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For more than 20 years, X-ray microtomography (µCT) has been extensively used to study dry snow (see e.g. [1, 2]). However, imaging of wet snow still resists the µCT approach for several reasons: (1) the low absorption contrast between ice and liquid water, (2) the difficulty of regulating temperature at 0 °C and (3) some very rapid processes that may occur during ice melting and water percolation. Despite multiple attempts to provide tomographic images of wet snow, the literature studies only report refrozen states [3, 4] or indirect evaluations by difference imaging.
We recently carried out several experiments that solved most of the problems mentioned above: using a specifically modified version of our cold stage CellStat [5], we were able to obtain relatively well thermalized samples at 0 °C, allowing to stabilize the ice-water interfaces for µCT acquisitions. A low energy approach using the 3SR laboratory tomograph was first used to provide snow images where the evolution of air, ice and liquid water can be detected at a voxel size of 5 to 8 µm. More recently, synchrotron tomography at ANATOMIX beamline provided much higher quality image series at the resolution of 3 µm using phase contrast tomography. In particular, segmented images showing the 3 phases can be obtained, giving access to the mean curvature field information of the interfaces [6]. Such results open new outlooks for the study of wet snow.
| References | 1) C. Coleou, B. Lesaffre, J.-B. Brzoska, W. Ludwig & E. Boller, 2001. Ann. Glaciol., 32, 75-81, https://doi.org/10.3189/172756401781819418. 2) S. Chen & I. Baker, 2010. J. Geophys. Res., 115, D21114, https://doi.org/10.1029/2010JD014. 3) F. Flin, B. Lesaffre, A. Dufour, L. Gillibert, A. Hasan, S. Rolland du Roscoat, S. Cabanes & P. Pugliese, 2011. Physics and Chemistry of Ice, 321-328, https://frederic-flin.github.io/pdf/flin_2011_ssa_sgca.pdf. 4) F. Avanzi, G. Petrucci, M. Matzl, M. Schneebeli & C. de Michele, 2017. Water Resour. Res., 53, 3713– 3729, https://doi.org/10.1002/2016WR019502. 5) A. Zennoune, P. Latil, F. Flin, J. Perrin, T. Weitkamp, M. Scheel, C. Geindreau, H. Benkhelifa & F.-T. Ndoye, 2022. Food Res. Int., 162(B), 112116, https://doi.org/10.1016/j.foodres.2022.112116. 6) Flin, F., J.-B. Brzoska, B. Lesaffre, C. Coléou & R. A. Pieritz, 2004. Ann. Glaciol., 38, 39-44, https://doi.org/10.3189/172756404781814942. ================================================================================== Acknowledgements: This research has been supported by the Agence Nationale de la Recherche through the MiMESis-3D ANR project (ANR-19-CE01-0009). We acknowledge SOLEIL for provision of synchrotron radiation facilities and financial support concerning the proposal 20220628, achieved on the ANATOMIX beamline. ANATOMIX is an Equipment of Excellence (EQUIPEX) funded by the Investments for the Future program of the ANR, project NanoimagesX, grant no. ANR-11-EQPX-0031. We also thank the tomographic service of the 3S-R laboratory, where several 3D images have been obtained. The 3SR lab is part of the Labex Tec 21 (Investissements d’Avenir, grant ANR-11-LABX-0030). CNRM/CEN is part of Labex OSUG@2020 (Investissements d’Avenir, grant ANR-10-LABX-0056). Special thanks are addressed to G. Daniel, A. Denis, L. Pezard, and J. Roulle for their technical support during the experiments. |
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| Country | France |
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