Pore morphology of polar firn around closure revealed by X-ray tomography

Abstract

Abstract. Understanding the slow densification process of polar firn into ice is essential in order to constrain the age difference between the ice matrix and entrapped gases. The progressive microstructure evolution of the firn column with depth leads to pore closure and gas entrapment. Air transport models in the firn usually include a closed porosity profile based on available data. Pycnometry or melting-refreezing techniques have been used to obtain the ratio of closed to total porosity and air content in closed pores, respectively. X-ray computed tomography is complementary to these methods, as it enables to obtain the full 5 pore network in 3D. This study takes advantage of this non-destructive technique to discuss the morphological evolution of pores on four different Antarctic sites. The computation of refined geometrical parameters for the very cold polar sites Dome C and Lock In (the two Antarctic plateau sites studied here) provides new information that could be used in further studies. The comparison of these two sites shows a more tortuous pore network at Lock In than at Dome C which should result in older gas ages in deep firn. A comprehensive estimation of the different errors related to X-ray tomography and to the sample variability 10 has been performed. The procedure described here may be used as a guideline for further experimental characterization on firn samples. We show that the closed to total porosity ratio, which is classically used for the detection of pore closure, is strongly affected by the sample size, the image reconstruction and by spatial heterogeneities. In this work, we introduce an alternative parameter, the connectivity index, which is practically independent on sample size and image acquisition conditions, and that accurately predicts the close-off depth and density. Its strength also lies in its simple computation, without any assumption on 15 the pore status (open or close). The close-off prediction is obtained for Dome C and Lock In, without any further numerical simulations on images (e.g. by permeability or diffusivity calculations).

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

“…This study is based on a set of 64 3‐D images that includes 37 images of snow samples and 27 images of firn and porous ice samples, all from previous studies. Firn samples are subsamples of Antarctic ice cores from three locations: Dome C, near Concordia Station (75°6 ′ S, 123°21 ′ E); Lock In, located at 136 km away from Concordia Station (74°8.310 ′ S, 126°9.510 ′ E); and Vostok, obtained during different previous expeditions (Burr et al, ; Coléou & Barnola, ; Gautier et al, ). They were extracted at depths ranging from 23 to 133 m, covering different levels of densification until the close‐off.…”

“…A linear correlation between density and conductivity is found but comes with a large scatter, which is attributed to measurement errors (Marchenko et al, ). The microstructure of firn and porous ice can be noticeably different at a given density because of the different thermomechanical constraints they underwent (Burr et al, , ; Lomonaco et al, ). Its influence was however never investigated.…”

Diffusivity and Solubility of H2 in Ice Ih: Implications for the Behavior of H2 in Polar Ice

“…The geometry assumed in this calculation is highly oversimplified. In reality, the open pores are a complex web‐like network, making it challenging to determine the average distance between closed bubbles and open pores (Burr et al., 2018, Figure 7). Images obtained from X‐ray tomography of firn (Figure 7) could be used to develop more refined calculations of equilibration times for pore close‐off fractionation.…”

“…Reproduced with permission from Burr et al. (2018).…”

Porosity dependence of elastic moduli of snow and firn

“…This allows the relation between the computed elastic properties and parameters characterizing the microstructure such as porosity, the ratio of closed to total porosity, pore connectivity, pore surface-to-volume ratio and structure model index to be examined (e.g. Kaempfer and Schneebeli, 2007; Ohser and others, 2009; Wang and Baker, 2013; Gregory and others, 2014; Burr and others, 2018; Fourteau and others, 2019). For example, Srivastava and others (2010) calculated the elastic properties of snow from microtomography using a voxel-based finite element technique, and compared the results with several microstructural parameters, the best correlation being with ice volume fraction.…”