2) early Pleistocene, in response to both external astronomical forcing and internal climate dynamics.

Introduction
A warm climate state most recently experienced in the late Pliocene (Piacenzian stage) 3.6–2.58 million years ago (Ma)1. In particular, during the mid-Piacenzian warm period at ~3.3–3 Ma, globally averaged temperatures were 2–4 °C higher than preindustrial conditions2–4 and global mean sea levels were ~20 m above the present level5,6, yet atmospheric CO2 concentrations were comparable to present-day values1,3,4,7–10. Following this climatic optimum, global climate cooled and high-latitude northern hemisphere (NH) regions became increasingly glaciated from ~3 Ma onward1. Notably, distinct and widespread intensification of NH glaciation (iNHG) occurred across the Pliocene–Pleistocene transition (2.58 Ma), which was marked by development of large, thick ice sheets in Greenland, North America, and Eurasia, while ice-rafted debris inputs to the North Pacific and North Atlantic Oceans increased substantially1,5,6. The iNHG marks a threshold in the long-term cooling trend to a well-established bipolar icehouse state that persists today1,5,11. High-resolution climate reconstructions across the iNHG are crucial for better understanding past, modern, and future climate processes under a broader range of climate-cryosphere boundary conditions beyond the permanent bipolar icehouse state that marked the Pleistocene. However, orbital- and millennial-scale climate variability remains poorly constrained across the iNHG, especially within continental interior settings that host much of the present global population. Millennial variability in mean annual air temperature oscillations throughout the last glacial cycle is reconstructed from Greenland ice cores (i.e., Dansgaard–Oeschger cycles)12 and from multiple centennial-resolution records from the North Atlantic Ocean, Mediterranean, Iberian margin, Balkan Peninsula (Lake Ohrid), and Chinese Loess Plateau (CLP) throughout the last 1.5 million years (Myr)13–16. However, millennial climate variability before 1.5 Ma remains underexplored in both oceanic and terrestrial settings.

As the largest monsoon system on Earth, the Asian monsoon determines climatic and environmental conditions over the South–East Asian continent, large parts of which are populated densely17. During boreal winters, cold air from the Siberian High pressure cell over the mid- to high-latitude Asian continental interior induces northwesterly Asian winter monsoon (AWM) advection (Fig. 1a). Conversely, the Asian summer monsoon (ASM) transports heat and moisture from the western Pacific and Indian Oceans across South Asia and tropical East Asia to North China and Japan during summers (Supplementary Fig. 1a).

The CLP is located at the transition between humid and arid regions in north-central China and harbors a vast expanse (~640,000 km2) of thick aeolian dust deposits (up to 1 km thickness). These deposits comprise a Neogene red clay sequence stratigraphically succeeded by a Quaternary sequence of alternating yellow loess and red palaeosol layers18–21. Magneto-stratigraphic results suggest that the transition from red clay to loess-palaeosol sequences across the CLP occurred synchronously around the Gauss–Matuyama boundary at 2.58 Ma20–26, which enables robustly-dated studies of climate changes across the iNHG. These dust deposits are sourced from the inland Gobi Desert and other nearby sandy deserts and poorly-vegetated areas and transported primarily by the near-surface northwesterly AWM27 (Fig. 1b). Grain-size variability of these wind-blown dust deposits is largely controlled by AWM intensity, with additional influence of transport distance and changes in sediment source regions21,23,28–31. High-resolution grain size records spanning from the Pliocene red clay to Pleistocene loess-palaeosol sequences can, therefore, provide indications of detailed temporal AWM intensity variations across the iNHG. CLP grain size studies suggest distinct orbital-scale Pleistocene AWM variability, persistent millennial-scale variability over the last 1.5 Myr, and stepwise mean state intensifications across the iNHG and mid-Pleistocene transition (MPT, 1.25–0.6 Ma)13,19,23,30,32–37. However, these studies lack detailed assessment of concurrent orbital- and millennial-scale AWM variability across the iNHG. To fill this gap, here we present a centennial-resolution CLP grain size record, which is dated between 3.6 and 1.9 Ma by magnetostratigraphy, to assess (1) secular evolution, (2) orbital- and millennial-scale variability, and (3) the underlying AWM dynamics across the iNHG that is marked by substantial climate-cryosphere boundary condition changes. By doing so, we extend the oldest record of co-occurring orbital- and millennial-scale AWM variability13 by >2 Myr, into the relatively warmer Pliocene.

Results
Our study site, the Chongxin section (35°15′ N, 107°8′ E), is located on the central CLP under the influence of seasonally alternating AWM and ASM circulation (Fig. 1c). The central CLP is covered with quasi-continuous Pleistocene loess-palaeosol and Pliocene red clay sequences20,21,32 compared to some sections on the northern (desert) margin of the CLP which may feature erosional hiatuses38. In the Pleistocene loess-palaeosol sequence, loess layers that formed during colder/drier intervals with lower ASM precipitation and stronger AWM winds are yellow, whereas intercalated palaeosol layers that formed during warmer/wetter intervals with higher ASM precipitation and weaker AWM winds are light red (Supplementary Fig. 1b). The underlying red clay, which was deposited under warmer and more sustained moist Pliocene conditions, has a higher saturated red colouration than the Pleistocene palaeosols (Supplementary Fig. 1b). We collected 3571 unoriented samples from the Chongxin loess-palaeosol/red clay section, which spans from the late Pliocene to early Pleistocene, at 2 cm intervals for grain size analysis. This large dataset resolves grain size variations on an average temporal resolution of ~0.5 kyr, which is unprecedented in both marine and terrestrial realms for this time interval. It enables detailed assessment of orbital- and millennial-scale AWM dynamics across the iNHG. We also collected 251 oriented block samples for magnetostratigraphic analysis.

Detailed rock magnetic and palaeomagnetic analyses establish a magnetochronology for the Chongxin section (“Methods”; Fig. 2a and Supplementary Figs. 2–6). Magnetite was identified as the major characteristic remanent magnetization (ChRM) carrier (“Methods”; Supplementary Figs. 2–6). Following removal of a low-temperature secondary overprint at temperatures up to 200–300 °C, a ChRM was isolated during subsequent stepwise thermal demagnetization up to 620 °C (Supplementary Fig. 6). From 251 demagnetized samples, 212 yielded stable ChRM directions, from which virtual geomagnetic pole (VGP) latitudes were calculated to establish a magnetostratigraphic zonation. The Chongxin magnetostratigraphic sequence has a distinct pattern of five normal and five reverse polarity zones, spanning from just below the Gilbert–Gauss reversal boundary to the normal polarity Olduvai subchron of the geomagnetic polarity timescale (GPTS)39 (Fig. 2a, b and Supplementary Fig. 7a, b). This magnetochronology is consistent with magnetostratigraphic correlations of other CLP red clay/loess-palaeosol sections20,21,23–26 (Supplementary Fig. 7). The Gauss–Matuyama boundary is located consistently around the transition from red clay to loess-palaeosol sequences. The base of the Olduvai subchron is situated (1) around the S26–L26 boundary in the Chongxin section, (2) in the lower part of palaeosol S26 in the Jingchuan20, Xifeng23, and Lingtai sections21, and (3) in the upper part of loess L27 in the Baoji section20. This slight displacement of geomagnetic polarity reversals in different sections may be linked to slightly variable post-depositional remanent magnetization lock-in depth across the CLP40 and/or different sampling intervals of magnetostratigraphic records. The short-duration Réunion geomagnetic excursion is not registered in most studied loess-palaeosol sections20,24, but appears clearly in the Chongxin section (Fig. 2a and Supplementary Fig. 7). We identify the Réunion excursion between the upper part of loess L28 and the lower part of palaeosol S27, broadly consistent with its location within loess L28 in the Shangchen section on the southern CLP margin41. The early Pleistocene loess-palaeosol sequence has a higher sedimentation rate than the underlying red clay and corresponds to the long Matuyama reverse polarity chron between the Gauss–Matuyama reversal boundary and the normal polarity Olduvai subchron. Consequently, the early Pleistocene loess-palaeosol sequence (in the Matuyama polarity chron) has a relatively coarser palaeomagnetic sample spacing in the depth domain, compared to the Pliocene red clay sequence in the Gauss polarity chron. However, our Matuyama polarity chron data are sufficiently dense to enable straightforward correlation to the GPTS and other CLP red clay/loess-palaeosol magnetostratigraphic sequences (Fig. 2a, b and Supplementary Fig. 7). Based on correlation to the 2020 GPTS39, linear interpolation between subsequent tie points using the identified geomagnetic polarity reversals yields a magnetochronology between ~3.60 and 1.94 Ma, i.e., a late Pliocene to early Pleistocene time interval (Piacenzian and Gelasian stages). Astronomical tuning is a routine approach for constructing more precise and accurate age models for CLP loess-palaeosol/red clay sequences, especially once an initial magnetostratigraphic age model has been developed20,23,42. We refined the Chongxin magnetostratigraphic age model by obliquity-tuning of the bulk sample mean grain size (MGS) record (AWM indicator) using an automatic orbital tuning procedure43 (“Methods”; Supplementary Figs. 8 and 9).

MGS records from bulk samples and extracted quartz particles have almost identical orbital cycles for both Pliocene red clay and Pleistocene loess-palaeosol sequences (see Fig. 2 in ref. 21), albeit with some differences in the magnitude of glacial–interglacial pacing and interglacial minima21,23,36. Overall consistency of orbital cycles suggests that the MGS of CLP bulk samples is as effective as MGS from extracted quartz particles in recording AWM intensity, without significant pedogenic overprinting. We, therefore, primarily employ the more commonly used bulk red clay and loess-palaeosol grain size13,19,20,30,31,35 to assess AWM variations. We measured grain size distributions for all 3571 unoriented bulk samples after laboratory organic matter and carbonate removal (“Methods”).

The Chongxin MGS record has distinct glacial-interglacial variability throughout the 3.6–1.9 Ma interval, which is broadly comparable to global mean sea level reconstructed from deep-sea-carbonate-microfossil–based δ18O records5 (Fig. 2c, e). Subtle differences are also observed in exact glacial-interglacial cycle shapes, which are, for example, more symmetrical in the sea level record. Generally, glacials have coarser grain sizes and stronger AWM winds than interglacials (Fig. 2c), consistent with Pleistocene observations and theory/model climate predictions13,21,30,31,44. Glacial MGS values increase markedly during marine isotope stage (MIS) G5 around 2.7 Ma and become even coarser after 2.6 Ma (Fig. 2c), which is indicative of increased dust transport capacity by stronger AWM winds from drier source regions to the north and west of the CLP under colder conditions across the iNHG21,30,31,36,45. Such glacial loess coarsening induced larger orbital-scale MGS oscillations across the iNHG (Fig. 2c). Generally, the early Pleistocene loess-palaeosol sequence has slightly coarser interglacial MGS values (~7–11 μm) but substantially coarser glacial MGS values (~11–14 μm) than the Pliocene red clay (typically ~7–8 μm in interglacials and ~8–10 μm in glacials), which is consistent with greater AWM intensification during glacials compared to interglacials across the iNHG. The larger orbital-scale Pleistocene MGS oscillations are more distinct in the <200 kyr filtered MGS record (Fig. 2d; “Methods”). Similarly increased glacial-interglacial amplitudes across the iNHG are also observed in the global mean sea level record5 and its <200 kyr filtered counterpart (Fig. 2e, f; “Methods”). Cross-wavelet and cross-power spectral analyses of the Chongxin MGS and global mean sea level5 records suggest that they have high coherency on the ~100-kyr and 41-kyr bands (Fig. 3), although their phase relationship varies over time (Fig. 3a, arrow directions vary through time). Cross-wavelet spectral analysis further confirms that the 41-kyr and ~100-kyr signals are enhanced across the iNHG, consistent with increased orbitally oscillating amplitudes (Figs. 2 and 3). Cross-power spectral analysis suggests that the 41-kyr band is statistically higher than the ~100-kyr band.

