The Chinese Loess Plateau (CLP) in northern China serves one of the most prominent loess records in the world. The CLP is an extensive record of changes in past aeolian dust activity in East Asia; however, the interpretation of the loess records is hampered by ambiguity regarding the origin of loess-forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999-2019), we modeled back trajectories for fine (~ 2mu) and super-coarse (~ 20mu) dust particles at six CLP sites during the peak dust storm season from March to May. The source receptor relationship from FLEXPART is combined with the dust emission inventory from FLEXDUST to create site-dependent high-resolution maps of the source contribution of deposited dust. The nearby dust-emission areas dominate the source contribution at all sites. Wet deposition is important for dust deposition at all sites, regardless of dust size. Non-negligible amounts of dust from distant emission regions could be wet deposited on the CLP following high-level tropospheric transport, with the super-coarse dust preferentially from emission areas upwind of sloping topography. On an interannual scale, the phase of the Arctic Oscillation (AO) in winter was found to have a strong impact on the deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential.

Natalie J Burls

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The Miocene epoch, spanning 23.03-5.33Ma, was a dynamic climate of sustained, polar amplified warmth. Miocene atmospheric CO2 concentrations are typically reconstructed between 300-600ppm and were potentially higher during the Miocene Climatic Optimum (16.75-14.5Ma). With surface temperature reconstructions pointing to substantial midlatitude and polar warmth, it is unclear what processes maintained the much weaker-than-modern equator-to-pole temperature difference. Here we synthesize several Miocene climate modeling efforts together with available terrestrial and ocean surface temperature reconstructions. We evaluate the range of model-data agreement, highlight robust mechanisms operating across Miocene modelling efforts, and regions where differences across experiments result in a large spread in warming responses. Prescribed CO2 is the primary factor controlling global warming across the ensemble. On average, elements other than CO2, such as Miocene paleogeography and ice sheets, raise global mean temperature by ~ 2℃, with the spread in warming under a given CO2 concentration (due to a combination of the spread in imposed boundary conditions and climate feedback strengths) equivalent to ~1.2 times a CO2 doubling. This study uses an ensemble of opportunity: models, boundary conditions, and reference datasets represent the state-of-art for the Miocene, but are inhomogeneous and not ideal for a formal intermodel comparison effort. Acknowledging this caveat, this study is nevertheless the first Miocene multi-model, multi-proxy comparison attempted so far. This study serves to take stock of the current progress towards simulating Miocene warmth while isolating remaining challenges that may be well served by community-led efforts to coordinate modelling and data activities within a common analysis framework.