The Community Firn Model (CFM) v1.0

Stevens, C. Max; Verjans, Vincent; Lundin, J.; Kahle, Emma C.; Horlings, Annika N.; Horlings, Brita I.; Waddington, Edwin D.

doi:10.5194/gmd-13-4355-2020

Cited by 47 publications

(56 citation statements)

References 82 publications

(151 reference statements)

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“…In addition to IMAU-FDM we also compare SNOWPACK to the NASA Goddard Space Flight Center firn densification model (GSFC-FDMv1) which provides simulated firn properties over the past 40 years for both the Greenland and Antarctic ice sheets (Medley et al, 2020). GSFC-FDM uses the Community Firn Model, a modular, open-source framework for Lagrangian modeling of several firn and firn-air-related processes within a single column (Stevens et al, 2020). The GSFC-FDM simulations are forced by an enhanced-resolution hybridized MERRA-2 that was developed by exploiting a 15-year, 12.5 km resolution offline MERRA-2 reanalysis.…”

Section: Gsfc-fdm Modelmentioning

confidence: 99%

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

et al. 2021

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Abstract. 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 m) density to be more in line with observations (near-surface bias reduction from −44.9 to −5.4 kg 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 mean bias=-9.7 kg m−3, IMAU-FDM mean bias=-32.5 kg m−3, GSFC-FDM mean bias=15.5 kg 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 m (SNOWPACK bias=-22.5 kg m−3, GSFC-FDM bias=10.6 kg m−3) and throughout the entire near surface at high-accumulation sites (SNOWPACK bias=-31.4 kg m−3, GSFC-FDM bias=-4.7 kg 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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Section: Gsfc-fdm Modelmentioning

confidence: 99%

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

et al. 2021

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“…The choice of this value was based on work in Antarctica which found that firn permeability reaches 0 over a range of densities centered on 810 kg m −3 (Gregory et al, 2014). Unfortunately, such studies remain scarce in Greenland, and results do not provide a definite constraint on permeability (e.g., Albert and Shultz, 2002;Sommers et al, 2017). The DTU model uses a similar threshold density to characterize a layer's impermeability but found that 917 kg m −3 gave the best match with observed firn density profiles (Simonsen et al, 2013).…”

Section: Ice Slabsmentioning

confidence: 99%

The firn meltwater Retention Model Intercomparison Project (RetMIP): evaluation of nine firn models at four weather station sites on the Greenland ice sheet

et al. 2020

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Abstract. Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models (±2σ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.

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“…Therefore, changes in elevation of an ice sheet can be modeled using accumulation and temperature data or estimates as inputs to a firn compaction model (FCM). We use accumulation and temperature changes from RACMO2.3p2 outputs and the model developed by Stevens et al (2020) to account for firn compaction [54]. Referring to the implementation by Stevens et al…”

Section: From Modelingmentioning

confidence: 99%

Inter-Annual Variability in the Antarctic Ice Sheets Using Geodetic Observations and a Climate Model

2021

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Quantifying the mass balance of the Antarctic Ice Sheet (AIS), and the resulting sea level rise, requires an understanding of inter-annual variability and associated causal mechanisms. Very few studies have been exploring the influence of climate anomalies on the AIS and only a vague estimate of its impact is available. Changes to the ice sheet are quantified using observations from space-borne altimetry and gravimetry missions. We use data from Envisat (2002 to 2010) and Gravity Recovery And Climate Experiment (GRACE) (2002 to 2016) missions to estimate monthly elevation changes and mass changes, respectively. Similar estimates of the changes are made using weather variables (surface mass balance (SMB) and temperature) from a regional climate model (RACMO2.3p2) as inputs to a firn compaction (FC) model. Elevation changes estimated from different techniques are in good agreement with each other across the AIS especially in West Antarctica, Antarctic Peninsula, and along the coasts of East Antarctica. Inter-annual height change patterns are then extracted using for the first time an empirical mode decomposition followed by a principal component analysis to investigate for influences of climate anomalies on the AIS. Investigating the inter-annual signals in these regions revealed a sub-4-year periodic signal in the height change patterns. El Niño Southern Oscillation (ENSO) is a climate anomaly that alters, among other parameters, moisture transport, sea surface temperature, precipitation, in and around the AIS at similar frequency by alternating between warm and cold conditions. This periodic behavior in the height change patterns is altered in the Antarctic Pacific (AP) sector, possibly by the influence of multiple climate drivers, like the Amundsen Sea Low (ASL) and the Southern Annular Mode (SAM). Height change anomaly also appears to traverse eastwards from Coats Land to Pine Island Glacier (PIG) regions passing through Dronning Maud Land (DML) and Wilkes Land (WL) in 6 to 8 years. This is indicative of climate anomaly traversal due to the Antarctic Circumpolar Wave (ACW). Altogether, inter-annual variability in the SMB of the AIS is found to be modulated by multiple competing climate anomalies.

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The Community Firn Model (CFM) v1.0

Cited by 47 publications

References 82 publications

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

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

The firn meltwater Retention Model Intercomparison Project (RetMIP): evaluation of nine firn models at four weather station sites on the Greenland ice sheet

Inter-Annual Variability in the Antarctic Ice Sheets Using Geodetic Observations and a Climate Model

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