Supplementary material for "Passive Seismology for Investigating the Ice-Bedrock Interface Zone of East Antarctica"

Supplementary Material for Chapter 3: Determining the character of subglacial sediments in the ice-bedrock interface zone of Antarctica using horizontal-to-vertical spectral ratios (HVSRs) of seismic ambient noise This document contains the supplementary material for Chapter 3, including: •Texts S3.1 to S3.7; •Tables S3.1 to S3.3; •Figures S3.1 to S3.26. Text S3.1: HVSR data processing For each station selected in our study, we compute HVSRs over 5-day time series with (nonoverlapping) window lengths of 600 s. Each window is linearly detrended, filtered using a Butterworth bandpass filter between 0.01–9 Hz, and tapered using a cosine taper with 5% width. The component spectra for each window are then separately computed, with the horizontalcomponent spectra averaged via the standard geometric mean (Molnar et al., 2022). Spectral smoothing (Konno and Ohmachi, 1998) is subsequently applied with a bandwidth coefficient b= 40 (Cox et al., 2020), before HVSRs are computed for each window and resampled between 0.05– 3 Hz, producing a median HVSR for each 5-day time series. We note that instrument response removal is not performed nor required, with the component instrument responses identical within the frequencies considered. This processing workflow is largely in keeping with Yan et al. (2018), with the exceptions of the non-overlapping windows (which are not considered necessary for the relatively long time series available), the use of the standard Konno-Ohmachi function for spectral smoothing (Molnar et al., 2022) rather than a Hanning window, and the increase in the resampled frequency range from 0.1–2 Hz (in order to extend interpretations, particularly regarding the loss of the fundamental peak to incoherencies <0.1 Hz). 1 The key difference to Yan et al. (2018) is our use of the hvsrpy software package to perform HVSR processing (Vantassel, 2025) and the frequency-domain window rejection algorithm provided (Cox et al., 2020). This window rejection algorithm is preferred over traditional STA/LTA anti-triggering (Wathelet et al., 2020), which requires a subjective choice in STA/LTA parameters, primarily excludes windows containing non-stationary events (which can provide constructive energies to HVSRs if in the far field; Dal Moro and Panza, 2022; Parolai and Galiana-Merino, 2006; Parolai et al., 2009), and is unsuited for the long windows required for kilometer-scale investigation depths (i.e., longer windows are more likely to contain non-stationary events and be rejected). In comparison, hvsrpy iteratively rejects windows in the frequency domain based purely on the lognormal statistics of a selected HVSR peak (Cox et al., 2020) and thus isolates noise energies (regardless of source type or mechanism) that have propagated through the subsurface and generate a consistent HVSR of structural origin. For most stations analyzed in this study, a clear and consistent peak is observed and used to define the window rejection statistics, with the number of standard deviations and maximum iterations set to 2 and 50, respectively. We find that few windows are rejected in most cases, as Antarctic HVSRs are extremely stable in the frequency domain except when instrumental issues or local fieldwork noise are present, which can be clearly identified in the time series (Section 3.3.2). We therefore do not apply window rejection at stations where no clear or consistent peaks can be discerned, allowing an assessment of subsurface factors influencing HVSR variability (Section 3.4.1). To reproduce the HVSRs at stations GM01, N052 and ST06 in Fig. 3.2 as faithfully as possible to Yan et al. (2018), we readjust the resampling bandwidth to 0.1–2 Hz and manually select 5-day time series in the austral summer season that generate HVSRs with amplitudes and shapes roughly congruent to those displayed in Yan et al. (2018) (who do not consider temporal HVSR variability and therefore do not specify the time periods their analyzed time series were selected from). For these stations, we find that the different window rejection scheme results in negligible differences in the median HVSR and corresponding peak frequencies (i.e., <0.01 Hz). We opt against displaying standard deviations in the HVSR peak frequencies compared to Yan et al. (2018). This is aptly explained by Cox et al. (2020): simply, that the standard deviation (derived from the set of fundamental