The Pliocene red clay sequence has thicker more homogeneous palaeosols that are redder in color and lack thick yellow loess intercalations typical of the overlying Pleistocene loess-palaeosol sequence (Supplementary Fig. 1b). Consistent with MGS changes across the iNHG, the red clay sequence transitioned to the loess-palaeosol sequence synchronously at Gauss–Matuyama boundary time as is documented across the entire CLP (Supplementary Fig. 7). The rapid lithological shift across the iNHG is a consequence of both glacial AWM strengthening (Fig. 2c) that increased dust transport and accumulation rates (Fig. 2a, b), and ASM weakening as indicated by distinct decreases in magnetic susceptibility23, rates of chemical weathering19,46, and soil carbonate δ13C values19. AWM strengthening and ASM weakening were likely results of the colder and more intensely glaciated Pleistocene5 associated with lower atmospheric CO2 concentrations3,7–11,47–50 (Fig. 2e–h).

In addition to orbital variability, previous high-resolution CLP loess-palaeosol grain size records spanning the past 1.5 Myr also suggest superposed millennial and even centennial variations13,33,51,52. Millennial and centennial oscillations in these younger records have lower amplitude than the orbital variability but higher amplitudes than analytical uncertainties associated with grain size measurements13,33,51,52 (Supplementary Fig. 10). Our centennial-resolution MGS record reveals that lower-amplitude millennial oscillations were also superposed on higher-amplitude orbital-scale AWM variability between 3.6 Ma and 1.9 Ma, i.e., during the late Pliocene–early Pleistocene and across the iNHG (Fig. 2c), similar to what was previously recognized for the time interval spanning the last 1.5 Myr13,33. Expression of millennial-scale climate variability becomes more distinct in the <10 kyr filtered MGS record (Fig. 2i and Supplementary Fig. 10; “Methods”). As is the case for increased orbital amplitudes, the <10 kyr filtered MGS record is also marked by increased millennial-scale cycle amplitudes after ~2.66 Ma (Fig. 2i). Wavelet and power spectral analyses of the <10 kyr filtered MGS record reveal statistically significant millennial peaks against a red noise model primarily between the 7-kyr and 1-kyr frequencies (Fig. 4). We note that millennial-scale age model uncertainties, which are linked to small uncertainties in geomagnetic boundaries and orbital tuning, sampling resolution, and smoothing related to pedogenesis, may have influenced expression of exact millennial periodicities. However, the combined effect of these factors was not strong enough to suppress the prevailing millennial variability in our centennial-resolution MGS record.

Orbital-scale AWM dynamics
Our AWM proxy record, combined with a published global mean sea level record, indicates that ~100-kyr variability was present across the iNHG (Fig. 3), comparable to the interval after the MPT as recognized previously34,35,37. Consistent variation in orbital-scale global mean sea level and Chongxin MGS periodicities and amplitudes across the iNHG suggest that the NH ice volume forcing of orbital-scale AWM variability observed during the last 1.6 Myr30,31,37 can be extended back to the late Pliocene–early Pleistocene. Generally, atmospheric CO2 concentrations varied in pace with global mean sea level and temperature records on orbital timescales, which is well documented by proxy reconstructions and inverse forward modeling outputs for the last 800 kyr5,7,53,54. CO2 is the principal greenhouse gas that amplified Earth’s climate response to orbital forcing and largely determined Earth’s thermal state. In addition to previously recognized NH ice volume forcing, orbital-scale atmospheric CO2 forcing is also a key factor for Plio-Pleistocene AWM evolution. Continuous, orbitally resolved proxy-based CO2 reconstructions from 3.6 to 1.9 Ma are currently unavailable. However, inverse forward modeling CO2 estimates spanning the past 3.6 Myr7 and shorter proxy-based CO2 reconstructions spanning from 3.6 to 1.9 Ma3,8–11,47–50 indicate that atmospheric CO2 concentrations have similar orbital periodicities across the iNHG as global mean sea level and North Atlantic Ocean sea surface temperature records (Fig. 2e–h). This suggests that although various CO2 reconstructions/model outputs may differ slightly from each other, it is plausible that strong coupling between climate and CO2, as observed for the middle and late Pleistocene, was also a feature of late Pliocene–early Pleistocene climate. Glacial CO2 lowering across the iNHG is distinct in both proxy and inverse forward modeling reconstructions (Fig. 2h). We infer that combined ice volume and radiative forcing (through both insolation and atmospheric CO2 concentration changes) governed late Pliocene–early Pleistocene orbital-scale AWM variability, likely via both regional and global temperature modulations. The striking match between (1) a high-resolution sea surface temperature record from the North Atlantic Ocean55,56 (Fig. 2g), (2) a global mean sea level record5 (Fig. 2e), and (3) our grain size records over glacial-interglacial cycles across the iNHG (Fig. 2c), is consistent with the global ice volume/CO2 forcing scenario. Moreover, typical glacial values shifted substantially in all three records across the iNHG, with lower sea surface temperatures and global mean sea levels corresponding to larger grain sizes (Fig. 2). Generally, larger ice sheets across the iNHG decreased Asian winter temperatures through increased albedo and atmospheric and oceanic circulation changes30,31,44,57, while contemporaneous lower atmospheric CO2 concentrations decreased Asian winter temperatures via weakened (regional) radiative forcing. This led to lower Asian winter temperatures, and, hence, enhanced the Siberian High pressure cell. In turn, this would have led to stronger AWM circulation during the colder Pleistocene. A marked stepwise glacial AWM intensity increase across the iNHG suggests a threshold AWM response to the more gradually increasing NH land-ice volume and decreasing global atmospheric CO2 concentration (Fig. 2). After the ice volume/CO2 threshold was passed across the iNHG, the glacial AWM thus switched modes to a more intense circulatory pattern.

Glacial AWM intensification across the iNHG is also suggested by several CLP grain size records from the east and south of our study site23,24 (Supplementary Fig. 11c–f). However, orbital AWM variability is not expressed as clearly in these records as in our centennial-resolution Chongxin grain size record, possibly because of their lower temporal (sampling) resolutions. Especially the persistence of orbital AWM variability from 3.6 to ~2.7 Ma is distinct in our record but is largely subdued or absent in previous records. Hence, we demonstrate that the AWM had a distinct orbital variability from 3.6 Ma onward, in dynamic response to a combination of ice volume and atmospheric CO2 forcing. Consistent with global climatic trends and evolution, our higher resolution MGS record also indicates that glacial-interglacial AWM amplitudes were relatively lower before the iNHG.

Millennial AWM dynamics
Our high-resolution Chongxin grain size record is marked by persistent millennial variability superposed on orbitally-paced AWM variability throughout the late Pliocene–early Pleistocene (Figs. 2 and 4). It constitutes the oldest evidence reported for millennial AWM variability, more than two million years older than recent observations from other CLP records (<1.5 Ma)13,58. This finding is important for understanding millennial-scale climate dynamics in general (i.e., the Asian monsoon system is an integral part of the global climate system), because we document prevailing millennial AWM variability in both the colder, lower-CO2 Pleistocene state and the more moderate glacials and warmer interglacials of the higher-CO2 Pliocene world. We infer that millennial AWM variability can exist across a much broader range of climate-cryosphere boundary conditions than previously recognized, and may be a pervasive, long-term feature intrinsically linked to orbital-scale variability in the geological past13–16,59–61. For example, Tarim Basin loess records suggest that lower-amplitude millennial-scale oscillations are superposed on larger-amplitude orbital variability in Westerly winds over the last 3.6 Myr62. Similar intriguing co-occurring millennial- and orbital-scale variability exists in multiple North Atlantic Ocean records during the last 3.2 Myr14,59. Modern observations and model simulations suggest that abrupt AWM intensity changes are closely related to high-latitude NH temperature changes63–65 (Fig. 1a). Similarly, millennial AWM variations were probably linked to NH temperature changes between 3.6 and 1.9 Ma, and influenced by (1) ice sheet dynamics, (2) oceanic meridional overturning circulation, (3) radiative forcing, and/or (4) combination tones and harmonics of primary orbital climate cycles14,16,60,61,66–74. Model simulations suggest that independent minor changes in NH ice sheet thickness, greenhouse gas concentrations, and insolation can trigger prominent millennial-scale NH climate variations through sea ice-ocean-atmosphere interactions or Atlantic meridional overturning circulation (AMOC)66–70. Carbon and neodymium isotopic compositions of North Atlantic Ocean sediments suggest distinct late Pliocene–early Pleistocene millennial AMOC oscillations75. Combination tones and harmonics of Milankovitch cycles can also induce millennial-scale NH climate variability60,61,72–74, especially on multi-millennial time scales. Similar mechanisms probably governed late Pliocene–early Pleistocene millennial AWM variability. We infer that both internal climate dynamics (ice sheet dynamics, ocean-atmosphere condition changes, and combination tones and harmonics of primary astronomical cyclicity) and external astronomical forcing (insolation) may have contributed to the observed late Pliocene–early Pleistocene millennial AWM variability by modulating high-latitude Asian winter temperature.

Our unique centennial-resolution 3.6–1.9 Ma grain size record from a representative aeolian red clay and loess-palaeosol sequence from the central CLP provides critical insights into both orbital- and millennial-scale monsoon variability during a key interval from the late Pliocene to early Pleistocene and across the iNHG. NH ice sheet expansion and atmospheric CO2 decrease enhanced glacial AWM intensity but did not shift its orbital-scale periodicities across the iNHG. Both 41-kyr and ~100-kyr cycles existed in the late Pliocene–early Pleistocene AWM in response to both ice volume and atmospheric CO2 drivers. Superposed on orbital-scale changes in our centennial-resolution grain size record are millennial AWM variations. We show that millennial AWM variability persisted during both glacials and interglacials of the warmer late Pliocene–early Pleistocene. Millennial AWM oscillations thus occurred across a broader range of climate-cryosphere boundary conditions and more than two million years earlier than previously recognized. These millennial AWM variations probably constitute a long-term, pervasive feature of monsoon-dominated (hydro-) climate variability that was governed by both external astronomical forcing and internal Earth climate dynamics.

