Evaluating a Regional Climate Model Simulation of Greenland Ice Sheet Snow and Firn Density for Improved Surface Mass Balance Estimates. Issue 21 (3rd November 2019) - Alexander, P. M.
Abstract: Modeling vertical profiles of snow and firn density near the surface of the Greenland ice sheet (GrIS) is key to estimating GrIS mass balance, and by extension, global sea level change. To understand sources of error in simulated GrIS density, we compare GrIS density profiles from a leading regional climate model with coincident in situ measurements. We identify key contributors to model density and mass balance biases, including underestimated simulated fresh snow density (which leads to underestimation of density in the top 1 m of snow by ~10%). In areas undergoing frequent melting, positive density biases (of 7% in the top 1 m, and 10% between 1 and 10 m) are likely associated with errors in representing meltwater production, retention, and refreezing. The results highlight the importance of accurately capturing fresh snow density and meltwater processes in models used to estimate GrIS mass balance change. Plain Language Summary: The density of snow (and firn–high‐density compacted snow) on the Greenland ice sheet is an important parameter because it is used to convert changes in ice sheet thickness measured from satellite and airborne instruments into changes in mass, which is key to estimating the ice sheet contribution to sea level change. The simulation of density in climate models such as the one examined in this study is therefore important to making estimates of current and future sea level change from ice sheets. In this study we compare snow density values simulated by a climate model with a large collection of measurements taken on the Greenland ice sheet. We find that the model tends to underestimate density near the surface in dry regions, and overestimates it where there is substantial meltwater produced during summer months that subsequently refreezes, which could lead to errors in mass change estimates. We provide suggestions regarding model adjustments that will likely improve the simulation of snow density and which are likely also relevant to other climate model simulations. Key Points: We evaluate simulated Greenland snow and firn density from the MAR regional climate model to address surface mass balance uncertainty A −10% model bias in density of the top 1 m could lead to a −10% SMB bias from remote sensing estimates in dry snow areas Meltwater processes produce a positive model density bias of 10% for 1‐ to 10‐m depth, limiting the snow liquid water retention capacity