peak frequencies from each accepted window in the HVSR calculation) does not represent the statistics of the fundamental peak frequency relating to the median HVSR curve. Text S3.2: Choice of the BW forward model to exemplify HVSR behavior for the IBIZ Here, we fully detail the numerical limitations with characterizing higher SW modes in the algorithms provided by Albarello et al. (2023) when a low-velocity zone is introduced, the solutions provided by updated implementations of these forward models, and our choice in this study to use the BW forward model to represent wavefield-independent, multi-mode HVSR peak behavior for the IBIZ. Fig. S3.1b–g displays modal RWE behavior for the fundamental, firstand second-higher modes for several shallow ice scenarios including an unlithified sediments layer. For all modes, strong numerical irregularities emerge at high frequencies when a low-velocity zone is introduced, scaling in magnitude and influence into lower frequencies as layer thickness increases and VS 2 tends to zero. As mentioned in Section 3.3.1, these irregularities can be related to the modal summation calculation and the root search used in the underlying dispersion curve calculation to distinguish modal SW branches (Wathelet, 2005, 2008). By computing the corresponding multi-modal dispersion curves for the same subsurface profiles, we see that the numerical irregularities emerge at frequencies at which modal osculation occurs (Boaga et al., 2013); that is, where modal branches appear to converge. Modal osculation is a common feature in SW dispersion curves when low-velocity zones are present (e.g., Dou and Ajo-Franklin, 2014; Mi et al., 2018), and indicates the transition of dominant energy propagation to higher modes as frequency increases. Anomalous peaks also emerge for higher-modal RWE below the osculation frequency, but do not appear to be features of subsurface origin. The standard interpretation of fmod 0from RWE (R0) nevertheless remains valid, aligning consistently with the corresponding fundamental peak from the BW-modeled HVSR, although noting that the RWE (R0) peak becomes less well defined as the subglacial layer VSdecreases. In the absence of these limitations attributed to modal summation, we suggest that peaks in higher-modal RWE can be expected to also align with higher-mode peaks in the BW-modeled HVSRs. This is supported by Fig. 4 of Bonnefoy-Claudet et al. (2008) for the normally dispersive ‘M2.2’ soil profile. We additionally simulate modal RWE for this profile and vary the surface soil layer hsfrom the original 25 m to 500 m (Fig. S3.1a), similarly observing clear, well-defined peaks in all modal RWE that strongly correspond in frequency with HVSR peaks from the BW model, independent of hs. Moreover, comparing this scenario with the ice-bed scenarios (Fig. S3.1b–g) clarifies that the generally weak amplitudes seen for the latter scenarios can be attributed to the unique impedance contrast defined by the ice and underlying substrate, and explains the failure in performing RWE inversion for the thicker ice sites studied by Picotti et al. (2017). We also evaluate synthetic HVSRs from the DFA and DSS models for the same set of IBIZ scenarios as above (Fig. S3.2) and furthermore isolate different wavefield components (Table S3.1). The higher-frequency numerical irregularities are also prevalent in the DFA algorithm and the SW implementation of the DSS model, occurring at the same osculation frequencies identified by the multi-modal dispersion curves (Fig. S3.1). Similar issues with determining higher SW modes in the respective formalizations are therefore present (García-Jerez et al., 2016; Lunedei and Albarello, 2010). In contrast, the FW implementation of the DFA model (Lunedei and Albarello, 2015) appears to be well behaved across all frequencies and exhibits higher-mode peaks that align both in frequency and shape with corresponding peaks from the BW model. The DSS models are limited in their sampling frequency however, and are therefore not suited to resolve low-frequency HVSRs; moreover, the attenuation parameterization causes higher-mode peaks to dampen rapidly and non-linearly with hl, hindering the interpretation of such features for the ice sheet thicknesses considered in our forward modeling. We note that higher-mode peaks of low amplitude can additionally be seen from the DFA model at frequencies below the numerical irregularities, which also align in frequency with the higher-mode peaks predicted by the DSS