Methods
Sampling
After cleaning and removal of surface outcrop, we collected 3571 unoriented samples from the Chongxin section, central CLP, at 2 cm intervals (equivalent to an average time spacing of ~0.5 kyr) for grain size analyses. For magnetostratigraphic analysis, we also collected 251 parallel block samples that were oriented in the field with a compass. Subsequently, oriented block samples were cut into 2 cm × 2 cm × 2 cm cubic samples in the laboratory for thermal demagnetization to establish a magnetochronology. Remaining material from oriented block samples was used for mineral magnetic measurements. All magnetic and grain size analyses were conducted at the Institute of Earth Environment, Chinese Academy of Sciences, Xi’an.

Grain size analysis
Grain size distributions of red clay and loess-palaeosol samples were measured in the laboratory. Before the laser diffraction measurements, 0.2–0.3 g of each sample was pretreated with 30% H2O2 and 10% HCl to remove organic matter and carbonates, respectively. Treated samples were then put into 10 ml 10% (NaPO3)6 solution in an ultrasonic bath for ~10 min for dispersion. After sample pretreatment, grain size was analyzed in 101 size bins using a Malvern 3000 Laser Instrument with a Hydro LV wet dispersion unit from 0.02 μm to 2000 μm. Light sources include a red He–Ne laser at a 623 nm wavelength and a blue light emitting diode at 470 nm. Constants of 1.33 for the refractive index of water, 1.52 for the refractive index of solid phases, and 0.1 for the absorption index were used. We maintained a pump speed of ~2900 rpm in the Hydro LV pump. Each sample was measured three times. Grain size data were processed with the Malvern Mastersizer 3000 software (version 3.81), which transforms scattered light data to particle size information based on the Mie Scattering Theory.

Magnetic analyses
To identify the magnetic minerals that record the palaeomagnetic signal, we measured high-temperature-dependent magnetic susceptibility (χ–T), isothermal remanent magnetization (IRM) acquisition, magnetic hysteresis loops, and first-order reversal curve (FORC) diagrams for six red clay/loess-palaeosol samples from the Chongxin section. χ–T curves were measured in an argon atmosphere from room temperature to 700 °C and back to room temperature using a MFK1-FA magnetic susceptibility meter equipped with a CS-3 high-temperature furnace (AGICO, Brno, Czech Republic). IRM acquisition curves, magnetic hysteresis loops, and FORC diagrams were measured with a Princeton Measurements Corporation (Model 3900) vibrating sample magnetometer (VSM). Each IRM acquisition curve contains 200 data points that were measured at logarithmically spaced field steps to 1 T. Hysteresis loops were measured to ±1 T or ±1.5 T at 3 mT increments, with a 300 ms averaging time. First-order reversal curves (FORCs) were measured at 5 mT increments to ∼600 mT, with a 100 ms averaging time. FORC data were processed using the FORCinel package76, with a smoothing factor of 3.

All measured χ–T heating curves are characterized by a major χ decrease near 580 °C (Supplementary Fig. 2), which indicates that magnetite is the magnetically dominant phase in the sediment. Most samples indicate a steady χ increase below 300 °C during heating, which may be caused by gradual unblocking of very fine-grained ferrimagnetic (i.e., the superparamagnetic (SP) and fine-grained single-domain (SD)) particles, or stress release upon heating in such particles77–79. All samples have a subsequent χ decrease between ~300 and ~500 °C, which is consistent with conversion of ferrimagnetic maghemite to weakly magnetic hematite80–82. In agreement with a dominant low-coercivity magnetite/maghemite contribution, all IRM acquisition curves have a major increase below 300 mT (Supplementary Fig. 3), and most hysteresis loops close below ~300 mT (Supplementary Fig. 4). All FORC diagrams have closed contours with maximum contour density at coercive force (Bc) values <20 mT (Supplementary Fig. 5), which suggests a substantial presence of SD magnetite83,84. Outer contours are generally divergent along the Bu axis, which suggests the presence of small vortex state magnetic particles85. A general vertical FORC distribution immediately adjacent to the Bu axis in the lower half plane is indicative of SP particles83,85–88. The hematite expression in the rock magnetic results is not distinct because its presence is generally masked magnetically by the much stronger magnetization of relatively smaller amounts of magnetite25. However, substantial amounts of pigmentary red hematite particles are suggested by red hues in the loess-palaeosol and red clay sediments (Supplementary Fig. 1).

Palaeomagnetic analyses
To establish a clear palaeomagnetic polarity sequence for the Chongxin section, 251 oriented samples were subjected to detailed stepwise thermal demagnetization of the natural remanent magnetization (NRM), which was conducted using a TD-48 thermal demagnetizer. Samples were heated at 14–15 successive steps with 20–50 °C increments to a maximum temperature of 600–620 °C, at which point >90% of the initial NRM was demagnetized. After each demagnetization step, the remaining NRM was measured with a 2-G Enterprises Model 755-R cryogenic magnetometer housed in a magnetically shielded space. Demagnetization results were evaluated using orthogonal diagrams89; the principal component direction for each sample was computed using least-squares linear fitting90. Principal component analysis (PCA) was performed with PaleoMag software91. More samples (196) were demagnetized for the red clay sequence than the loess-palaeosol sequence (55 samples) because (1) the former (red clay) has lower sedimentation rates and contains several short-duration magnetic polarity zones, and (2) geomagnetic polarity reversals have been identified more precisely in the latter (loess-palaeosol) in previous studies20,21,23,24,92.

The NRM contains a secondary overprint that was removed by thermal demagnetization to 200–300 °C, followed by isolation of the characteristic remanent magnetization (ChRM) up to 600–620 °C (Supplementary Fig. 6). At least four consecutive demagnetization steps that decay linearly to the origin of orthogonal diagrams were used to determine ChRM directions above 250–350 °C, with a maximum angular deviation (MAD) ≤15° for line fits (not anchored to the origin)93. From 251 demagnetized samples, 212 yielded stable ChRM directions, from which virtual geomagnetic pole (VGP) latitudes were calculated to establish the magnetostratigraphic zonation. The Chongxin section records five normal and five reverse polarity zones (Fig. 2a and Supplementary Fig. 7b). Each zone is defined based on at least three consecutive VGP latitudes of identical polarity. Combining the well-established age of the iNHG for the boundary between loess-palaeosol and red clay on the CLP, we can readily correlate the Chongxin magnetostratigraphy to the geomagnetic polarity timescale (GPTS)39. The section spans from the youngest Gilbert reverse polarity chron to the Olduvai normal subchron, with a straightforward magnetostratigraphic correlation to the late Pliocene–early Pleistocene GPTS (Fig. 2a, b and Supplementary Fig. 7a, b). Our magnetostratigraphic assignment for the Chongxin section is consistent with those of other central and eastern CLP red clay/loess-palaeosol sections, such as at Jingchuan20,24, Xifeng23, Lingtai21, Baoji20,24, Lantian24, Shilou25, and Jiaxian26 sections (Supplementary Fig. 7).

Age model development
We combine magnetostratigraphy and astronomical tuning to establish an age model for the Chongxin section. Magnetostratigraphy was used to establish a first-order age model between 3.6 and 1.9 Ma for the Chongxin section based on linear interpolation between subsequent tie points using the nine identified geomagnetic polarity reversals, which were assigned ages from the GPTS39 (Supplementary Fig. 8a, b and Supplementary Table 1). Using this magnetochronology, the Chongxin MGS record has distinct ~100-kyr eccentricity and 41-kyr obliquity bands between 3.6 and 1.9 Ma (Supplementary Fig. 9a). Accordingly, we refined the magnetochronology by tuning the high-frequency 41-kyr MGS variations to orbital obliquity cycles in the astronomical solution94 with an automatic orbital tuning procedure43. Following previous orbital tunings of the CLP loess-palaeosol sequences with this procedure20,23, we repeatedly matched the 41-kyr cycles filtered from the Chongxin MGS record with the 8-kyr-lagged obliquity curve by manually adding time control points. An 8 kyr lag between the AWM and obliquity is used commonly in tunings of CLP loess-palaeosol grain size records20,23. Generally, larger MGS and filtered 41-kyr grain size peaks are associated with strong AWM and are correlated with obliquity minima. Ages for palaeomagnetic reversals are not kept fixed to optimize tuning results given uncertainties in palaeomagnetic boundaries and post-depositional NRM lock-in depth in aeolian sediments95,96, whereas tuned ages should not differ much (less than two obliquity cycles: <80 kyr) from those obtained from the palaeomagnetic record. After iteratively adding and/or adjusting age control points, the most likely astronomical timescale is shown in Supplementary Fig. 8c. The astronomical timescale is constrained by 31 tie points where MGS maxima facilitate tie point selection throughout the interval (Supplementary Fig. 8c and Supplementary Table 2). The filtered 41-kyr grain size component essentially correlates cycle-to-cycle with the calculated orbital obliquity in both coherency and amplitude modulation patterns in the astronomical timescale (Supplementary Fig. 8c). Palaeomagnetic reversal ages in the astronomical timescale are broadly consistent with their GPTS ages (Supplementary Table 1). Good phase matching is a function of tuning, while amplitude matches are independent of tuning, which supports the accuracy of our astronomical age model20,23. Overall, differences between the magnetochronology and our astronomical timescale obtained from obliquity tuning are not significant. The MGS record has a broadly similar orbital expression in our astronomical and magnetostratigraphic age models, with distinct co-occurring eccentricity and obliquity cycles (Supplementary Fig. 9). Orbital tuning refines the age model, corrects displaced obliquity cycles in the untuned magnetostratigraphic age model, and enhances the recorded orbital expression, but it does not change primary orbital periodicities. Therefore, the MGS record has higher obliquity power and lower non-orbital noise in our refined astronomical timescale than in the untuned magnetostratigraphic age model (Supplementary Fig. 9).

