Global and Planetary Change最新文献

Interannual-to millennial-scale climate cycles have been recognized in ancient sedimentary strata and may be closely associated with solar activity. However, the physical driving mechanisms of such cycles remain a mystery. To better understand the nature and evolution of suborbital cycles in ice-free conditions, we performed a quantitative analysis of high-resolution phosphorus (P), gray-scale values, and iron (Fe) data obtained from a core deposited in a mid-latitude lake (Funing Formation of the Subei Basin) during the Late Paleocene-Early Eocene. Time series analysis reveals evidence for ∼88-yr and ∼ 11-yr solar activity cycles in the gray value data, and ∼ 20-kyr precession cycles, ∼10-kyr half-precession cycles, and ∼ 2-kyr solar activity cycles in the Fe data. The data indicate that paleoclimate changes in the Subei Basin at this time were driven by both orbital and suborbital cycles. Amplitude modulation analysis suggests that ∼20-kyr precession modulated the amplitude of the observed 2-kyr cycles. It is inferred that the Earth's climate is driven not only by eccentricity-modulated precession cycle, but also by precession-modulated millennial cycles.

Southern Europe is hypothesized to have acted as a glacial refugium for hominin populations during the Pleistocene. Of particular importance is South-East Europe, which most likely played a dual role, both as refugium and dispersal corridor, especially during the Middle Pleistocene glaciations, when drastic climatic conditions led to major sea level drops in the Aegean. However, little is known about the palaeoenvironmental conditions at the time of hominin presence in this region, making these hypotheses difficult to test. Here we analyze biomarker data and leaf wax stable isotopic compositions of the MIS 12 Lower Palaeolithic site Marathousa 1 (Megalopolis Basin, Greece) to assess the climatic conditions accompanying the time of hominin presence in the area. Our data indicate a major cooling affecting the north Mediterranean/Aegean domain during this time interval, with lowest temperatures recorded between ∼440–432 ka. The glacial peak is associated with changes in vegetation (i.e., from more forested to more open landscape), reduction of humidity and water availability (i.e., moisture depletion, increased evaporation). Hominins are present at the Marathousa 1 location at the end of this interval (434–432 ka), confirming that the Megalopolis Basin served as a refugium for hunter-gatherer groups during periods of harsh climatic conditions. Additionally, the progressive cooling is associated with an important sedimentary hiatus between ∼465–440 ka reflected in all circum-Mediterranean records (both marine and continental), indicating a regional impact of the MIS 12 glaciation over surface processes.

Understanding future temperature extremes is pivotal to preparing for and mitigating the impacts of climate change. This study proposed machine learning techniques to develop a multi-model ensemble model for high-resolution projection of global land temperature extremes under different emission scenarios, hence providing enhanced precision over previous climate model projections. By utilizing the NEX-GDDP-CMIP6 dataset with bias adjustment and the Gradient Booster algorithm, we reduced the biases that existed in Global Climate Models. The model significantly reduces the root mean square errors (RMSEs) for both the daily maximum and daily minimum temperature extremes. A future scenario analysis revealed that global temperature extremes would substantially increase under high-emission scenarios, highlighting the urgency for stringent emission reduction commitments. This study also identified regions like Greenland, the Tibetan Plateau, and the regional Arctic Archipelago as potential hotspots of temperature extremes under these scenarios. The multi-model ensemble approach, tuned with machine learning and driven by high-resolution data, contributes to climate science by providing refined insights into future temperature extremes, thereby offering direction to climate change mitigation and adaptation strategies.

In recent decades, the Central Plains Urban Agglomeration of China (CPUA) has faced recurring extreme precipitation events (EPEs), leading to severe floods, endangering residents, and causing significant property damage. This study examines the spatiotemporal patterns of summer EPEs in the CPUA from 1961 to 2022. We used the Hybrid Single-Particle Lagrangian Integrated Trajectory model to trace the water vapor trajectories associated with these events, identifying atmospheric circulations linked to various moisture sources. Summer EPEs in the CPUA have become more frequent and intense. Urban regions typically experience stronger EPEs, while mountainous regions encounter more frequent but milder precipitation. The moisture contributing to these events comes from sources including Eurasia (9.94 %), the northern and southern Western North Pacific (48.39 %), and the Bay of Bengal and South China Sea (41.67 %). Notably, contributions from Eurasia and the northern Western North Pacific have increased, whereas those from the Bay of Bengal and the South China Sea have decreased. Events driven by Western North Pacific moisture have stronger impacts on urban areas, influenced by abnormal anticyclonic patterns and the development of the Huang-Huai cyclone, which triggers intense convective activity over the CPUA. The strengthening of the Western North Pacific subtropical high promotes the transport of warm air, which merges with colder inland air, leading to extreme precipitation.

Mongolia and northern China have the highest frequency of dust weather in Northeast Asia. Dust transport from Mongolia to China is a major cause of dust weather in northern China. However, there has been limited research on the frequency changes of cross-border dust storms from Mongolia to China over the past few decades. Based on observational data, we analyzed the variation in cross-border dust storms between China and Mongolia during 1987–2022. The results indicate that, on average, approximately seven cross-border dust storm events occur annually between China and Mongolia, predominantly during the spring. The frequency of cross-border dust storms from Mongolia to China significantly increased from 2.2 events in P1 (1987–1999) to 7.5 events in P2 (2000−2022). Long-term trends suggest that rising dust emissions in east-central Mongolia largely contributed to this increase. The increase in cross-border dust storms from Mongolia to China in the spring was driven by more frequent cyclones in eastern Mongolia and Northeast China during P2. This is evidenced by a negative height anomaly and increased vorticity at 850 hPa over Northeast China. The cyclones were linked to the northward shift of the East Asian Polar Front Jet Stream (EAPJ) at 300 hPa between 50°N and 60°N. Additionally, surface conditions such as higher temperatures and decreased vegetation in Mongolia contributed to the increased frequency of cross-border dust storms from P1 to P2.