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Abstract Subglacial lakes have been mapped across Antarctica with two methods, radio‐echo sounding (RES) and ice‐surface deformation. At sites where both are coincident, these methods typically provide conflicting interpretations about the ice‐bed interface. With a single exception,activesubglacial lakes identified by surface deformation do not display the expected flat, bright, and specular bed reflection in RES data, characteristic ofnon‐activelakes. This observational conundrum suggests that our understanding of Antarctic subglacial hydrology, especially beneath important fast‐moving ice streams, remains incomplete. Here, we use an airborne RES campaign that surveyed a well‐characterized group of active subglacial lakes on lower Mercer and Whillans ice streams, West Antarctica, to explore inconsistency between the two observational techniques. We test hypotheses of increased scattering and attenuation due to the presence of an active subglacial lake system that could suppress reflected bed‐echo power for RES observations in these locations, finding that entrained water is most plausible. 

Dielectric anisotropy in ice alters the propagation of polarized radio waves, so polarimetric radar sounding can be used to survey anisotropic properties of ice masses. Ice anisotropy is either intrinsic, associated with ice‐crystal orientation fabric (COF), or extrinsic, associated with material heterogeneity, such as bubbles, fractures, and directional roughness at the glacier bed. Anisotropy develops through a history of snow deposition and ice flow, and the consequent mechanical properties of anisotropy then feed back to influence ice flow. Constraints on anisotropy are therefore important for understanding ice dynamics, ice‐sheet history, and future projections of ice flow and associated sea‐level change. Radar techniques, applied using ground‐based, airborne, or spaceborne instruments, can be deployed more quickly and over a larger area than either direct sampling, via ice‐core drilling, or analogous seismic techniques. Here, we review the physical nature of dielectric anisotropy in glacier ice, the general theory for radio‐wave propagation through anisotropic media, polarimetric radar instruments and survey strategies, and the extent of applications in glacier settings. We close by discussing future directions, such as polarimetric interpretations outside COF, planetary and astrophysical applications, innovative survey geometries, and polarimetric profiling. We argue that the recent proliferation in polarimetric subsurface sounding radar marks a critical inflection, since there are now several approaches for data collection and processing. This review aims to guide the expanding polarimetric user base to appropriate techniques so they can address new and existing challenges in glaciology, such as constraining ice viscosity, a critical control on ice flow and future sea‐level change. 

Radio-echo sounding (RES) has revealed an internal architecture within both the West and East Antarctic ice sheets that records their depositional, deformational and melting histories. Crucially, RES-imaged internal-reflecting horizons, tied to ice-core age–depth profiles, can be treated as isochrones that record the age–depth structure across the Antarctic ice sheets. These enable the reconstruction of past climate and ice dynamical processes on large scales, which are complementary to but more spatially extensive than commonly used proxy records (e.g. former ice limits constrained by cosmogenic dating or offshore sediment sequences) around Antarctica. We review the progress towards building a pan-Antarctic age–depth model from these data by first introducing the relevant RES datasets that have been acquired across Antarctica over the last 6 decades (focussing specifically on those that detected internal-reflecting horizons) and outlining the processing steps typically undertaken to visualise, trace and date (by intersection with ice cores or modelling) the RES-imaged isochrones. We summarise the scientific applications for which Antarctica's internal architecture has been used to date and present a pathway to expanding Antarctic radiostratigraphy across the continent to provide a benchmark for a wider range of investigations: (1) identification of optimal sites for retrieving new ice-core palaeoclimate records targeting different periods; (2) reconstruction of surface mass balance on millennial or historical timescales; (3) estimation of basal melting and geothermal heat flux from radiostratigraphy and comprehensive mapping of basal-ice units to complement inferences from other geophysical and geological methods; (4) advancement of the knowledge of volcanic activity and fallout across Antarctica; and (5) refinement of numerical models that leverage radiostratigraphy to tune time-varying accumulation, basal melting and ice flow, firstly to reconstruct past behaviour and then to reduce uncertainties in projecting future ice-sheet behaviour. 

Some notation changes to go with the community notation decided in the review article. Some Jupyter notebooks to reproduce figures in the article. 

{"Abstract":["This is an extracted data product for radar bed reflectivity from Whillans Ice Plain, West Antarctica. The original data are hosted by the Center for Remote Sensing of Ice Sheets (CReSIS; see associated citation below). The files here can be recalculate and are meant to be used within a set of computational notebooks here:https://doi.org/10.5281/zenodo.10859135\n\nThere are two csv files included here, each structured as a Pandas dataframe. You can load them in Python like:df = pd.read_csv('./Picked_Bed_Power.csv')\n\nThe first file, 'Picked_Bed_Power.csv' is the raw, uncorrected power from the radar image at the bed pick provided by CReSIS. There are also other useful variables for georeferencing, flight attributes, etc.\n\nThe second file, 'Processed_Reflectivity.csv' is processed from the first file. Processing includes: 1) a spreading correction; 2) an attenuation correction; and, 3) a power adjustment flight days based on compared power at crossover points. This file also has identifiers for regions including "grounded ice", "ungrounded ice", and "subglacial lakes"."]} 

Full version published with manuscript