Spectral analyses
We calculated cross-wavelet and cross-power spectra between the global mean sea level and the seven-point running average of the Chongxin MGS record using the Acycle software97 to better evaluate late Pliocene to early Pleistocene orbital variability. To improve expression of orbital-scale variability in global mean sea level and the seven-point running average of the Chongxin MGS record, their <200 kyr variability was filtered. To improve expression of millennial variability in the Chongxin MGS record, <10 kyr variability was filtered. A high-pass filter in the Acycle software97 was used to obtain the <200 kyr and <10 kyr components. This high-pass filtering isolates higher frequency signals and excludes the influence of lower frequency signals. The <10 kyr filtered MGS record was also used for wavelet power spectral evolution and power spectrum analyses. Wavelet power spectral evolution was calculated using the Acycle software97. We used the 2π-Multi-Taper Method (MTM) to analyze power spectra with the function Spectral Analysis98.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of the manuscript “Orbital and millennial Asian monsoon variability across the Pliocene–\nPleistocene glacial intensification” by Ao et al. [NCOMMS-23-40160]\nGeneral comments:\nThe intensification of Northern Hemisphere glaciation across the Pliocene–Pleistocene transition marks\nthe final step in the overall cooling trend to a fully established bipolar icehouse. As a key component of\nthe global climate system, the Asian monsoon has been extensively investigated for both the\nPleistocene and the Pliocene; however, its response to such a milestone event in the Earth’s Cenozoic\nclimate history on different timescales remains unclear. In this study, the authors document a\ncomplete evolution of the Asian winter monsoon (AWM) variability on both orbital and millennial\nscales for the period from the late Pliocene to the early Pleistocene based on a continuous, centennial-\nresolved grain-size record from a new loess-paleosol/red clay section on the central Chinese Loess\nPlateau. They suggest that intensification of Northern Hemisphere glaciation had not altered orbital-\nscale AWM periodicities but could have enhanced both glacial and interglacial AWM intensities; while\nmillennial AWM intensity fluctuations persisted during both the warmer late Pliocene and the colder\nearly Pleistocene. The data and inferences presented in this study are of great significance and would\ncontribute to a deep understanding of the mechanism responsible for Asian monsoon variability on\nmillennial scale. I recommend acceptance of this manuscript for publication in Nature Communications\nafter minor revisions.\nSpecific comments:\n1. Lines 68–70: There is no logic in this argument. That is to say, lacking a hydrological signature that\nmarks ASM records cannot be the reason for more difficulties to reconstruct AWM variability. This is\nbecause AWM is distinct in nature from ASM as explained on lines 56–63.\n2. Lines 139–142: Note that the differences should be manifested in both the magnitude of glacial–\ninterglacial variations and the minima of low interglacial values.\n3. Lines 153–155: How young is younger and how old is older? Are the young / the old younger /\nolder than the period of the iNHG? It is better to say specially.\n4. Lines 201–208: It appears better to move these sentences to ‘Introduction’.\n5. Lines 240–293: It appears better to move this part to before ‘Millennial-scale AWM dynamics’.\nMinor comments:\n1. Line 30: Change ‘palaeosol’ (in the entire manuscript) to ‘paleosol’.\n2. Line 72: Change ‘central’ to ‘north-central’.\n3. Line 96: Change ‘accumulated’ to ‘is covered with’.\n4. Line 103: Change ‘variability’ to ‘variations’.\n5. Line 105: Delete ‘from this section’.\n6. Line 106: Delete ‘first-order’\n7. Line 113: Change ‘record’ to ‘sequence’.\n8. Line 119: Insert ‘and’ before ‘in the lower …’.\n9. Line 122: Change ‘variable sampling data’ to ‘different sampling intervals’.\n10. Line 124: Delete ‘magnetostratigraphy’.\n11. Line 128: Change ‘However’ to ‘although’ and merged this sentence into the one before it.\n12. Line 131: Change ‘records’ to ‘sequences’.\n13. Line 135: Delete ‘further’.\n14. Lines 143–144: Delete ‘that is underpinned by a detailed initial magnetostratigraphic age model’.\n15. Lines 152–153: Change ‘a greater aeolian dust transport capacity by’ to ‘drier conditions in the\ndust source regions as well as’.\n16. Lines 156–159: This sentence needs to be rewritten. It is not clear.\n17. Lines 161–162: Change ‘an observation that provides’ to ‘providing’.\n18. Line 164: Change ‘thick higher’ to ‘thicker’.\n19. Line 164: Insert ‘relatively thicker’ to before ‘yellow’.\n20. Lines 162–168: Both sentences sound repeated.\n21. Line 180: Delete ‘Visual inspection of’.\n22. Line 185: Delete ‘Furthermore’.\n23. Line 197: insert ‘strong’ between ‘not’ and ‘enough’.\n24. Lines 209–210: Change the passive voice to the active one.\n25. Line 212: insert ‘a’ between ‘such’ and ‘AWM’.\n26. Line 213: Change ‘now’ to ‘in this study’.\n27. Line 217: Delete ‘central Asian’.\n28. Line 243: Delete ‘both’.\n29. Line 246: Insert ‘and’ between ‘volume’ and ‘atmospheric’.\n30. Line 264: Delete ‘sheet’.\n31. Line 266: Change ‘Both ice volume and greenhouse gas concentrations’ to ‘These two factors’.\n32. Line 286: Change ‘sheet’ to ‘volume’ (two places).\n33. Line 292: Change ‘a pervasive and long-term’ to ‘a long-term, pervasive’.", "reviewer_2": "REVIEWERS' COMMENTS\n\nReviewer #2 (Remarks to the Author):\nThe authors have done a very thorough job revising their manuscript in line with all of the reviewers’\ncomments, and the revised paper is clearer, more accessible, and more impactful. I therefore\nrecommend it for publication in its present form, with a few small comments below.\nRevised Figures 1b and 1c are a great addition, and are much more informative with respect to dust\nsources. To make this figure even better, I suggest putting a black outline box on Map a showing the\narea in Map b, and in Map b denoting the area blown up in Map c!\nRevised Figure 2 is also much improved in my view, and my comments have been taken on board. The\nnew pCO2 figure is very nice and much more representative of actual proxy reconstructions. I suggest\nputting more intuitive axis titles for panels d and f showing the filtered records, instead of “fitting”\n(e.g., xx-xx kyr filtered MGS). Is the text that says “Red clay” below record c supposed to be there? If\nso, I wasn’t sure why. The inclusion of the 982 SST record is nice, please check that you used the\nupdated age model in Herbert 2016.\nI don’t think that “northern hemisphere” should be systematically capitalised. Same for late Pliocene\nand early Pleistocene, as they are not official sub-epochs.\nLine 176 “stronger inferred AWM winds”?\nThe cross-wavelet analysis between MGS and sea level is a nice addition to the paper.\nThe new Supp. Fig 11 comparing different iNHG monsoon records is really interesting and definitely\nopens the floor for discussion. Nice addition.\nSupp. Fig. 8 – I don’t quite understand why the grey dashed lines, which presumably show tie points\n(not specified in the caption), don’t match up with the red dots (“tuning points”)\nClara Bolton\n\nReviewer #3 (Remarks to the Author):\nThe authors have duly addressed the issues raised in my review. I have no further comments.", "reviewer_3": "Review of „Orbital and millennial Asian monsoon variability across the Pliocene–Pleistocene glacial\nintensification” by Ao et al.\nThe East Asian winter and summer monsoon (EAWM/EASM) affects the lives of millions of people, so\nunderstanding how the EAWM/EASM operated in the past is important in a warming climate that now\nmore and more resembles conditions at the end of the Pliocene in terms of both CO2 levels and\naverage temperatures. Ao and co-workers present a new, high resolution grain size record\n(representing EAWM) with a strong paleomagnetic age control from the central part of the Chinese\nLoess Plateau, spanning a period of 3.6-1.9 Ma (late Pliocene/early Pleistocene). They find that late\nPliocene–early Pleistocene EAWM is characterized by persistent 41-kyr and ~100-kyr cycles, and\nsuperimposed on orbital variability, millennial timescale EAWM fluctuations occurred much earlier than\npreviously thought. The data presented in the manuscript reflect the results of very significant field\nand laboratory work, with the authors performing paleomagnetic measurements of 251 samples and\nlaser diffraction analysis of 3487 loess/paleosol/red clay samples, which makes this study impressive\nand unique. The text of the manuscript is very well written, clear and easy to follow, and most of the\nauthors' conclusions are logical and scientifically sound. There are of course some issues that need to\nbe clarified in a minor revision, but in my opinion (with perhaps one exception) they are not of such\nimportance that they would fundamentally affect the main conclusions of the paper. My concerns are\nprimarily related to chapter “Orbital-scale AWM dynamics” (lines 273-279) and Figure 2, and I think\nthe text needs some minor amendments:\n1) From Figure 2c, it can be seen that interglacial intensities were similar before / after the iNHG or\nperhaps a little less intense after 2.7 Ma. As for the glacials, they clearly became more intense after 2.7 Ma. So, the statement that both glacials and interglacials became more intense (\"marked stepwise\nincrease in both glacial and interglacial AWM intensity\") is not evident in the MGS record, only that\nglacials became more intense and the amplitudes of fluctuations between glacials/interglacials. This\nmust be addressed during the revisions.\n2) Based on Fig. 2, the MGS record resembles the sea level curve, with larger amplitude fluctuations\nafter 2.7 Ma. This is in marked contrast to the CO2 record showing larger (sometimes >100 ppm)\nswings before the iNHG, while smaller scale fluctuations (~40 ppm) after 2.7 Ma. At the same time,\nCO2 concentrations fluctuated around a lower mean value (~260 ppm) after the iNHG indicating\nsignificant changes in the GHG boundary conditions (likewise ice volume), leading to a different\nclimate state. Is this what the authors are referring to?\nOther, less important questions also arise in relation to the interpretations or methodology:\n3) This is just a pedantic point, but the authors describe in several places (e.g. lines 68, 83) that the\nrecord they examine is continuous. Unfortunately, this is only an assumption. It would be difficult to\nimagine a dynamic eolian environment such as the CLP without shorter/longer (up to at least decades\nor a few hundred years) erosional periods over the last 3.6 million years. There is direct evidence for\nsedimentation gaps at the CLP margin based on luminescence dating results (see Stevens et al., 2018\nand references therein). Therefore, I suggest using the term “quasy-continuous” in the text.\n4) The authors state that “Mean grain sizes of bulk samples and extracted quartz particles have almost\nidentical variation for both red clay and loess-palaeosol sequences on the CLP”, by referring to Sun et\nal. (2010). In my view, this should have been tested using a subset of their samples to prove that this\nis true at the study site. For instance, bulk and quartz grain size variations were shown to be different\nin European loess (Újvári et al., 2016, 2017). I'm not stating that this holds true for the CLP, but it\nwould have been worth testing.