Abstract. In recent decades, rapid ice shelf disintegration along the Antarctic Peninsula has had a global impact through enhancing outlet glacier flow and hence sea level rise and the freshening of Antarctic Bottom Water. Ice shelf thinning due to basal melting results from the circulation of relatively warm water in the underlying ocean cavity. However, the effect of sub-shelf circulation on future ice shelf stability cannot be predicted accurately with computer simulations if the geometry of the ice shelf cavity is unknown. To address this deficit for Larsen C Ice Shelf, West Antarctica, we integrate new water column thickness measurements from recent seismic campaigns with existing observations. We present these new data here along with an updated bathymetry grid of the ocean cavity. Key findings include a relatively deep seabed to the southeast of the Kenyon Peninsula, along the grounding line and around the key ice shelf pinning-point of Bawden Ice Rise. In addition, we can confirm that the cavity's southern trough stretches from Mobiloil Inlet to the open ocean. These areas of deep seabed will influence ocean circulation and tidal mixing and will therefore affect the basal-melt distribution. These results will help constrain models of ice shelf cavity circulation with the aim of improving our understanding of sub-shelf processes and their potential influence on ice shelf stability. The datasets are comprised of all the new point measurements of seabed depth. We present the new depth measurements here, as well as a compilation of previously published measurements. To demonstrate the improvements to the sub-shelf bathymetry map that these new data provide we include a gridded data product in the Supplement of this paper, derived using the additional measurements of both offshore seabed depth and the thickness of grounded ice. The underlying seismic datasets that were used to determine bed depth and ice thickness are available at https://doi.org/10.5285/315740B1-A7B9-4CF0-9521-86F046E33E9A (Brisbourne et al., 2019), https://doi.org/10.5285/5D63777D-B375-4791-918F-9A5527093298 (Booth, 2019), https://doi.org/10.5285/FFF8AFEE-4978-495E-9210-120872983A8D (Kulessa and Bevan, 2019) and https://doi.org/10.5285/147BAF64-B9AF-4A97-8091-26AEC0D3C0BB (Booth et al., 2019).

The density structure of firn has implications for hydrological and climate modelling and for ice shelf stability. The firn structure can be evaluated from depth models of seismic velocity, widely obtained with Herglotz-Wiechert inversion (HWI), an approach that considers the slowness of refracted seismic arrivals. However, HWI is appropriate only for steady-state firn profiles and the inversion accuracy can be compromised where firn contains ice layers. In these cases, Full Waveform Inversion (FWI) can be more successful than HWI. FWI extends HWI capabilities by considering the full seismic waveform and incorporates reflected arrivals, thus offering a more accurate estimate of a velocity profile. We show the FWI characterisation of the velocity model has an error of only 1.7% for regions (vs. 4.2% with HWI) with an ice slab (20 m thick, 40 m deep) in an otherwise steady-state firn profile.

The density structure of firn has implications for hydrological and climate modelling, and ice-shelf stability. The structure of firn can be evaluated from depth models of seismic velocity, widely obtained with Herglotz–Wiechert inversion (HWI), an approach that considers the slowness of refracted seismic arrivals. However, HWI is strictly appropriate only for steady-state firn profiles and the inversion accuracy can be compromised where firn contains ice layers. In these cases, full waveform inversion (FWI) may yield more success than HWI. FWI extends HWI capabilities by considering the full seismic waveform and incorporates reflected arrivals. Using synthetic firn density profiles, assuming both steady- and non-steady-state accumulation, we show that FWI outperforms HWI for detecting ice slab boundaries (5–80 m thick, 5–80 m deep) and velocity anomalies within firn. FWI can detect slabs thicker than one wavelength (here, 20 m, assuming a maximum frequency of 60 Hz) but requires the starting velocity model to be accurate to ±2.5%. We recommend for field practice that the shallowest layers of velocity models are constrained with ground-truth data. Nonetheless, FWI shows advantages over established methods, and should be considered when the characterisation of firn ice slabs is the goal of the seismic survey.