and BW models (Fig. S3.2). Isolating the wavefield components in the FW models additionally indicates that Love waves provide the primary energy contribution to HVSRs (Fig. S3.2), with the inclusion of BWs having minimal effect on peak amplitudes and Rayleigh-wave contributions closely approximating the RWE (Fig. S3.1). This is in agreement with previous findings (Albarello et al., 2023; Arai and 3 Tokimatsu, 2004; Bonnefoy-Claudet et al., 2008) and encourages the incorporation of Love-wave contributions in HVSR interpretations and inversions (Bonnefoy-Claudet et al., 2006; Endrun, 2011). It is important to underline that we are not concerned with the difference in synthetic HVSR peak amplitudes between the forward models, as these evidently vary with internal algorithm parameterizations, the choice in non-VSparameters (Figs. S3.3–S3.6), and other factors (e.g., number of SW modes included, method for combining horizontal components; Albarello et al., 2023), and therefore cannot be reliably interpreted to represent observed HVSR peak amplitudes (which additionally vary with, e.g., wavefield conditions, instrumentation, ground-sensor coupling; see Section 3.4.1). Only the HVSR peak frequencies can be considered a robust measure of subsurface VSstructure, as reflected in the underlying framework of resonance (Eq. 3.1), and the above evidence indicates that both higher-mode BW resonance and higher SW modes can explain higher-mode HVSR peaks. We therefore select the BW model to represent multi-modal HVSR behavior when a lowvelocity zone is present. In contrast to the other algorithms provided by Albarello et al. (2023), HVSRs from the BW model remains well behaved in all cases and across all frequencies, with both fundamental and higher-mode peaks that are clear and well defined. The FW implementation of the DSS model by Lunedei and Albarello (2015), or the updated implementation of the DFA model from Lontsi et al. (2019) using discrete wavenumber integration instead of modal summation, are equally valid choices for interpreting HVSR peak frequencies. However, the weaker amplitudes predicted in the higher-mode HVSR peaks provide a poorer visual correspondence to the higher-mode peaks in the observed HVSRs (e.g., Fig. S3.21); moreover, the BW model is more computationally simple and efficient. Nevertheless, we still check the consistency in HVSR behavior from the BW model against the fundamental-mode RWE and FW descriptions of the DFA and DSS models in the below supplementary plots in order to examine any wavefield dependency for HVSR peak frequency behavior. Text S3.3: Choice of forward modeling parameters for simple-case scenarios Here, we fully outline all parameter values selected for our simple-case scenarios for 1-D forward modeling and justify their choice to approximate the Antarctic IBIZ, summarized in Table S3.2. This is supported by parameter sensitivity tests for a representative 1000 m-thick ice sheet layer, where VP,ρ,QSand QPare isolated and varied within realistic bounds in the ice, subglacial layers and basement half-space (Figs. S3.3–S3.7). Note as in the main text, model parameters associated with the ice, subglacial layers and basement half-space are correspondingly denoted by subscript Xi,Xland Xb. Ice sheet For all profiles, a single, uniform ice sheet layer is set at the surface with varying thickness hi of [500, 1000, 2000, 3000] m to capture the major distribution of ice sheet thicknesses across the grounded portions of the AIS (Fretwell et al., 2013; Morlighem et al., 2020; Pritchard et al., 2025). Thinner ice areas are present on coastal highlands but are not considered for computational expediency and a higher priority on evaluating HVSR sensitivity for thicker 4 ice regions, which are more likely to overlie substantial packages of subglacial material (i.e., subglacial sedimentary basins; Aitken et al., 2023). Seismic velocities of VP,i = 3870 m/s and VS,i = 1900 m/s are taken, aligning with typical values assumed by passive seismic investigations in Antarctica and Greenland (Chai et al., 2017; Chaput et al., 2014; Dunham et al., 2020; Pha .m and Tkalčić, 2018; Walter et al., 2014; Yan et al., 2018; Yan et al., 2020; Zhou et al., 2022). Fixed values are validated by multi-variate knowledge from active seismic measurements (e.g., Anandakrishnan et al., 1998; Kohnen, 1974; Peters et al., 2008; Peters et al., 2006; Picotti et al., 2015; Robinson, 1968), borehole logging and ice core analysis (e.g., Bennett, 1968; Bentley, 