\n5) Line 151-153, “coarser grain size-stronger winds relation”: I agree that stronger wind is one of the\nmost likely explanations, in addition to other factors that influence the transport capacity of the\nmedium, including, for example, the state of the eolian surface and temperature of the transport\nmedium. At lower temperatures an aeolian surface is more active, cohesive forces are weaker and the\nair is denser, so under colder conditions larger particles can be transported (see 3.1.1.4 subchapter in\nUjvari et al., 2016).\n6) Methods section, grain size analyses (lines 305-309): Provide information on instrument\nparameters (absorption and refractive index). Have you used the Mie theory (or Fraunhofer\napproximation) for GSD calculations?\n7) Methods section, age model (lines 377-379): Orbital tuning may have resulted in increased power\nat the 41 ka band, nicely seen in Fig S9. Could you comment on this?\n8) Methods section, 8 ka lag (lines 381-382): This lag is debated, others argue for a shorter lag (~5\nka) based on absolute ages (Stevens et al., 2018). However, the ~ 5 ka lag was proposed for the\nresponse of EASM to insolation forcing.\n9) Methods, age model (lines 386): What was the accepted tolerance of paleomagnetic boundary\nshifts in kyrs?\nTechnical corrections, typos\nline 103: “unprecedent” should be replaced by “unprecedented”\nline 137: write “AMW indicator”\nline 192: consider writing “2.66 Ma” instead of “2.7 Ma”\nline 245: “CO2 concentration increase”, do you mean “decrease”?\nline 246: write “ice volume and atmospheric CO2”\nlines 259-260: consider using “different control” instead of “larger control”\nline 374: write “which were assigned”\nline 641: replace “Loss” by “Loess”\nFigure 1: I suggest changing the label of Fig. 1b to make sure these are readable. What does the\nhatching mean?\nReferences\nStevens, T., Buylaert, JP., Thiel, C. et al. (2018). Ice-volume-forced erosion of the Chinese Loess\nPlateau global Quaternary stratotype site. Nature Communications 9, 983.\nSun, Y.B., An, Z.S., Clemens, S.C., Bloemendal, J., Vandenberghe, J. (2010). Seven million years of\nwind and precipitation variability on the Chinese Loess Plateau. Earth and Planetary Science Letters\n297, 525–535.\nÚjvári, G., Kok, J.F., Varga, G., Kovács, J. (2016). The physics of wind-blown loess: implications for\ngrain size proxy interpretations in Quaternary paleoclimate studies. Earth-Science Reviews 154, 247–\n278.\nÚjvári, G., Stevens, T., Molnár, M., Demény, A., Lambert, F., Varga, G., et al. (2017). Coupled European\nand Greenland last glacial dust activity driven by North Atlantic climate. Proceedings of the National\nAcademy of Sciences of the United States of America, 114, 10622–10631."}, "author_response": "We thank the reviewers and the editor for evaluating our manuscript. Please find below our\npoint-by-point responses in blue. Our revisions in the main text are also marked blue.\nReviewer #1\nGeneral comments:\nThe intensification of Northern Hemisphere glaciation across the Pliocene–Pleistocene transition\nmarks the final step in the overall cooling trend to a fully established bipolar icehouse. As a key\ncomponent of the global climate system, the Asian monsoon has been extensively investigated for both\nthe Pleistocene and the Pliocene; however, its response to such a milestone event in the Earth’s\nCenozoic climate history on different timescales remains unclear. In this study, the authors document\na complete evolution of the Asian winter monsoon (AWM) variability on both orbital and millennial\nscales for the period from the late Pliocene to the early Pleistocene based on a continuous, centennial-\nresolved grain-size record from a new loess-paleosol/red clay section on the central Chinese Loess\nPlateau. They suggest that intensification of Northern Hemisphere glaciation had not altered orbital-\nscale AWM periodicities but could have enhanced both glacial and interglacial AWM intensities; while\nmillennial AWM intensity fluctuations persisted during both the warmer late Pliocene and the colder\nearly Pleistocene. The data and inferences presented in this study are of great significance and would\ncontribute to a deep understanding of the mechanism responsible for Asian monsoon variability on\nmillennial scale. I recommend acceptance of this manuscript for publication in Nature\nCommunications after minor revisions.\nResponse: We thank Reviewer #1 for positive evaluation and helpful comments.\nSpecific comment #1\nLines 68–70: There is no logic in this argument. That is to say, lacking a hydrological signature that\nmarks ASM records cannot be the reason for more difficulties to reconstruct AWM variability. This is\nbecause AWM is distinct in nature from ASM as explained on lines 56–63.\nResponse: Thank you. Indeed, in retrospect the argument did not make that much sense. We have\nremoved this argument.\nSpecific comment #2\nLines 139–142: Note that the differences should be manifested in both the magnitude of glacial–\ninterglacial variations and the minima of low interglacial values.\nResponse: We have included this note in the revised manuscript (lines 156-157).\nSpecific comment #3\nLines 153–155: How young is younger and how old is older? Are the young / the old younger / older\nthan the period of the iNHG? It is better to say specially.\nResponse: These terms are now rephased more specifically. To avoid repetition, the former sentence\non lines 153–155 has been deleted.\nSpecific comment #4\nLines 201–208: It appears better to move these sentences to ‘Introduction’.\nResponse: These sentences have been revised and moved to the “Introduction” as suggested (lines 62-\n68).\nLines 240–293: It appears better to move this part to before ‘Millennial-scale AWM dynamics’.\nResponse: We have implemented this change.\nMinor comment #1\n1. Line 30: Change ‘palaeosol’ (in the entire manuscript) to ‘paleosol’.\nResponse: “Palaeosol” and “paleosol” represent British and American English, respectively. Nature\npublications use British English, so we have not changed “palaeosol” to “paleosol” in the revised\nmanuscript.\nMinor comment #2–7\n2. Line 72: Change ‘central’ to ‘north-central’.\n3. Line 96: Change ‘accumulated’ to ‘is covered with’.\n4. Line 103: Change ‘variability’ to ‘variations’.\n5. Line 105: Delete ‘from this section’.\n6. Line 106: Delete ‘first-order’\n7. Line 113: Change ‘record’ to ‘sequence’.\nResponse: We have incorporated these suggested changes.\nMinor comment #8\n8. Line 119: Insert ‘and’ before ‘in the lower …’.\nResponse: To clarify this sentence, we have added roman numerals to the list of positions where the\nOlduvai subchron is found (lines 128-131).\nMinor comment #9–10\n9. Line 122: Change ‘variable sampling data’ to ‘different sampling intervals’.\n10. Line 124: Delete ‘magnetostratigraphy’.\nResponse: We have incorporated these suggested changes.\nMinor comment #11\n11. Line 128: Change ‘However’ to ‘although’ and merged this sentence into the one before it.\nResponse: We have rephrased related sentences in the revised manuscript (lines 137-140).\nMinor comment #12–14\n12. Line 131: Change ‘records’ to ‘sequences’.\n13. Line 135: Delete ‘further’.\n14. Lines 143–144: Delete ‘that is underpinned by a detailed initial magnetostratigraphic age model’.\nResponse: We have included these changes.\nMinor comment #15\n15. Lines 152–153: Change ‘a greater aeolian dust transport capacity by’ to ‘drier conditions in the\ndust source regions as well as’.\nResponse: We have changed it to “increased dust transport capacity by stronger AWM winds from\ndrier source regions to the north and west of the CLP under colder conditions across the iNHG (Ding\net al., 1995; Hao et al., 2012; Sun et al., 2010; Ujvári et al., 2016; Xiao et al., 1995)”.\n16. Lines 156–159: This sentence needs to be rewritten. It is not clear.\n17. Lines 161–162: Change ‘an observation that provides’ to ‘providing’.\nResponse: We have clarified these sentences.\nMinor comment #18–20\n18. Line 164: Change ‘thick higher’ to ‘thicker’.\n19. Line 164: Insert ‘relatively thicker’ to before ‘yellow’.\n20. Lines 162–168: Both sentences sound repeated.\nResponse: To avoid repetition, we have removed this sentence.\nMinor comment #21–33\n21. Line 180: Delete ‘Visual inspection of’.\n22. Line 185: Delete ‘Furthermore’.\n23. Line 197: insert ‘strong’ between ‘not’ and ‘enough’.\n24. Lines 209–210: Change the passive voice to the active one.\n25. Line 212: insert ‘a’ between ‘such’ and ‘AWM’.\n26. Line 213: Change ‘now’ to ‘in this study’.\n27. Line 217: Delete ‘central Asian’.\n28. Line 243: Delete ‘both’.\n29. Line 246: Insert ‘and’ between ‘volume’ and ‘atmospheric’.\n30. Line 264: Delete ‘sheet’.\n31. Line 266: Change ‘Both ice volume and greenhouse gas concentrations’ to ‘These two factors’.\n32. Line 286: Change ‘sheet’ to ‘volume’ (two places).\n33. Line 292: Change ‘a pervasive and long-term’ to ‘a long-term, pervasive’.\nResponse: We have adopted these helpful edits.\nReferences cited in our response above\nDing, Z.L., Liu, T.S., Rutter, N.W., Yu, Z.W., Guo, Z.T. and Zhu, R.X., 1995. Ice-volume forcing of\nEast Asian winter monsoon variations in the past 800,000 Years. Quaternary Research, 44(2):\n149–159.\nHao, Q.Z., Wang, L., Oldfield, F., Peng, S.Z., Qin, L., Song, Y., Xu, B., Qiao, Y.S., Bloemendal, J. and\nGuo, Z.T., 2012. Delayed build-up of Arctic ice sheets during 400,000-year minima in\ninsolation variability. Nature, 490(7420): 393–396.\nSun, Y.B., An, Z.S., Clemens, S.C., Bloemendal, J. and Vandenberghe, J., 2010. Seven million years\nof wind and precipitation variability on the Chinese Loess Plateau. Earth and Planetary Science\nLetters, 297(3-4): 525–535.\nUjvári, G., Kok, J.F., Varga, G. and Kovács, J., 2016. The physics of wind-blown loess: Implications\nfor grain size proxy interpretations in Quaternary paleoclimate studies. Earth-Science Reviews,\n154: 247–278.\nXiao, J.L., Porter, S.C., An, Z.S., Kumai, H. and Yoshikawa, S., 1995. Grain size of quartz as an\nindicator of winter monsoon strength on the loess plateau of central China during the last\n130000 yr. Quaternary Research, 43: 22–29.\nGeneral comments:\nThis manuscript by Ao et al presents a new, contiCO2nuous, extremely high-resolution dataset of grain\nsize from a sedimentary section in the central Chinese Loess Plateau, interpreted to represent changes\nin dust delivery to the area by Asian winter monsoon winds. The record is of very high quality, allowing\nexcellent paleomagnetic age control and orbital tuning. High-resolution, continuous records such as\nthis one that span the intensification of northern hemisphere glaciation are precious in terms of our\nunderstanding of monsoon dynamics over periods of evolving global climate boundary conditions. The\npaper is very well written, well referenced, and clearly structured. The figures and supplementary\nfigures are very nice (although I have a few suggestions for additions). I would like to state that I am\nnot an expert on palaeomagnetism or loess records, so my review focuses on the more general monsoon\naspects and the iNHG context. The new grain size record is clearly explained and interpreted; however,\nI think the paper would benefit from additional context and comparison with other summer/winter\nsouth Asian/east Asian monsoon records that span iNHG, and also a more thorough assessment of\npCO changes and their potential role on monsoon evolution. Below are some specific comments and\n2\nthoughts that I hope will be constructive to the authors when revising the paper.