<p>Full Waveform Inversion (FWI) is a well-established seismic imaging technique used in the exploration industry to acquire high resolution, high precision velocity models of the subsurface from seismic data. Although FWI is computationally expensive and requires customized data acquisition, the technique has the potential to improve subsurface glaciological imaging.</p><p>Firn is formed as an intermediate material (of density ~400 – 810 kg m<sup>-3</sup>) as snow is compressed into ice (~810 – 917 kg m<sup>-3</sup>). Variations in surface conditions and periods of surface melting commonly lead to the presence of discrete layers and lenses of refrozen (‘infiltration’) ice within the firn column; layers that can be from millimetres to several tens of metres thick. Therefore, firn characteristics provide a tool for reconstructing climate conditions relating to the amount of snow accumulation, melt, temperature conditions and subsequent snow preservation. Given the complexity of these relationships, it has not been possible to develop a theoretical model that predicts accurately variations in firn properties or density with depth. Consequently, seismic techniques, which are logistically less demanding than extracting firn cores, are typically used to reconstruct these physical properties of the firn column.</p><p>Firn seismic velocity is often derived from seismic data using the Herglotz-Wiechert (HW) inversion. A velocity trend would be expected to increase from ~400 m s<sup>-1</sup> in snow through to ~3,800 m s<sup>-1</sup> in ice. Thus, the presence of infiltration ice within the firn column results in anomalously high velocity intervals at shallow depths. HW inversion can be limited by the accuracy of first-break picking (specifically in the near offset, where a small error in the travel time pick gives the greatest variability to the HW velocity output), and it cannot recover the velocity inversion below a refrozen ice layer without elastodynamic redatumming. Importantly, FWI has the capacity to mitigate issues such as these, and thereby potentially offers a new standard for glaciological seismic modelling.</p><p>Using seismic datasets obtained from Pine Island Glacier, Antarctica, and synthetic data that simulate firn columns that include substantial thicknesses of infiltration ice (‘ice slabs’, up to 100 m thick and from 5-80 m deep), we show how FWI improves on current seismic techniques in terms of identifying the velocity variations associated with both included ice layers and the firn underlying them. We present a best practice methodology for the use of FWI with glaciological data, including (i) the extraction of a source wavelet from the data for the use with modelling, (ii) the steps needed to ensure a consistent waveform, (iii) the appropriate offset-to-depth ratio, and (iv) the requirement of a constraint for the uppermost part of the velocity model. Finally, we evaluate the robustness of the FWI approach by comparing it with well-established HW methods for building velocity models.</p>

<p>The transformation of snow into ice is a fundamental process in glaciology. The yearly accumulation of fresh snowfall increases the overburden pressure, changing the snow’s properties such that it transitions into firn and pure glacier ice thereafter. Additionally, periods of melt and variations in subsurface and surface conditions can lead to the presence of ice layers and firn aquifers within the firn column. Therefore, firn characteristics provide a tool for evaluating past and present climate conditions relating to the amount of snow accumulation, melt, temperature conditions and the subsequent preservation of the snow. <br><br></p><p>Due to the importance of relationships between firn and other glaciological processes (e.g., settling, sublimation, recrystallization and other deformation processes) it has not been possible to develop a theoretically-based model which accurately predicts firn properties with depth. Therefore, methods of measuring firn are either intrusive or rely on (potentially unreliable) empirical conversions. Full Waveform Inversion (FWI) may offer a new standard for glaciological seismic modelling, mitigating issues within current seismic modelling techniques and paving the way for the recovery of elastic properties, including density. Constraining firn properties also leads to improved corrections for deeper seismic responses, e.g. glacier bed reflectivity.</p><p> </p><p>Using seismic datasets obtained from Norway’s Hardangerjøkulen Ice Cap (60.47°N, 7.49°W) along with varying synthetic firn column scenarios (introducing the presence of ice lenses and firn aquifers), we show how FWI can mitigate the dependence on intrusive techniques and empirical relationships. Furthermore, we compare the robustness of the FWI approaches versus traditional glaciological approaches to velocity model building (Herglotz-Wiechert inversion).</p><p> </p>