1972; Diez and Eisen, 2015; Gow and Kohnen, 1979; Gusmeroli et al., 2012; Kerch et al., 2018) and other observations (e.g., distributed acoustic sensing; Booth et al., 2020; Brisbourne et al., 2021; Lutz et al., 2022) that seismic velocity variations in polar ice are minimal and can be reasonably approximated within the ranges of 3800–4000 m/s (for VP,i) and 1800–2000 m/s (for VS,i). Similarly, we assume a standard density of ρi= 920 kg/m3for pure glacial ice (Cuffey and Paterson, 2010) and ignore the slight evolution with depth from the firn-ice transition (∼830 kg/m3) to the base of the ice sheet (917–923 kg/m3; Hollmann et al., 2021), considering the negligible influence of realistic ice density variations on the frequency-domain response of the synthetic HVSRs (Fig. S3.4). In contrast, constraints of seismic attenuation in ice are lacking, particularly for S-waves. Existing measurements of englacial Q-factors vary widely from ∼5 to >500 (Agnew et al., 2023; Peters et al., 2012, and references therein), attributable to differences in the analysis method, wave type and bandwidth, study region, and between laboratory and field settings. We assume values of QS,i = 20 and QP,i = 100, aligning with previous estimates and particularly with QS,i factors suggested in the polar ice sheets for low seismic frequencies (Jones et al., 2023; Toyokuni et al., 2021). A different choice in QP,i minimally affects HVSR peak amplitudes (Fig. S3.6) compared to QS,i, which strongly diminishes higher-mode peaks at low values (Fig. S3.5): we therefore err towards a low QS,i value to evaluate HVSR sensitivity under non-ideal, high-attenuation conditions. Subglacial geology In approaching a parameterization of the subglacial profile, we must first recognize the poor present knowledge of the crustal geology beneath the AIS. Geophysical observables primarily interpret long-wavelength structural features, such as subglacial sedimentary basins (Aitken et al., 2023; Li et al., 2022), large igneous intrusions (e.g., Aitken et al., 2014; Ferraccioli et al., 2009; Jordan et al., 2020; Smith et al., 2013), subglacial lakes (e.g., Livingstone et al., 2022) or distributions of dilatant till (e.g., Anandakrishnan, 2003; Brisbourne et al., 2017; Clyne et al., 2020; Kulessa et al., 2017; Luthra et al., 2016; Muto et al., 2019; Smith, 2007, 1997). Information from rock outcrops (Cox et al., 2023; Sanchez et al., 2021) are limited to ∼0.2% of the Antarctic surface (Burton-Johnson et al., 2016) and provide a biased data set towards crystalline highlands and older, uplifted sedimentary rocks (Aitken et al., 2023), whilst the current expenses of sub-ice drilling limits widespread application (Engelhardt et al., 1990; Smith et al., 2021). Offshore sampling (e.g., Gohl et al., 2017; Maritati et al., 2019; Thomson et al., 2013) enables access to younger sediments, but uncertainties in their source location limits relevance for characterizing subglacial geology (Aitken and Urosevic, 2021). The consequent ambiguity in crustal composition beneath the AIS is being recognized, for instance in the context of geothermal heat flow (Stål et al., 2024) and developments towards petrophysical 5 interpretations from regional geophysical data are being established (Li and Aitken, 2024; Lowe et al., 2024). However, geological heterogeneity over a continental scale is significant, and further complicated in Antarctica by the expected yet unresolved presence of subglacial groundwater (Christoffersen et al., 2014), permafrost (Dobiński et al., 2023) and gas hydrates (Ruppel, 2015), which can all significantly affect bulk seismic velocities and attenuation depending on their concentration (e.g., Dvorkin and Uden, 2004; Gei and Carcione, 2003; Johansen et al., 2003; Matsushima et al., 2014; Yun et al., 2005; Zimmerman and King, 1986). We therefore rely on standard rock physics measurements (Carmichael, 1982, 1984; Clark, 1966; Mavko et al., 2020; Schön, 2015; Telford et al., 1990; Toksöz and Johnston, 1981) to approximate reasonable VSranges and Q-factor values for unlithified sediments, sedimentary rocks and upper-crustal crystalline basement consistent with existing knowledge of the Antarctic IBIZ. These values naturally integrate the influences of lithology, pore fluid content and degree of freezing, although do not account for possible overburden pressure effects (King, 1966; Korneev and Glubokovskikh, 2013) or the presence of rock fractures (Berryman, 2007; Boadu and Long, 1996). VPand ρvalues are approximated