Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density

Keenan, Eric; Wever, Nander; Dattler, Marissa; Lenaerts, Jan T. M.; Medley, Brooke; Kuipers Munneke, Peter; Reijmer, Carleen

Estimates of snow and firn density are required for satellite-altimetry-based retrievals of ice sheet mass balance that rely on volume-to-mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance and by extension ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new drifting-snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We show that our new scheme improves existing versions of SNOWPACK by increasing simulated near-surface (defined as the top 10 inline-formulam) density to be more in line with observations (near-surface bias reduction from inline-formula−44.9 to inline-formula−5.4 inline-formulakg m−3). Furthermore, we demonstrate high-quality simulation of near-surface Antarctic snow and firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models (SNOWPACK inline-formula M5inlinescrollmathml mean bias = - normal 9.7 88pt10ptsvg-formulamathimgd4563868c957e632f059fa36e2231f24 tc-15-1065-2021-ie00001.svg88pt10pttc-15-1065-2021-ie00001.png inline-formulakg m−3, IMAU-FDM inline-formula M7inlinescrollmathml mean bias = - normal 32.5 94pt10ptsvg-formulamathimg69a418015481211ba8e90f0255d99d5f tc-15-1065-2021-ie00002.svg94pt10pttc-15-1065-2021-ie00002.png inline-formulakg m−3, GSFC-FDM inline-formulamean bias=15.5inline-formulakg m−3). Notably, our analysis is restricted to the near surface where firn density is most variable due to accumulation and compaction variability driven by synoptic weather and seasonal climate variability. Additionally, the GSFC-FDM exhibits lower mean density bias from 7–10 inline-formulam (SNOWPACK inline-formula M12inlinescrollmathml bias = - normal 22.5 64pt10ptsvg-formulamathimge6c05470f8e77a22a94e434af6f2a97a tc-15-1065-2021-ie00003.svg64pt10pttc-15-1065-2021-ie00003.png inline-formulakg m−3, GSFC-FDM inline-formulabias=10.6inline-formulakg m−3) and throughout the entire near surface at high-accumulation sites (SNOWPACK inline-formula M16inlinescrollmathml bias = - normal 31.4 64pt10ptsvg-formulamathimg4ad179be01fb3b38b331d9a69c2e79e6 tc-15-1065-2021-ie00004.svg64pt10pttc-15-1065-2021-ie00004.png inline-formulakg m−3, GSFC-FDM inline-formula M18inlinescrollmathml bias = - normal 4.7 58pt10ptsvg-formulamathimge8f3edc2b3728534494a59661e6445e7 tc-15-1065-2021-ie00005.svg58pt10pttc-15-1065-2021-ie00005.png inline-formulakg m−3). However, we found that the performance of SNOWPACK did not degrade when applied to sites that were not included in the calibration of semi-empirical models. This suggests that SNOWPACK may possibly better represent firn properties in locations without extensive observations and under future climate scenarios, when firn properties are expected to diverge from their present state.

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Keenan, Eric / Wever, Nander / Dattler, Marissa / et al: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density. 2021. Copernicus Publications.

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