Search

Mio‐Pliocene sedimentary archives of the East Asian summer monsoon (EASM) in NE Tibet record a monotonic response to orbital forcing, dominated by eccentricity. By contrast, Pleistocene archives display a more stochastic response that varies regionally and temporally. When and why this response changed is poorly understood. Here, we present a new high‐resolution Rb/Sr ratio data set of EASM intensity from the Sanmenxia Basin, North China, that spans the Plio‐Pleistocene transition. Our results indicate decreased monsoonal rainfall in the late Pliocene, dated at 2.75–2.6 Ma, associated with an intensified response to obliquity and enhanced climate stochasticity. This transition is attributed to the increase of Northern Hemisphere ice volume. Quaternary monsoons display a sensitivity unique to the modern icehouse with large bipolar ice sheets, while pre‐Quaternary monsoons were solely impacted by Antarctic ice sheet dynamics on orbital time‐scales. Plain Language Summary: The late Pliocene‐early Pleistocene transition (LP/EP) is a period of global cooling and the intensification of Northern Hemisphere glaciation. Yet, the evolution of the East Asian summer monsoon (EASM) during this time remains a topic of ongoing discussion and debate. Here we present high‐resolution paleoclimate data from a record of lake sediments across the Pliocene‐Pleistocene transition period. We show that there was a reorganization of the East Asian monsoon system 2.75–2.6 million years ago, associated with an increase in climate forcing caused by cyclic changes in Earth's tilt and in climate stochasticity. This transition is attributed to the appearance of new high‐latitude forcing mechanisms on monsoon intensity caused by the growth of ice sheets in the Northern Hemisphere. Key Points: Cyclic patterns in East Asian summer monsoonal intensity during the Pliocene were mainly driven by Antarctic ice sheet variationsA major reorganization of the East Asian climate system occurred at 2.75–2.6 Ma in response to Northern Hemisphere glaciationQuaternary East Asian summer monsoon on orbital scales displays a sensitivity that is unique to the modern icehouse with bipolar ice sheets [ABSTRACT FROM AUTHOR]

Across the Qinghai–Tibet Plateau (QTP) there is a narrow engineering corridor with widely distributed slopes called the Qinghai–Tibet Engineering Corridor (QTEC), where a variety of important infrastructures are concentrated. These facilities are transportation routes for people, materials, energy, etc. from inland China to the Tibet Autonomous Region. From Golmud to Lhasa, the engineering corridor covers 632 km of permafrost containing the densely developed Qinghai–Tibet Railway and Qinghai–Tibet Highway, as well as power and communication towers. Slope failure in permafrost regions, caused by permafrost degradation, ground ice melting, etc., affects the engineering construction and permafrost environments in the QTEC. We implement a variety of sensors to monitor the hydrological and thermal deformation between permafrost slopes and permafrost engineering projects in the corridor. In addition to soil temperature and moisture sensors, the global navigation satellite system (GNSS), terrestrial laser scanning (TLS), and unmanned aerial vehicles (UAVs) were adopted to monitor the spatial distribution and changes in thermal deformation. An integrated dataset of hydrological and thermal deformation in permafrost engineering and slopes in the QTEC from the 1950s to 2020, including meteorological and ground observations, TLS point cloud data, and RGB and thermal infrared (TIR) images, can be of great value for estimating the hydrological and thermal impact and stability between engineering and slopes under the influence of climate change and engineering disturbance. The dataset and code were uploaded to the Zenodo repository and can be accessed through https://zenodo.org/communities/qtec (last access: 23 June 2021), including meteorological and ground observations at 10.5281/zenodo.5009871 (Luo et al., 2020d), TLS measurements at 10.5281/zenodo.5009558 (Luo et al., 2020a), UAV RGB and TIR images at 10.5281/zenodo.5016192 (Luo et al., 2020b), and R code for permafrost indices and visualisation at 10.5281/zenodo.5002981 (Luo et al., 2020c). [ABSTRACT FROM AUTHOR]