from the corresponding VSusing the empirical approximations of Brocher (2005), justified by their lack of influence on the frequency-domain HVSR response, with the minor exception at extremely low layer densities (Figs. S3.3 and S3.4). Fixed Q-factors are similarly supported, although noting slight peak frequency shifts for low QS,l (Figs. S3.5 and S3.6). hlranges for the two separate scenarios of a single layer of unlithified sediments and sedimentary rocks are primarily guided by previous geophysical interpretations, as outlined below. Unlithified sediments hlis varied from 0 to 500 m; an extreme upper thickness bound when considering the meters-thick till layers mapped by active seismic measurements over fast-flowing glaciers (e.g., Anandakrishnan, 2003; Blankenship et al., 1986; Brisbourne et al., 2017), but rationalized by the suggestion of thick, low-velocity packages from receiver function studies (Anandakrishnan and Winberry, 2004; Chaput et al., 2014; Dunham et al., 2020; Walter et al., 2014) and the possibility of significant deposits being preserved in interior, marine-lying regions of the AIS (Jamieson et al., 2010; Paxman et al., 2019). We choose a wide range of VS,l values from 200 to 1800 m/s to incorporate all plausible conditions from fine-grained marine sediments (Hamilton, 1971) to completely frozen soils (Ji et al., 2024). A selection of QS,l =QP,l = 10 is made to simulate a low-attenuation, water-saturated environment, as similarly argued for the ice sheet layer. Sedimentary rocks In this case, hlis varied from 0 to 5000 m, representative of the kilometer-scale subglacial sedimentary basins in East Antarctica (Aitken et al., 2023). VS,l ranges from 1200 to 2800 m/s to accommodate varying lithological and hydrological conditions: the lower velocity limit approximates high-porosity, water-saturated sandstone, one of the most commonly exposed sedimentary rocks types (Cox et al., 2023; Sanchez et al., 2021) and a likely primary unit of the subglacial sedimentary basins (Aitken et al., 2023; Li et al., 2022); the upper bound is representative of drier and more consolidated rock types, such as limestone and siltstone. As with the unlithified sediments layer, relatively low Q-factors of QS,l =QP,l = 20 are chosen. 6 Crystalline basement VS,b for the half-space is set to 3000 m/s as a reasonable archetype of granite or gneiss which are commonly identified from Antarctic outcrops (Cox et al., 2023; Sanchez et al., 2021) and aligning with VSvalues mapped for the upper crust from regional SW inversion (Dunham et al., 2020; Dylan Mikesell et al., 2022; O’Donnell et al., 2019; Zhou et al., 2022). Changes in VS,b affect the defined impedance contrast and are therefore observed to primarily impact HVSR amplitudes (Figs S3.7a– c), supporting our choice of a fixed basement to investigate frequencydomain HVSR sensitivity. Relatively low values of QS,b =QP,b = 50 were assumed, as similarly rationalized for the overlying layers. Text S3.4: Choice of forward modeling parameters for complex-case scenarios Here, we fully outline all parameter values selected for our complex-case end-member scenarios for 1-D forward modeling and justify their choice to approximate realistic complexity in the Antarctic IBIZ. For all complex-case scenarios, hiis varied between [1000, 2000, 3000] m. Firn layer Only 1–2% of the glacial surface is exposed in Antarctica (Hui et al., 2014; Winther et al., 2001); all other areas are covered by snow and firn, the latter denoting the transitional stage of snow into glacial ice under overburden pressure and atmospheric forcing (Amory et al., 2024). The thickness of the firn layer, conventionally defined by the depth of the critical pore closeoff density of 830 kg/m3(Cuffey and Paterson, 2010), varies across Antarctica from a few meters along the ice sheet margins to >100 m within the cold and dry East Antarctic interior (Ligtenberg et al., 2011; van den Broeke, 2008; Veldhuijsen et al., 2023). In dry firn, viscoelastic properties increase monotonically with depth (Agnew et al., 2023; Albert, 1998; Diez et al., 2016; Hollmann et al., 2021; Picotti et al., 2024; Picotti et al., 2015; Schlegel et al., 2019), but the presence of ice slabs, meltwater and smaller-scale structural heterogeneities can introduce anomalies into the profile (Killingbeck et al., 2020; Montgomery et al., 2020; Pearce et al., 2023; Pearce et al., 2024). Spectral resonance in the Antarctic firn is observed at higher frequencies (>5 Hz) than considered