\nResponse: We thank Reviewer #2 for their helpful feedback and comments on our manuscript.\nFollowing these suggestions, we include additional context and comparison with other summer/winter\nsouth Asian/east Asian monsoon records spanning the iNHG (lines 255-263; Supplementary Note 1),\nwith a more thorough assessment of pCO changes and their potential role on monsoon evolution (Fig.\n2\n2h and lines 213-243).\nSpecific comment #1\nLine 34: in phase (rather than in pace)?\nResponse: It is not accurate to use “in phase” here because phases of orbital-scale oscillations of Asian\nwinter monsoon, ice sheet, and atmospheric CO concentration are not always identical, with slight\n2\nlags and leads. We change “in pace with” to “in response to”, to clarify the sentence.\nSpecific comment #2\nLine 43: ice-sheet size or volume.\nResponse: We checked this sentence: “Middle and Late Pleistocene” is more reasonable than “Middle\nand Late Pleistocene ice-sheet size or volume” (lines 45 in the revised manuscript).\nSpecific comment #3\nLines 44-48: It would make sense to specify/restrict these sentences to the mid-Pliocene warm period,\nif you want to talk about higher than pre-industrial pCO and temperatures.\nSpecific comment #4\nLine 52: long-term rather than overall?\nResponse: We adopted this change.\nSpecific comment #5\nLine 80: I think it would be great to include somewhere (ideally in the main text) a plot of the new\nrecord with other AWM/ASM records that span iNHG. This will help highlight the novelty and added\n4\nvalue of the new record, as well as being useful to refer to in the discussion.\nResponse: We now compare other AWM/ASM records with our grain size record spanning the iNHG\nin Supplementary Fig. 11, with related discussion in the main text (lines 255-263) and Supplementary\nNote 1. Our study focuses on the AWM, so related discussion of ASM variability across the iNHG is\nincluded in Supplementary Note 1 to avoid distraction. However, the related other AWM records are\ndiscussed in the main text (lines 255-263).\nSpecific comment #6\nLine 86: “we assess […] through detailed land-sea comparison” – although this would be great, it isn’t\nreally the case in the current version of the manuscript. Marine monsoon records over iNHG are not\ndiscussed.\nResponse: We rephrase these sentences and removed “through detailed land-sea comparison”.\nSpecific comment #7\nLine 89: rephrase “in contrast to previous thought”.\nResponse: We have deleted this sentence and rephrased this issue (lines 93-97).\nSpecific comment #8\nSentence line 139: add reference to a figure?\nResponse: We now include a figure reference (line 155-156).\nSpecific comment #9\nSentence line 142-144: Add a link to the previous sentence… we therefore utilize; or As a result, we\nutilize; re-stating the age model info seems unnecessary here – this has already been described by this\npoint.\nResponse: We have modified this sentence as suggested.\nSpecific comment #10\nLine 103: unprecedented.\nResponse: Done.\nSpecific comment #11\nIn the introduction, it would be helpful to the reader to explicitly talk about the aeolian dust sources\n(i.e., where are they? Include the source area on the map in Fig. 1?), and explain why we think the\ntransition in sedimentology from red clay to loess/paleosol layers occurs around 2.6 Ma (i.e., the state-\nof the-art with respect to this). Also, what drives the switches between loess and paleosol layers post-\n2.6 Ma? Because we only see the sedimentary log on the depth scale, it’s hard to see whether these\nalternations are linked to G-IG cycles or not. All of this is perhaps very obvious to people who work\non loess monsoon records all the time, but less so to people working for example in the marine realm\nor on paleobotanical records, so it would improve the accessibility and reach of the paper to explicitly\nmention this.\nResponse: We now discuss aeolian dust sources in the revised “Introduction” (lines 83-84). Source\nareas are also included in Fig. 1b. In the revised “Introduction”, we explain that magnetostratigraphic\nresults from the Chinese Loess Plateau suggest a sedimentological transition from red clay to loess-\npalaeosol layers at ~2.6 Ma (lines 80-83). We explain what drives alternations between loess and\n5\npalaeosol layers after 2.6 Ma (lines 104-107). We further show the Chongxin mean grain size record\nplotted against depth in Fig. 2a. We further revise Figure 2 by including L- and S-numbers in Fig. 2c\non the age scale to refer to alternating loess and palaeosol layers after 2.6 Ma, respectively.\nSpecific comment #12\nFig. 1b: the red text on the map is difficult to read, I suggesting using another colour. Could dust source\nregion be shown on the map?\nResponse: We revised Fig. 1, with inclusion of dust source regions on a topographic map (Fig. 1b).\nSpecific comment #13\nFig 2: I would consider using a more than three-point running average to smooth the data, so it’s more\ncomparable to the “global climate” curves plotted below. Also, see comments below about CO2 and\nbenthic d18O. Consider including the sedimentological info also on the age scale (like the paleomag).\nResponse: We now use a seven-point average to smooth the data in the revised Fig. 2c.\nSpecific comment #14\nFig. 3: consider adding horizontal lines for the main orbital periods on the wavelets. See comments\nbelow about CO , cross-wavelets, etc.\nSpecific comment #15\nLine 147 and more broadly; I would be careful referring to this curve as “the” reference atmospheric\npCO record. The pCO curve of Berends et al 2021 is derived from an inverse forward modelling\n2 2\napproach that deconvolutes the ice volume and deep-sea temperature signals in benthic foraminiferal\nδ18O records. In the authors’ words, this approach “is a tool that determines how modelled CO should\n2\nhave evolved over time in order to affect the global climate in such a way that the observed benthic\nδ18O record is reproduced”. Whilst I appreciate that it is simpler to compare your record to and perform\nspectral analyses on a high-resolution, continuous synthetic pCO curve, it seems important that you\n2\nalso compare your AWM record with data-based paleo-pCO reconstructions, such as those compiled\n2\n& homogenised by Sosdian et al., 2018 and Rae et al 2021 (possibly also including newer records for\nthe Pliocene such as Guillermic et al 2022); see example figure below. I would strongly suggest\nincluding these pCO data on Figure 2. The uncertainly on the modelled CO curve (c.f. Fig 4 of\n2 2\nBerends et al 2021), which is particularly high for the warm mid-Pliocene, should also be included in\nyour figure. As is clear from Fig. 6 of Berends et al 2021, the different modelled CO curves often\n2\nshow quite different trends from each other over iNHG which are not necessarily in agreement with\nproxy data, so it needs to be clear in your text and figures that the Berends CO curve is a proposed\n2\nscenario and NOT the record of past pCO variations, as it is currently treated. For example,\n2\nsentences/comments such as those lines 34, 147-149, 170, 241, 264, 279, etc need to be more nuanced\nwith respect to this.\nArguably, rather than carrying out spectral analyses on this modelled CO2 scenario derived from\nbenthic d18O, it might be more direct and make more sense to compare the spectral characteristics of\nyour grain size record with the (more robust) benthic d18O compilation, taken to represent “global\nclimate” variations. In this context, given the high-resolution age model presented for your new record,\nI wonder if it might be a good idea to carry out cross-spectral analyses (or cross-wavelets) between,\nfor example, mean grain size and benthic d18O or SL (rather than singular spectral analyses/wavelets\nof each record). This would allow you to assess changing coherence and phase relationships over time.\nResponse: We have changed the spectral analyses of Chongxin mean grain size, global average sea\nlevel, and atmospheric CO concentration to cross-wavelet spectral analysis of Chongxin mean grain\n2\nsize and global average sea level as suggested (lines 178-184 and Fig. 3).\nSpecific comment #17\nGiven the discussion line 222 onwards, it also might be nice to also compare the record to NH high-\nlatitude sea surface temperature for example (e.g. the Herbert et al. high-latitude NH SST stack\n(2010,2016), or the Lawrence et al 2009 ODP Site 982 SST record, or a different one I am not aware\nof), and also plot this in Fig. 2.\nResponse: We now include the North Atlantic Ocean SST record (Lawrence et al., 2009) in Fig. 2.\nSpecific comment #18\nLine 153 – it is not clear what you are referring to as “the younger loess-paleosol sequence”. It looks\nto me like the increase in variability in the detrended record shown starts gradually around 2.8-2.9 Ma;\nwhereas the switch to higher “mean state” mean grain size occurs almost exactly at the Gauss-\n(to Fig. 2) a detrended record that shows orbital-scale (not just millennial) variability to support this\nstatement; and also, the global benthic d18O compilation record to illustrate the switch to larger-\namplitude G-IG cycles that you describe. Also, the change in baseline IG mean grain size after 2.6 Ma\nwarrants a mention.\nResponse: We changed “the younger loess-paleosol sequence” to be more specific: “the Pleistocene\nloess-paleosol sequence”. We also include detrended and orbitally filtered records of the Chongxin\nmean grain size and global sea level records, which both show orbital-scale variability in the revised\nFig. 2. We further modified related discussion, as suggested, including discussion of grain size shifts\nat 2.7 Ma and 2.6 Ma, and changes in baseline G-IG mean grain size after 2.6 Ma (lines 168-178).\nSpecific comment #19\nLine 157: To what extent is the switch in mean grain size at ~2.6 Ma mechanistically linked to the\nswitch in sedimentology (clay to loess-paleosol)? Are the two variables necessarily linked (i.e., are\nyou saying that the switch in sedimentology is a direct and complete result of the change in winter\nmonsoon wind strength and increased dust deposition?)? As I mentioned for the introduction, this may\nseem obvious to CLP specialists but is not clear to me. Is the lithological change as abrupt as it appears\non-abrupt as it appears\non the log or is it more gradual, like the grain size change?\nResponse: We now further clarify the link between grain size and sedimentological shifts across the\niNHG (lines 185-194).\nSpecific comment #20\nLine 159: “and ASM weakening” – needs an explanation, not intuitive\nResponse: We change “ASM weakening” to “ASM weakening as indicated by distinct decreases in\nmagnetic susceptibility (Sun et al., 2006), rates of chemical weathering (An et al., 2001; Wang et al.,\n2022), and soil carbonate δ13C values (An et al., 2001)” (lines 191-192).\nSpecific comment #21\nLine 164: “A thick higher”… is this a mistake?