Investigating the Impact of Aerosol Deposition on Snow Melt over the Greenland Ice Sheet Using a Large-Ensemble Kernel

Yang Li, Mark G. Flanner
2018 Atmospheric Chemistry and Physics Discussions  
<p><strong>Abstract.</strong> Accelerating surface melt on the Greenland Ice Sheet (GrIS) has led to a doubling of Greenland's contribution to global sea level rise during recent decades. Black carbon (BC), dust, and other light absorbing impurities (LAI) darken the surface and enhance snow melt by boosting the absorption of solar energy. It is therefore important for coupled aerosol-climate and ice sheet models to include snow darkening effects from LAI, and yet most do not. In this study, we
more » ... In this study, we conduct several thousand simulations with the Community Land Model (CLM) component of the Community Earth System Model (CESM) to characterize changes in melt runoff due to variations in the amount, timing, and nature (wet or dry) of BC deposition on the GrIS. From this large matrix of simulations, we develop a kernel relating runoff to the location, month, year (from 2006&amp;ndash;2015), and magnitudes of BC concentration within precipitation and dry deposition flux. BC deposition during June&amp;ndash;August causes the largest increase in annually-integrated runoff, but winter deposition events also exert large (roughly half as great) runoff perturbations due to re-exposure of impurities at the snow surface during summer melt. Current BC deposition fluxes simulated with the atmosphere component of CESM induce a climatological-mean increase in GrIS-wide runoff of ~<span class="thinspace"></span>8<span class="thinspace"></span>Gt/yr, or +<span class="thinspace"></span>6.8<span class="thinspace"></span>% relative to a paired simulation without BC deposition. We also provide linear equations that relate the increase in total runoff to GrIS-wide wet and dry BC deposition fluxes. It is our hope that the runoff kernel and simple equations provided here can be used to extend the utility of state-of-the-art aerosol models.</p>
doi:10.5194/acp-2018-542 fatcat:sevfiyczsnbvlbytv52s5vslx4