in our study (Chaput et al., 2018; Chaput et al., 2022; Chaput et al., 2023); nevertheless, the deviation from the fixed ice sheet velocity profile we assume in our simple-case scenarios could potentially cause increased uncertainties when interpreting peak frequencies relative to f0, as similarly noted for receiver function interpretations of subglacial sediments from the phase arrival delay (Chaput et al., 2014). For this end-member scenario, we parameterize three different firn layers with h= 100 m at the surface of the ice sheet layer: (i) a monotonically-increasing profile with depth (discretized by 10 layers), with surface values of VS= 250 m/s, VP= 400 m/s, ρ= 350 kg/m3taken from the measurements of Schlegel et al. (2019), and QS=QP= 10; (ii) an inclusion into the firn layer of (i) of a 10 m-thick slab of glacial ice at 30 m depth, following Pearce et al. (2023); (iii) a single, uniform, low-VSfirn layer, as previously employed to interpret HVSR peaks from the Antarctic firn column (Lévêque et al., 2010), with properties assumed from the surficial values of the firn layer of (i). Each case is modeled for an ice-basement profile and including a 500 m7 thick subglacial layer of unlithified sediments with lower-bound elastic parameters (Table S3.2) and compared against synthetic HVSRs for a uniform ice sheet of corresponding ice thickness to assess the maximal possible influence of a firn layer on HVSR behavior. All other model parameters are kept as for the simple-case scenarios (Table S3.2). Basal ice Deeper variations in glacial ice are expected and could also challenge the reliability of assuming a uniform ice sheet layer for HVSR interpretations. Englacial seismic velocities are primarily affected by temperature and fabric anisotropy (Faria et al., 2014a, 2014b). A weakly inverse relationship exists for both VP,i and VS,i with englacial temperature (Gow and Kohnen, 1979; Kohnen, 1974), which typically evolves towards the pressure-melting point at the ice sheet base due to overburden pressure, basal friction and upwelling geothermal heat (Dawson et al., 2022; Dawson et al., 2024; McCormack et al., 2022). The ice fabric also develops with depth, generally described by a gradual transition from an isotropic distribution of randomly-oriented ice crystals to an anisotropic pattern under compression and flow-related deformation (Diez and Eisen, 2015; Gillet-Chaulet et al., 2006; Richards et al., 2022). This induces a similar evolution in seismic velocities with depth, although in varying degrees for Pand S-waves, and additionally depending on the fabric type (Bennett, 1968; Bentley, 1971; Blankenship and Bentley, 1987; Diez et al., 2015; Diez et al., 2014; Kerch et al., 2018; Picotti et al., 2015). Both englacial temperature and anisotropy was incorporated in the numerical ice sheet simulations of Llorens et al. (2020), which predicted a slight monotonic decrease in VS,i (∼5%) but a consistent VP,i with depth that agreed with deep borehole measurements (Gusmeroli et al., 2012). An evolution in englacial attenuation with depth is also inferred to exist, predominantly due to temperature (Peters et al., 2012). Entrained debris is another influence on the effective viscoelastic properties, being incorporated predominantly into the ice sheet base through pressure-melting regelation, glaciohydraulic supercooling and net adfreezing (Fitzsimons et al., 2008; Jennings and Hambrey, 2021; Lipovsky et al., 2019). The presence of basal debris has been widely observed in the bottom 5–10 m of Antarctic ice cores (e.g., Goodwin, 1993; Gow et al., 1979; Tison et al., 1993), but has also been associated to larger reflector units of 100–200 m thickness from RES (Franke et al., 2023; Winter et al., 2019). Further insight into basal debris characteristics remains ambiguous and highly localized however, restricting seismic and radar modeling to broad assumptions regarding debris content, composition and grain-matrix mixing (Christianson et al., 2016; Christoffersen et al., 2010; Franke et al., 2023; Luthra et al., 2017; Winter et al., 2019). The combination of the above factors has the potential to distort HVSR peak frequencies relative to f0(i.e., assuming a uniform ice layer) and result in misinterpretations of subglacial layer presence and character. For this end-member scenario, we parameterize three different non-uniform ice sheet layers: (i) the suggested seismic velocity profile of Llorens et al. (2020) without water inclusions (discretized by 10 layers), with