\nResponse: We remove this sentence to avoid repetition.\nSpecific comment #22\nLine 173 – this is not clear on the wavelet figures, perhaps add horizontal lines denoting the orbital\nperiods you discuss.\nResponse: We include horizontal lines to denote our discussed orbital periodicities (Fig. 3).\nSpecific comment #23\nLine 180-181: this isn’t really clear from the raw data figure (that the 100-kyr cycles are obliquity\nbundles) – maybe illustrate this somehow with a filter or annotation?\nResponse: We remove this statement.\nSpecific comment #24\nLine 185: shouldn’t this uncertainty in grain-size measurements be included on figure 2 (raw and\nfiltered data)?\nResponse: We include grain-size measurement uncertainties in Supplementary Fig. 10.\nOne thing that I think would add to the paper would be a final figure that compares the new record\nwith other monsoon records spanning iNHG. What to include is of course up to the authors (perhaps\nsome of the ones mentioned in the discussion?), but I think it would help put the new record into a\nregional (land & ocean) context, in terms of how it advances the state of the art on monsoon evolution.\nResponse: See response to specific comment #5.\nSpecific comment #26\nLine 243; add reference to new figure with paleo-pCO data.\nSpecific comment #27\nLine 246: missing word?\nResponse: We have removed this statement from the revised manuscript.\nSpecific comment #28\nLine 286: can you really say this with certainty? It seems quite hard to decouple to influence of global\nclimate cooling and NH ice sheet growth from concurrent pCO2 decreases.\nResponse: In our revision, we rephrased and toned down this argument (lines 222-254).\nReferences cited in our response above\nAn, Z.S., Kutzbach, J.E., Prell, W.L. and Porter, S.C., 2001. Evolution of Asian monsoons and phased\nuplift of the Himalaya-Tibetan plateau since Late Miocene times. Nature, 411: 62–66.\nLawrence, K.T., Herbert, T.D., Brown, C.M., Raymo, M.E. and Haywood, A.M., 2009. High-\namplitude variations in North Atlantic sea surface temperature during the early Pliocene warm\nperiod. Paleoceanography, 24(2): PA2218.\nSun, Y.B., Clemens, S.C., An, Z.S. and Yu, Z.W., 2006. Astronomical timescale and palaeoclimatic\nimplication of stacked 3.6-Myr monsoon records from the Chinese Loess Plateau. Quaternary\nScience Reviews, 25(1-2): 33–48.\nWang, K.X., Lu, H.Y., Lei, F., Lyu, H.Z., Wang, H.L. and Wang, Y.C., 2022. East Asian monsoon\nprecipitation decrease during Plio-Pleistocene transition revealed by changes in the chemical\nweathering intensity of Red Clay and loess-paleosol. Palaeogeography Palaeoclimatology\nPalaeoecology, 601: 111080.\nOverview:\nThe East Asian winter and summer monsoon (EAWM/EASM) affects the lives of millions of people,\nso understanding how the EAWM/EASM operated in the past is important in a warming climate that\nnow more and more resembles conditions at the end of the Pliocene in terms of both CO2 levels and\naverage temperatures. Ao and co-workers present a new, high resolution grain size record\n(representing EAWM) with a strong paleomagnetic age control from the central part of the Chinese\nLoess Plateau, spanning a period of 3.6-1.9 Ma (late Pliocene/early Pleistocene). They find that late\nPliocene–early Pleistocene EAWM is characterized by persistent 41-kyr and ~100-kyr cycles, and\nsuperimposed on orbital variability, millennial timescale EAWM fluctuations occurred much earlier than\npreviously thought. The data presented in the manuscript reflect the results of very significant field\nand laboratory work, with the authors performing paleomagnetic measurements of 251 samples and\nlaser diffraction analysis of 3487 loess/paleosol/red clay samples, which makes this study impressive\nand unique. The text of the manuscript is very well written, clear and easy to follow, and most of the\nauthors' conclusions are logical and scientifically sound. There are of course some issues that need to\nbe clarified in a minor revision, but in my opinion (with perhaps one exception) they are not of such\nimportance that they would fundamentally affect the main conclusions of the paper. My concerns are\nprimarily related to chapter “Orbital-scale AWM dynamics” (lines 273-279) and Figure 2, and I think\nthe text needs some minor amendments:\nResponse: We thank Reviewer #3 for positive feedback and comments about our manuscript. We have\nrevised the manuscript as suggested.\nSpecific comment #1\n1) From Figure 2c, it can be seen that interglacial intensities were similar before/after the iNHG or\nperhaps a little less intense after 2.7 Ma. As for the glacials, they clearly became more intense after 2.7\nMa. So, the statement that both glacials and interglacials became more intense (\"marked stepwise\nincrease in both glacial and interglacial AWM intensity\") is not evident in the MGS record, only that\nglacials became more intense and the amplitudes of fluctuations between glacials/interglacials. This\nmust be addressed during the revisions.\nResponse: We agree that glacial MGS changes across the iNHG are substantially larger than\ninterglacial MGS changes, similar to the sea level record (Fig. 2). We have changed the statement, as\nsuggested, to “glacial AWM became more intense after the iNHG”.\nSpecific comment #2\n2) Based on Fig. 2, the MGS record resembles the sea level curve, with larger amplitude fluctuations\nafter 2.7 Ma. This is in marked contrast to the CO record showing larger (sometimes >100 ppm)\n2\nswings before the iNHG, while smaller scale fluctuations (~40 ppm) after 2.7 Ma. At the same time,\nCO2 concentrations fluctuated around a lower mean value (~260 ppm) after the iNHG indicating\nsignificant changes in the GHG boundary conditions (likewise ice volume), leading to a different\nclimate state. Is this what the authors are referring to?\nResponse: We now include the derived CO curve from high-resolution benthic δ18O records using\n2\nthe inverse forward modelling approach (Berends et al., 2021), as well as data-based CO\n2\nreconstructions (Bartoli et al., 2011; de la Vega et al., 2020; Dyez et al., 2018; Guillermic et al., 2022;\nMartínez-Botí et al., 2015; Sosdian et al., 2018) in the revised Fig. 2. Larger-amplitude orbital\noscillations before 2.7 Ma in the CO record of Berends et al. (2021) derived from benthic δ18O records\n2\n10\nis not observed in the benthic δ18O and global mean sea level records, nor in the data-based CO\n2\nreconstructions, so it may be a modelling artefact. Therefore, we now only compare the Chongxin\nMGS record with global mean sea level record and not with CO variability on the orbitally oscillating\n2\namplitudes. However, we do use sea level and both proxy- and model-based CO reconstructions to\n2\nrefer to different climate-cryosphere boundary conditions before and after the iNHG, because it has\nbeen well documented that Northern Hemisphere glaciation was enhanced when atmospheric CO\n2\nconcentrations decreased across the iNHG. We find that this climate-cryosphere boundary condition\nchange did not alter orbital-scale AWM periodicities but substantially enhanced glacial AWM intensity\nacross the iNHG.\nSpecific comment #3\nOther, less important questions also arise in relation to the interpretations or methodology: 3) This is\njust a pedantic point, but the authors describe in several places (e.g. lines 68, 83) that the record they\nexamine is continuous. Unfortunately, this is only an assumption. It would be difficult to imagine a\ndynamic eolian environment such as the CLP without shorter/longer (up to at least decades or a few\nhundred years) erosional periods over the last 3.6 million years. There is direct evidence for\nsedimentation gaps at the CLP margin based on luminescence dating results (see Stevens et al., 2018\nand references therein). Therefore, I suggest using the term “quasy-continuous” in the text.\nResponse: We have removed “continuous” from or changed it to “quasi-continuous”, with a mention\nof potential erosional hiatuses in sections on the northern desert margin of the CLP (Stevens et al.,\n2018) (lines 101-104).\nSpecific comment #4\n4) The authors state that “Mean grain sizes of bulk samples and extracted quartz particles have almost\nidentical variation for both red clay and loess-palaeosol sequences on the CLP”, by referring to Sun et\nal. (2010). In my view, this should have been tested using a subset of their samples to prove that this\nis true at the study site. For instance, bulk and quartz grain size variations were shown to be different\nin European loess (Újvári et al., 2016, 2017). I'm not stating that this holds true for the CLP, but it\nwould have been worth testing.\nResponse: Mean grain size variations of quartz particles and bulk samples from different sections\nacross the CLP are largely comparable (e.g., Ding et al., 2002; Sun et al., 2006, 2010), such as the\nXifeng and Lingtai sections in Fig. 1 below. This is different from European loess. Quart particle\nextraction from thousands of bulk samples is labour intensive work that is not feasible for the Chongxin\nsection, so we use bulk sample grain sizes to infer AWM variability.\nXifeng and Lingtai loess-paleosol/red clay sections (Sun et al., 2006).\nSpecific comment #5\n5) Line 151-153, “coarser grain size-stronger winds relation”: I agree that stronger wind is one of the\nmost likely explanations, in addition to other factors that influence the transport capacity of the medium,\nincluding, for example, the state of the eolian surface and temperature of the transport medium. At\nlower temperatures an aeolian surface is more active, cohesive forces are weaker and the air is denser,\nso under colder conditions larger particles can be transported (see 3.1.1.4 subchapter in Ujvari et al.,\n2016).\nResponse: We have changed the wording to “indicative of increased dust transport capacity by stronger\nAWM winds from drier source regions located to the north and west to the CLP under colder conditions\nacross the iNHG (Ding et al., 1995; Hao et al., 2012; Sun et al., 2010; Ujvári et al., 2016; Xiao et al.,\n1995)” (lines 170-172).\nSpecific comment #6\n6) Methods section, grain size analyses (lines 305-309): Provide information on instrument\nparameters (absorption and refractive index). Have you used the Mie theory (or Fraunhofer\napproximation) for GSD calculations?\nResponse: In the revised Methods section, we now include details of grain size analyses, including\nrelated instrument parameters and a mention of the Mie theory used for GSD calculations (lines 321-\n332).\nSpecific comment #7\n12\n7) Methods section, age model (lines 377-379): Orbital tuning may have resulted in increased power\nat the 41 ka band, nicely seen in Fig S9. Could you comment on this?\nResponse: We comment on this in the revised Method section (lines 425-429).\nSpecific comment #8\n8) Methods section, 8 ka lag (lines 381-382): This lag is debated, others argue for a shorter lag (~5 ka)\nbased on absolute ages (Stevens et al., 2018). However, the ~ 5 ka lag was proposed for the response\nof EASM to insolation forcing.