DOI: 10.5194/tc-15-1065-2021
论文题名: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density
作者: Keenan E. ; Wever N. ; Dattler M. ; Lenaerts J.T.M. ; Medley B. ; Kuipers Munneke P. ; Reijmer C.
刊名: Cryosphere
ISSN: 19940416
出版年: 2021
卷: 15, 期: 2 起始页码: 1065
结束页码: 1085
语种: 英语
英文关键词: calibration
; climate variation
; ice sheet
; satellite altimetry
; sea level change
; snow cover
; snowpack
; Antarctic Ice Sheet
; Antarctica
英文摘要: 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 driftingsnow 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 m) density to be more in line with observations (near-surface bias reduction from 44.9 to 5.4 kgm 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 mean bias D 9:7 kgm 3, IMAU-FDM mean bias D 32:5 kgm 3, GSFC-FDM mean bias D 15:5 kgm 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 7-10m (SNOWPACK bias D 22:5 kgm 3, GSFC-FDM bias D 10:6 kgm 3) and throughout the entire near surface at high-accumulation sites (SNOWPACK bias D 31:4 kgm 3, GSFC-FDM bias D 4:7 kgm 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. © 2021 Copernicus GmbH. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/164722
Appears in Collections: 气候变化与战略
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作者单位: Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO USA, United States; Department of Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD USA, United States; Cryospheric Sciences Laboratory, Nasa Goddard Space Flight Center, Greenbelt, MD, United States; Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, Netherlands
Recommended Citation:
Keenan E.,Wever N.,Dattler M.,et al. Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density[J]. Cryosphere,2021-01-01,15(2)