A representative density profile of the North Greenland snowpack

Abstract

Abstract. Along a traverse through North Greenland in May 2015 we collected snow cores up to 2 m depth and analyzed their density and water isotopic composition. A new sampling technique and an adapted algorithm for comparing data sets from different sites and aligning stratigraphic features are presented. We find good agreement of the density layering in the snowpack over hundreds of kilometers, which allows the construction of a representative density profile. The results are supported by an empirical statistical density model, which is used to generate sets of random profiles and validate the applied methods. Furthermore we are able to calculate annual accumulation rates, align melt layers and observe isotopic temperatures in the area back to 2010. Distinct relations of δ 18 O with both accumulation rate and density are deduced. Inter alia the depths of the 2012 melt layers and high-resolution densities are provided for applications in remote sensing.

Evaluating a Regional Climate Model Simulation of Greenland Ice Sheet Snow and Firn Density for Improved Surface Mass Balance Estimates

“…We compare MAR with snow and firn density measurements from the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) data set Montgomery et al, 2018), which is a compilation of density measurements from multiple sources (Alley, 1999;Baker, 2016;Benson, 2013Benson, , 2017Bolzan & Strobel, 1999a, 1999b, 1999c, 1999d, 1999e, 1999f, 1999g, 2001a, 2001bChellman, 2016;Conway, 2003;Cooper et al, 2018;Dibb & Fahnestock, 2004;Dibb et al, 2007;Harper et al, 2012;Hawley et al, 2014;Koenig et al, 2014;Vandecrux et al, 2019;Machguth et al, 2016;Mayewski & Whitlow, 2009a, 2009b, 2009c, 2009dMiège et al, 2013;Miller & Schwager, 2000a, 2000bMosley-Thompson et al, 2001;Ohmura, , 1992Renaud, 1959;Schaller et al, 2016Schaller et al, , 2017Wilhelms, 2000aWilhelms, , 2000bWilhelms, , 2000cWilhelms, , 2000d. The 2018 version of the SUMup data set contains 761 unique profiles collected at 633 locations on the Greenland ice sheet.…”

A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling

“…We gathered annual air temperatures, accumulation rates, and density observations from snow pits and firn cores from the Greenland Climate Network (GC-Net) (Steffen et al, 1996), the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) (Van As et al, 2016b), and the Arctic Circle Traverses (ACTs) (e.g., Machguth et al, 2016). Lastly, we also included observations by Schaller et al (2016) from the NEEM to EGRIP traverse, and from the López-Moreno et al 2016Greenland circumnavigation. Accumulation rates in the database are not long-term averages, but represent the preceding year's snowfall.…”

“…There is a strong impetus to constrain critical processes in order to reduce uncertainties in mass balance estimates (e.g., Shepherd et al, 2012;IPCC, 2013;Khan et al, 2015). In particular, an improved understanding of ice-sheet-wide snow and firn properties can reduce uncertainties in: remotely-sensed or modeled ice sheet mass budget (e.g., Van den Broeke et al, 2016), identifying internal layers for calculating accumulation rates from combined radar and firn core surveys (Hawley et al, 2006(Hawley et al, , 2014de la Peña et al, 2010;Miège et al, 2013;Karlsson et al, 2016;Koenig et al, 2016;Overly et al, 2016;Lewis et al, 2017), and quantifying meltwater retention (Harper et al, 2012;Humphrey et al, 2012;Machguth et al, 2016) and accumulation rates (López-Moreno et al, 2016;Schaller et al, 2016) from firn cores and snow pits. Improved estimates of surface snow density, which serves as an important boundary condition in firn densification modeling, can reduce uncertainties in mass budget studies (e.g., Sørensen et al, 2011;Csatho et al, 2014;Hurkmans et al, 2014;Morris and Wingham, 2014;Colgan et al, 2015) that convert remotely-sensed volume changes to mass changes based on either depth-density profile relations or surface snow density parameterizations.…”

Microstructure of Snow and Its Link to Trace Elements and Isotopic Composition at Kohnen Station, Dronning Maud Land, Antarctica

“…Due to seasonally varying snowfall conditions, snow density can exhibit a seasonal pattern, when spatial variability is considered (e.g. Laepple et al, 2016;Schaller et al, 2016). Strong wind events can lead to high-density layers as tracers of dune formations (e.g.…”