Deposition of light-absorbing particles on glacier surfaces poses a series of adverse impacts on the cryospheric environment, climate and human health. Broad attention of the scientific community has been paid on insoluble light-absorbing impurities (ILAIs) in snow and ice on glaciers over the Tibetan Plateau (TP). However, systematic investigation of ILAIs in snowpack of glaciers on the TP is scarce. In this study, the properties and darkening effect of ILAIs in snowpack on glaciers are extensively investigated in the southeast of TP. Results show that ILAIs concentrations in multiple types of snow and ice samples were significantly different. Snowpit depths varied substantially from one profile to another during May and June 2016. The average concentrations of ILAls in snowpits increase as snow melting progresses. Black carbon (BC) and dust cause snow albedo reduction more in snow with larger grain size Re. Based on a radiative transfer model calculation, the average albedo reduction induced by BC in the snowpack was 0.141 +/- 0.02, and associated daily maximum radiative forcing (RF) was 72.97 +/- 12.7 W m(-2). BC is a controlling light-absorbing factor in snowpack and causes substantial albedo reduction and thus the associated daily maximum RF. The maximum reduction of snow cover duration was 4.56 +/- 0.71 days caused by BC and dust in snowpack in southeastern TP. The average mass absorption cross- (MAC) of BC from multiple snowpits was 3.26 +/- 0.46 m(2) g(-1), which represents a typical value of MAC in snow on glaciers, but it is type-dependent of snow/ice samples. Tropospheric aerosols vertically extended up to 8 km over the TP and its surrounding areas, which indicates the transport of aerosols from remote sources through elevated pathways. A large amount of carbon stored in the brittle glaciers can be potentially released with meltwater runoff under a warming climate. This study provides a new insight for investigating carbonaceous and light-absorbing particles in glacierization areas. (C) 2019 Elsevier Ltd. All rights reserved.

Deposition of light-absorbing particles on glacier surfaces poses a series of adverse impacts on the cryospheric environment, climate and human health. Broad attention of the scientific community has been paid on insoluble light-absorbing impurities (ILAIs) in snow and ice on glaciers over the Tibetan Plateau (TP). However, systematic investigation of ILAIs in snowpack of glaciers on the TP is scarce. In this study, the properties and darkening effect of ILAIs in snowpack on glaciers are extensively investigated in the southeast of TP. Results show that ILAIs concentrations in multiple types of snow and ice samples were significantly different. Snowpit depths varied substantially from one profile to another during May and June 2016. The average concentrations of ILAls in snowpits increase as snow melting progresses. Black carbon (BC) and dust cause snow albedo reduction more in snow with larger grain size Re. Based on a radiative transfer model calculation, the average albedo reduction induced by BC in the snowpack was 0.141 +/- 0.02, and associated daily maximum radiative forcing (RF) was 72.97 +/- 12.7 W m(-2). BC is a controlling light-absorbing factor in snowpack and causes substantial albedo reduction and thus the associated daily maximum RF. The maximum reduction of snow cover duration was 4.56 +/- 0.71 days caused by BC and dust in snowpack in southeastern TP. The average mass absorption cross- (MAC) of BC from multiple snowpits was 3.26 +/- 0.46 m(2) g(-1), which represents a typical value of MAC in snow on glaciers, but it is type-dependent of snow/ice samples. Tropospheric aerosols vertically extended up to 8 km over the TP and its surrounding areas, which indicates the transport of aerosols from remote sources through elevated pathways. A large amount of carbon stored in the brittle glaciers can be potentially released with meltwater runoff under a warming climate. This study provides a new insight for investigating carbonaceous and light-absorbing particles in glacierization areas. (C) 2019 Elsevier Ltd. All rights reserved.

[1] New aerosol modules of global ( circulation and chemical transport) models are evaluated. These new modules distinguish among at least five aerosol components: sulfate, organic carbon, black carbon, sea salt, and dust. Monthly and regionally averaged predictions for aerosol mass and aerosol optical depth are compared. Differences among models are significant for all aerosol types. The largest differences were found near expected source regions of biomass burning ( carbon) and dust. Assumptions for the permitted water uptake also contribute to optical depth differences ( of sulfate, organic carbon, and sea salt) at higher latitudes. The decline of mass or optical depth away from recognized sources reveals strong differences in aerosol transport or removal among models. These differences are also a function of altitude, as transport biases of dust do not always extend to other aerosol types. Ratios of optical depth and mass demonstrate large differences in the mass extinction efficiency, even for hydrophobic aerosol. This suggests that efforts of good mass simulations could be wasted or that conversions are misused to cover for poor mass simulations. In an attempt to provide an absolute measure for model skill, simulated total optical depths ( when adding contributions from all five aerosol types) are compared to measurements from ground and space. Comparisons to the Aerosol Robotic Network (AERONET) suggest a source strength underestimate in many models, most frequently for ( subtropical) tropical biomass or dust. Comparisons to the combined best of Moderate-Resolution Imaging Spectroradiometer ( MODIS) and Total Ozone Mapping Spectrometer ( TOMS) indicate that away from sources, model simulations are usually smaller. Particularly large are discrepancies over tropical oceans and oceans of the Southern Hemisphere, raising issues on the treatment of sea salt in models. Totals for mass or optical depth in many models are defined by the absence or dominance of only one aerosol component. With appropriate corrections to that component ( e. g., to removal, to source strength, or to seasonality) a much better model performance can be expected. Still, many important modeling issues remain inconclusive as the combined result of poor coordination ( different emissions and meteorology), insufficient model output ( vertical distributions, water uptake by aerosol type), and unresolved measurement issues ( retrieval assumptions and temporal or spatial sampling biases).