Hostname: page-component-89b8bd64d-46n74 Total loading time: 0 Render date: 2026-05-09T03:00:51.716Z Has data issue: false hasContentIssue false

Paths forward in radioglaciology

Published online by Cambridge University Press:  09 March 2023

Dustin M. Schroeder*
Affiliation:
Departments of Geophysics and of Electrical Engineering, Stanford University, Stanford, CA, USA
*
Author for correspondence: Dustin M. Schroeder, E-mail: dustin.m.schroeder@stanford.edu
Rights & Permissions [Opens in a new window]

Abstract

Ice-penetrating radar sounding is a powerful geophysical tool for studying terrestrial and planetary ice with a rich glaciological heritage reaching back over half a century. Recent years have also seen rapid growth in both the radioglaciological community itself and in the scope and sophistication of its analysis of ice-penetrating radar data. This has been spurred by a combination of growing datasets and improvements in computational resources as well as advances in radar sounding instrumentation and platforms. Together, these developments are transforming the field and highlight exciting paths forward for future innovation and investigation.

Information

Type
Letter
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The International Glaciological Society
Figure 0

Fig. 1. Advances in the analysis of ice-penetrating radar data have demonstrated the capacity to interpret signatures of radar scattering, reflection, attenuation and reflectivity to observe a growing range of near-surface, englacial and subglacial processes.

Figure 1

Fig. 2. Developments in instruments and platforms are enabling radioglaciology to transition from a relatively data poor field typified by sparse profiles and point measurement to field richer spatial, temporal, geometric and signal coverage.