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The patchwork loess of Central Asia: Implications for interpreting aeolian dynamics and past climate circulation in piedmont regions

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    0568437 - ÚJF 2024 RIV US eng J - Journal Article
    Dave, A. K. - Lisá, Lenka - Scardia, G. - Nigmatova, S. - Fitzsimmons, K. E.
    The patchwork loess of Central Asia: Implications for interpreting aeolian dynamics and past climate circulation in piedmont regions.
    Journal of Quaternary Science. Roč. 38, č. 4 (2023), s. 526-543. ISSN 0267-8179. E-ISSN 1099-1417
    R&D Projects: GA MŠMT EF16_019/0000728
    Institutional support: RVO:61389005
    Keywords : Central Asia * Chinese Loess Plateau * loess * luminescence dating * mass accumulation rates
    OECD category: Analytical chemistry
    Impact factor: 2.3, year: 2022
    Method of publishing: Limited access
    https://doi.org/10.1002/jqs.3493

    Reconstruction of mass accumulation rates (MARs) in loess deposits are widely used for interpreting long-term aeolian transport and climate dynamics in terrestrial environments. However, these interpretations are often driven by a preponderance of reconstructions from individual or selected sites, which can bias our understanding of past climate, especially in the absence of other proxy information. Recent studies on MARs from multiple loess sites in Arid Central Asia (ACA) reveal disparities in the timing of peaks in accumulation between sites, as well as asynchronies with loess flux in the Chinese Loess Plateau (CLP). We investigate this issue by (1) dating five new sites from the western Ili Basin, therefore extending the spatial cover of loess chronologies across ACA and (2) combining that with MARs from >30 sites across ACA and the CLP over the last 60 ka. Our results indicate spatio-temporal inhomogeneity in the timing and rate of loess deposition across the ACA, and highlight the importance of interrogating local and regional influences on dust supply and transport. Our synthesis of MARs from ACA and the CLP suggests that the timing of peak dust flux as an indicator of large-scale climate dynamics is best derived from an aggregate of sites, this removes site-specific bias where local processes or topographic settings outweigh the climate signature.
    Permanent Link: https://hdl.handle.net/11104/0342749


    Research data: NOAA/WDS Paleoclimatology
     
     
Number of the records: 1  

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