Reconstructing thermal properties of firn at Summit, Greenland, from a temperature profile time series

Giese, Alexandra; Hawley, R. L.

doi:10.3189/2015jog14j204

Cited by 14 publications

(27 citation statements)

References 43 publications

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“…Similar behavior has been observed in some alpine glaciers, which exhibit thermal fracturing in response to cold nighttime temperatures (Podolskiy et al, 2018;Zhang et al, 2019). Because short-period temperature fluctuations only propagate to a depth of several meters in glacial ice (Giese & Hawley, 2015), shallow icequake locations are consistent with the correlation between icequake activity and surface air temperatures. Since both the tidal and the thermal mechanisms produce horizontal tensional stress, it is likely that they act in concert.…”

Section: Temperature Controls Multiday and Seasonal Patterns In Seismsupporting

confidence: 78%

Tidal and Thermal Stresses Drive Seismicity Along a Major Ross Ice Shelf Rift

Olinger

Lipovsky

Wiens

et al. 2019

Geophysical Research Letters

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Understanding deformation in ice shelves is necessary to evaluate the response of ice shelves to thinning. We study microseismicity associated with ice shelf deformation using nine broadband seismographs deployed near a rift on the Ross Ice Shelf. From December 2014 to November 2016, we detect 5,948 icequakes generated by rift deformation. Locations were determined for 2,515 events using a least squares grid‐search and double‐difference algorithms. Ocean swell, infragravity waves, and a significant tsunami arrival do not affect seismicity. Instead, seismicity correlates with tidal phase on diurnal time scales and inversely correlates with air temperature on multiday and seasonal time scales. Spatial variability in tidal elevation tilts the ice shelf, and seismicity is concentrated while the shelf slopes downward toward the ice front. During especially cold periods, thermal stress and embrittlement enhance fracture along the rift. We propose that thermal stress and tidally driven gravitational stress produce rift seismicity with peak activity in the winter.

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Section: Temperature Controls Multiday and Seasonal Patterns In Seismsupporting

confidence: 78%

Tidal and Thermal Stresses Drive Seismicity Along a Major Ross Ice Shelf Rift

Olinger

Lipovsky

Wiens

et al. 2019

Geophysical Research Letters

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“…Overall, Figure 3. Comparison of the evolution of the thermal conductivity with density between (a) our computations at −20 • C and the data of Giese and Hawley (2015) and Marchenko et al (2019), and (b) our computations at −3 • C and estimates from the commonly used parameterizations described in Table 1, the SC model, as well as equation (5). The bulk thermal diffusivity provided by Giese and Hawley (2015) (25 m 2 /year) was converted in terms of thermal conductivity (0.48 W·m −1 ·K −1 ) using a bulk density of 425 kg/m 3 and a density-dependent specific heat capacity at −30 • C of 1,412 J·kg −1 ·K −1 .…”

Section: Comparison With Predictive Formulas 351 Estimates At −3 • Cmentioning

confidence: 99%

Thermal Conductivity of Snow, Firn, and Porous Ice From 3‐D Image‐Based Computations

Calonne

Milliancourt

Burr

et al. 2019

Geophysical Research Letters

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Estimating thermal conductivity of snow, firn, and porous ice is key for modeling the thermal regime of alpine and polar glaciers. Whereas thermal conductivity of snow was widely investigated, studies on firn and porous ice are very scarce. This study presents the effective thermal conductivity tensor computed from 64 3‐D images of microstructures of snow, antarctic firn, and porous ice at −3, −20, and −60°C. We show that, in contrast with snow, conductivity of firn and porous ice correlates linearly with density, is approximately isotropic, and is largely impacted by temperature. We report that performances of commonly used estimates of thermal conductivity vary largely with density. In particular, formulas designed for snow lead to significant underestimations when applied to denser ice structures. We present a new formulation to accurately estimate the thermal conductivity throughout the whole density range, from fresh snow to bubbly ice, and for any temperature conditions encountered in glaciers.

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“…We can estimate the diffusive e-folding timescale τ to 200 m depth for the temperature perturbation by nondimensionalizing the heat equation: τ ≈ z 2 /κ. Approximating the thermal diffusivity of firn κ ¼ 8 × 10 À7 m 2 s À1 (Giese and Hawley, 2015):…”

Section: Temperature Variabilitymentioning

confidence: 99%

Firn Model Intercomparison Experiment (FirnMICE)

et al. 2017

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ABSTRACT. Evolution of cold dry snow and firn plays important roles in glaciology; however, the physical formulation of a densification law is still an active research topic. We forced eight firn-densification models and one seasonal-snow model in six different experiments by imposing step changes in temperature and accumulation-rate boundary conditions; all of the boundary conditions were chosen to simulate firn densification in cold, dry environments. While the intended application of the participating models varies, they are describing the same physical system and should in principle yield the same solutions. The firn models all produce plausible depth-density profiles, but the model outputs in both steady state and transient modes differ for quantities that are of interest in ice core and altimetry research. These differences demonstrate that firn-densification models are incorrectly or incompletely representing physical processes. We quantitatively characterize the differences among the results from the various models. For example, we find depth-integrated porosity is unlikely to be inferred with confidence from a firn model to better than 2 m in steady state at a specific site with known accumulation rate and temperature. Firn Model Intercomparison Experiment can provide a benchmark of results for future models, provide a basis to quantify model uncertainties and guide future directions of firn-densification modeling.

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Reconstructing thermal properties of firn at Summit, Greenland, from a temperature profile time series

Cited by 14 publications

References 43 publications

Tidal and Thermal Stresses Drive Seismicity Along a Major Ross Ice Shelf Rift

Tidal and Thermal Stresses Drive Seismicity Along a Major Ross Ice Shelf Rift

Thermal Conductivity of Snow, Firn, and Porous Ice From 3‐D Image‐Based Computations

Firn Model Intercomparison Experiment (FirnMICE)

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