\nResponse: We agree that the lag between orbital forcing and CLP grain size (AWM) remains debated,\nparticularly before 1 Ma. Following previous orbital tunings of CLP loess-palaeosol grain size records\nwith the same procedure (Ding et al., 2002; Sun et al., 2006), we also adopt the 8-kyr-lagged obliquity\ncurve, which refers to the SPECMAP-defined lag for obliquity (Imbrie et al., 1984), for tuning, like\nprevious studies. However, obliquity tuning using 8-kyr- or 5-kyr-lagged obliquity results in only very\nslight differences (~3 kyr) in the related astronomical age models, which does not influence our\ninterpretations. Nevertheless, given that detailed luminescence dating results suggest that EASM lags\nprecession-paced summer insolation by ~5 kyr (Stevens et al., 2018), which means that the EASM lags\nshort-duration precession by ~5 kyr, and likely thus longer-duration obliquity by >5 kyr, the commonly\nadopted 8 kyr lag between Asian monsoon and obliquity appears to enable more reasonable tuning\nresults.\nSpecific comment #9\n9) Methods, age model (lines 386): What was the accepted tolerance of paleomagnetic boundary shifts\nin kyrs?\nResponse: We now specify that our tolerance of paleomagnetic boundary shifts caused by tuning is\nless than two obliquity cycles (<80 kyr) (lines 412-413). However, our orbital tuning generally shifted\nthe ages of major palaeomagnetic reversal boundaries (polarity chrons or subchrons) by <30 kyr\n(Supplementary Table 1). The age of the short-duration Réunion geomagnetic excursion is ~60 kyr\nyounger in our astronomical timescale than in the 2020 GPTS (Gradstein et al., 2020). This slightly\nlarger shift of the Réunion geomagnetic excursion may be due to increased age uncertainties of\ngeomagnetic excursions (Laj and Channell, 2007; Roberts, 2008) and relatively more variable\npositions and post-depositional NRM lock-in depths in CLP aeolian sediments (Jin et al., 2019; Pan et\nal., 2021).\nSpecific comment #10\nTechnical corrections, typos\nline 103: “unprecedent” should be replaced by “unprecedented”\nline 137: write “AMW indicator”\nline 192: consider writing “2.66 Ma” instead of “2.7 Ma”\nline 245: “CO2 concentration increase”, do you mean “decrease”?\nline 246: write “ice volume and atmospheric CO2”\nline 374: write “which were assigned”\nline 641: replace “Loss” by “Loess”\nResponse: We have included these helpful edits in the new version of the text.\nSpecific comment #11\n13\nlines 259-260: consider using “different control” instead of “larger control”\nResponse: On rereading this sentence, we found that this argument did not make that much sense, so\nwe have deleted it.\nSpecific comment #12\nFigure 1: I suggest changing the label of Fig. 1b to make sure these are readable. What does the\nhatching mean?\nResponse: We include a revised Fig. 1, which no longer contains hatching.\nReferences cited in our response above\nBartoli, G., Hönisch, B. and Zeebe, R.E., 2011. Atmospheric CO decline during the Pliocene\n2\nintensification of Northern Hemisphere glaciations. Paleoceanography, 26(4): PA4213.\nBerends, C.J., de Boer, B. and van de Wal, R.S.W., 2021. Reconstructing the evolution of ice sheets,\nsea level, and atmospheric CO during the past 3.6 million years. Climate of the Past, 17(1):\n2\n361–377.\nde la Vega, E., Chalk, T.B., Wilson, P.A., Bysani, R.P. and Foster, G.L., 2020. Atmospheric CO during\n2\nthe Mid-Piacenzian Warm Period and the M2 glaciation. Scientific Reports, 10(1): 11002.\nDing, Z.L., Derbyshire, E., Yang, S.L., Yu, Z.W., Xiong, S.F. and Liu, T.S., 2002. Stacked 2.6-Ma grain\nsize record from the Chinese loess based on five sections and correlation with the deep-sea\nδ18O record. Paleoceanography, 17(3): doi:10.1029/2001PA000725.\nDing, Z.L., Liu, T.S., Rutter, N.W., Yu, Z.W., Guo, Z.T. and Zhu, R.X., 1995. Ice-volume forcing of\nEast Asian winter monsoon variations in the past 800,000 Years. Quaternary Research, 44(2):\n149–159.\nDyez, K.A., Hönisch, B. and Schmidt, G.A., 2018. Early Pleistocene obliquity‐scale pCO variability\n2\nat~ 1.5 million years ago. Paleoceanography and Paleoclimatology, 33(11): 1270–1291.\nGradstein, F.M., Ogg, J.G., Schmitz, M.D. and Ogg, G.M., 2020. Geologic Time Scale 2020. Elsevier.\nGuillermic, M., Misra, S., Eagle, R. and Tripati, A., 2022. Atmospheric CO estimates for the Miocene\n2\nto Pleistocene based on foraminiferal δ11B at Ocean Drilling Program Sites 806 and 807 in the\nWestern Equatorial Pacific. Climate of the Past, 18(2): 183–207.\nHao, Q.Z., Wang, L., Oldfield, F., Peng, S.Z., Qin, L., Song, Y., Xu, B., Qiao, Y.S., Bloemendal, J. and\nGuo, Z.T., 2012. Delayed build-up of Arctic ice sheets during 400,000-year minima in\ninsolation variability. Nature, 490(7420): 393–396.\nJin, C.S., Liu, Q.S., Xu, D.K., Sun, J.M., Li, C.G., Zhang, Y., Han, P. and Liang, W.T., 2019. A new\ncorrelation between Chinese loess and deep-sea δ18O records since the middle Pleistocene.\nEarth and Planetary Science Letters, 506: 441–454.\nLaj, C. and Channell, J.E.T., 2007. Geomagnetic excursions. In: Treatise in Geophysics: Volume 5,\nGeomagnetism (editor: M. Kono). Chapter 10, Elservier, Amsterdam: 373–416.\nMartínez-Botí, M.A., Foster, G.L., Chalk, T.B., Rohling, E.J., Sexton, P.F., Lunt, D.J., Pancost, R.D.,\nBadger, M.P.S. and Schmidt, D.N., 2015. Plio-Pleistocene climate sensitivity evaluated using\nhigh-resolution CO\n2\nrecords. Nature, 518(7537): 49–54.\nPan, Q., Xiao, G.Q., Zhao, Q.Y., Chen, R.S., Ao, H., Shen, Y.F., Cheng, J.Y. and Zhu, Z.M., 2021. The\nJaramillo subchron in Chinese loess-paleosol sequences. Palaeogeography Palaeoclimatology\nPalaeoecology, 572: 110423.\nRoberts, A.P., 2008. Geomagnetic excursions: knowns and unknowns. Geophysical Research Letters,\n35: L17307.\nthe evolution of Neogene ocean carbonate chemistry using the boron isotope pH proxy. Earth\nand Planetary Science Letters, 498: 362–376.\nSun, Y.B., An, Z.S., Clemens, S.C., Bloemendal, J. and Vandenberghe, J., 2010. Seven million years\nof wind and precipitation variability on the Chinese Loess Plateau. Earth and Planetary Science\nLetters, 297(3-4): 525–535.\nSun, Y.B., Clemens, S.C., An, Z.S. and Yu, Z.W., 2006. Astronomical timescale and palaeoclimatic\nimplication of stacked 3.6-Myr monsoon records from the Chinese Loess Plateau. Quaternary\nScience Reviews, 25(1-2): 33–48.\nUjvári, G., Kok, J.F., Varga, G. and Kovács, J., 2016. The physics of wind-blown loess: Implications\nfor grain size proxy interpretations in Quaternary paleoclimate studies. Earth-Science Reviews,\n154: 247–278.\nXiao, J.L., Porter, S.C., An, Z.S., Kumai, H. and Yoshikawa, S., 1995. Grain size of quartz as an\nindicator of winter monsoon strength on the loess plateau of central China during the last\n130000 yr. Quaternary Research, 43: 22–29.\nReviewer #2 (Remarks to the Author):\nThe authors have done a very thorough job revising their manuscript in line with all of the reviewers’\ncomments, and the revised paper is clearer, more accessible, and more impactful. I therefore\nrecommend it for publication in its present form, with a few small comments below.\nRevised Figures 1b and 1c are a great addition, and are much more informative with respect to dust\nsources. To make this figure even better, I suggest putting a black outline box on Map a showing the\narea in Map b, and in Map b denoting the area blown up in Map c!\nRevised Figure 2 is also much improved in my view, and my comments have been taken on board. The\nnew pCO2 figure is very nice and much more representative of actual proxy reconstructions. I suggest\nputting more intuitive axis titles for panels d and f showing the filtered records, instead of “fitting”\n(e.g., xx-xx kyr filtered MGS). Is the text that says “Red clay” below record c supposed to be there? If\nso, I wasn’t sure why. The inclusion of the 982 SST record is nice, please check that you used the\nupdated age model in Herbert 2016.\nI don’t think that “northern hemisphere” should be systematically capitalised. Same for late Pliocene\nand early Pleistocene, as they are not official sub-epochs.\nLine 176 “stronger inferred AWM winds”?\nThe cross-wavelet analysis between MGS and sea level is a nice addition to the paper.\nThe new Supp. Fig 11 comparing different iNHG monsoon records is really interesting and definitely\nopens the floor for discussion. Nice addition.\nSupp. Fig. 8 – I don’t quite understand why the grey dashed lines, which presumably show tie points\n(not specified in the caption), don’t match up with the red dots (“tuning points”)\nClara Bolton\nReviewer #3 (Remarks to the Author):\nThe authors have duly addressed the issues raised in my review. I have no further comments.\nWe thank the reviewers and the editor for evaluating our manuscript. Please find below our\npoint-by-point responses in blue. Our revisions in the main text are also marked in blue.\nReviewer #2\nGeneral comments:\nThe authors have done a very thorough job revising their manuscript in line with all of the reviewers’\ncomments, and the revised paper is clearer, more accessible, and more impactful. I therefore\nrecommend it for publication in its present form, with a few small comments below.\nResponse: We thank Reviewer #2 for their positive evaluation and helpful comments.\nSpecific comment #1\nRevised Figures 1b and 1c are a great addition, and are much more informative with respect to dust\nsources. To make this figure even better, I suggest putting a black outline box on Map a showing the\narea in Map b, and in Map b denoting the area blown up in Map c!\nResponse: We have further revised Fig. 1 as suggested.\nSpecific comment #2\nRevised Figure 2 is also much improved in my view, and my comments have been taken on board. The\nnew pCO2 figure is very nice and much more representative of actual proxy reconstructions. I suggest\nputting more intuitive axis titles for panels d and f showing the filtered records, instead of “fitting”\n(e.g., xx-xx kyr filtered MGS). Is the text that says “Red clay” below record c supposed to be there? If\nso, I wasn’t sure why. The inclusion of the 982 SST record is nice, please check that you used the\nupdated age model in Herbert 2016.\nResponse: We have revised panels d and f as suggested. “Red clay” below record c has been removed.\nWe now adopt the updated age model of the 982 SST record by Herbert et al. (2016).\nSpecific comment #3\nI don’t think that “northern hemisphere” should be systematically capitalised. Same for late Pliocene\nand early Pleistocene, as they are not official sub-epochs.\nResponse: We have changed “Northern Hemisphere”, “Late Pliocene”, and “Early Pleistocene” to\n“northern hemisphere”, “late Pliocene”, and “early Pleistocene”, respectively, throughout.\nSpecific comment #4\nLine 176 “stronger inferred AWM winds”?\nResponse: This indicates more significant AWM intensification during glacials compared to\ninterglacials across the iNHG. We have included this information in the revised manuscript (lines 164-\n165).\nSpecific comment #5\nThe cross-wavelet analysis between MGS and sea level is a nice addition to the paper. The new Supp.\nFig 11 comparing different iNHG monsoon records is really interesting and definitely opens the floor\nfor discussion. Nice addition.\nResponse: We thank Reviewer #2 for their positive evaluation on these revisions.\nSpecific comment #6\n(not specified in the caption), don’t match up with the red dots (“tuning points”).\nResponse: We have changed the now green (previous grey) dashed lines to match the red dots\n(Supplementary Fig. 8).\n2"}]

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