VP,i fixed to 3840 m/s and VS,i monotonically varying with depth from 1950 to 1840 m/s, along with ρi(from 830 to 920 kg/m3; see Text S3.3) and Q-factor values (from QS,i = 20 and QP,i = 100 to QS,i =QP,i = 10 at the ice sheet base); (ii) an inclusion into the ice sheet layer of (i) of a 200 m-thick basal-debris unit with 20% debris inclusion (Franke et al., 2023) and properties assumed for the low-VSunlithified sediments (Table S3.2), incorporated into the effective medium parameters using the standard Bruggeman mixing model 8 (Roethlisberger, 1972); (iii) a single, uniform basal ice layer as suggested by Yan et al. (2018), with thicknesses 20% of hi,VS= 1500 m/s, VP= 3750 m/s, ρ= 920 kg/m3and QS=QP= 10. As with the firn layer scenario, each case is modeled for an ice-basement profile and including a 500 m-thick subglacial layer of unlithified sediments with lower-bound elastic parameters (Table S3.2), and compared against synthetic HVSRs for a uniform ice sheet of corresponding ice thickness. All other model parameters are kept as for the simple-case scenarios (Table S3.2). Subglacial layering The treatment of subglacial material as a single, uniform layer of either unlithified sediments or sedimentary rocks is not realistic: sedimentary packages often possess internal architecture that reflect an interplay of sediment deposition, transport and preservation across a range of spatial scales, as well as tectonic and environmental influences (Miall, 2013). In the simplest case, one can expect unlithified sediments to overlie crystalline basement or a sedimentary basin only if recent or ongoing deposition has occurred with insufficient time for compaction and lithification. Deeper stratigraphic units delineate an underlying history of sedimentary events (Nichols, 2023) and are commonly identified from seismic reflection data (Posamentier et al., 2022; Sheriff, 2012). Reflection horizons have been distinguished within the Antarctic IBIZ (e.g., Benjumea and Teixidó, 2001; King et al., 2007; Smith et al., 2007; Smith et al., 2013; Smith and Murray, 2009), albeit only near to the basal interface due to limited seismic resolutions beneath the AIS. Nevertheless, stratigraphy and other structural features (e.g., faults, sills) are expected to be prevalent in the thick subglacial sedimentary basins of Antarctica (Aitken et al., 2023). More continuous transitions in lithological properties caused by post-depositional processes (e.g., compaction, diagenesis) and fluid infiltration are also prevalent in sedimentary units, resulting in depthwise gradients in seismic velocity, density and seismic attenuation (Bjørlykke, 2014; Cartwright, 2007). In the context of HVSR interpretations, this combined heterogeneity is known to distort estimates of bedrock depth if the subsurface VSprofile is assumed to be constant or otherwise poorly defined (Cascone et al., 2022; Guéguen et al., 2007) and typically necessitates a calibration against the local geology for accurate measurements (Molnar et al., 2022). If unaccounted for, layering in the subglacial material could both cause HVSR misinterpretations assuming a single subglacial layer and introduce additional peak features into HVSRs. For this end-member scenario, we parameterize three different example cases of subglacial layering: (i) a 200 m-thick unlithified sediments layer with VS,l = 200 m/s overlying a 2000 m-thick sedimentary rocks layer of varying VS,l between 1200–3000 m/s; (ii) two distinct sedimentary rocks layers, with an upper layer of VS,l = 2300 m/s and a lower layer of VS,l = 2700 m/s; (iii) a 2000 m-thick subglacial layer with a linear gradient in parameters (discretized by 10 layers) from VS,l = 200 m/s to between 1200–2400 m/s at the basement half-space. Each case is modeled and compared against synthetic HVSRs for an ice-basement profile of corresponding ice thickness, as well as for relevant single subglacial layer profiles. Corresponding VP, and ρlare derived from Brocher (2005), whilst all other model parameters are kept as for the simple-case scenarios (Table S3.2). We acknowledge that these example cases do not encompass all plausible subglacial conditions, but are chosen to assess any first-order effects on HVSR behavior compared to the simple-case scenarios. 9 1000 2000 3000 VS [m/s] 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 Depth [m] hi = 10 m hl = 2 m (b) 1 10 100 1000 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 16 1000 2000 3000 VS [m/s] 0 5 10 15 20 25 30 35 40 Depth [m] hi = 20 m hl = 4 m (c) 0.5 1 10 100 500 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 17 1000 2000 3000 VS [m/s] 0 20 40 60 80 100 Depth [m] hi = 50 m hl = 10 m (d) 0.2 1 10 100 200 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 18 1000 2000 3000 VS [m/s] 0 25 50 75 100 125 150 175 200 Depth [m] hi = 100 m hl = 20 m (e) 0.1 1 10 100 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 19 1000 2000 3000 VS [m/s] 0 50 100 150 200 250 300 350 400 Depth [m] hi = 200 m hl = 40 m (f) 0.05 0.1 1 10 50 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 20 1000 2000 3000 VS [m/s] 0 200 400 600 800 1000 Depth [m] hi = 500 m hl = 100 m (g) 0.02 0.1 1 10 20 Frequency [Hz] 0 1000 2000 3000 Phase velocity [m/s] DC 0 2 4 6 8 HVSR BW 0 1 2 HVSR RWE (R0) 0 1 2 HVSR RWE (R1) 0 1 2 HVSR RWE (R2) 21 Figure S3.1: (Previous pages.) Synthetic RWE modeled for the fundamental (R0, solid lines), first (R1, dashed lines) and second (R2, dotted lines) higher modes for various shallow scenarios, compared against the corresponding HVSRs from the BW model and multi-modal dispersion curves (DC). Row (a) displays results for 1-D profiles derived from M2.2 from Bonnefoy-Claudet et al. (2008), with surface layer thicknesses hsranging from the original 25 m to 500 m. An IBIZ configuration with a subglacial layer of unlithified sediments is considered in rows (b) to (g), with hlset to 20% of hi, varying between 10–500 m. All other model parameters are kept as for the simple-case scenarios (Table S3.2). 22 1000 2000 3000 VS [m/s] 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 Depth [m] hi = 10 m hl = 2 m (a) 0 2 4 6 8 HVSR BW 0 2 4 HVSR DFA (FW) 0 2 4 6 8 10 12 14 16 18 HVSR DSS (FW) 0 2 4 HVSR DFA (RLN) 0 2 4 6 8 10 12 HVSR DSS (RLN) 0 1 HVSR DFA (RN) 1 10 100 1000 Frequency [Hz] 0 1.5 HVSR DSS (RN) Considering higher SW modes in DFA & DSS 23 1000 2000 3000 VS [m/s] 0 5 10 15 20 25 30 35 40 Depth [m] hi = 20 m hl = 4 m (b) 0 2 4 6 8 HVSR BW 0 2 4 HVSR DFA (FW) 0 2 4 6 8 10 12 HVSR DSS (FW) 0 2 4 HVSR DFA (RLN) 0 2 4 6 8 10 12 HVSR DSS (RLN) 0 1 HVSR DFA (RN) 1 10 100 500 Frequency [Hz] 0 1.5 HVSR DSS (RN) 24 1000 2000 3000 VS [m/s] 0 20 40 60 80 100 Depth [m] hi = 50 m hl = 10 m (c) 0 2 4 6 8 HVSR BW 0 2 4 HVSR DFA (FW) 0 2 4 6 8 10 12 14 HVSR DSS (FW) 0 2 4 HVSR DFA (RLN) 0 2 4 6 8 10 12 HVSR DSS (RLN) 0 1 HVSR DFA (RN) 0.2 1 10 100 200 Frequency [Hz] 0 1.5 HVSR DSS (RN) 25 Figure S3.3: (Previous pages.) Parameter sensitivity tests for P-wave velocity VP. Rows (a) to (f) show isolated variations in VPfor different scenarios with hi= 1000 m, with associated synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) models (Table S3.1; Text S3.4). Rows (a) and (b) correspond to an ice-basement configuration; rows (c) and (d) include a 500 m-thick subglacial layer of unlithified sediments with VS,l = 1000 m/s; rows (c) and (d) include a 5000 m-thick subglacial layer of sedimentary rocks with VS,l = 1500 m/s. In (a), VP,i is varied between 3500–4000 m/s. In (c), VP,l is varied between 1500–2300 m/s. In (e), VP,l is varied between 2250–3500 m/s. For (b), (d) and (f), VP,b is varied between 4500–7500 m/s. All other layer and half-space parameters are kept as for the simple-case scenarios (Table S3.2) except for Q-factors, which are uniformly set to QS=QP= 100 for all layers. 32 1000 2000 ρ [kg/m 3 ] 600 800 1000 1200 1400 Depth [m] (a) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 1000 2000 3000 ρ [kg/m 3 ] 600 800 1000 1200 1400 Depth [m] (b) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 1000 2000 ρ [kg/m 3 ] 500 750 1000 1250 1500 1750 2000 Depth [m] (c) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) Parameter sensitivity test for ρ 33 1000 2000 3000 ρ [kg/m 3 ] 500 750 1000 1250 1500 1750 2000 Depth [m] (d) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 1000 2000 3000 ρ [kg/m 3 ] 2000 4000 6000 Depth [m] (e) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 1000 2000 3000 ρ [kg/m 3 ] 2000 4000 6000 Depth [m] (f) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 34 Figure S3.4: (Previous pages.) Parameter sensitivity tests for density ρ. Rows (a) to (g) show the same scenarios as given in Fig. S3.3. In (a), ρiis varied between 830–920 kg/m3. In (c), ρl is varied between 1500–2300 kg/m3. In (e), ρlis varied between 2000–3000 kg/m3. For (b), (d), and (f), ρbis varied between 2000–3000 kg/m3. All other model parameters are kept as for the simple-case scenarios (Table S3.2), with QS=QP= 100 set for all layers. Refer to Fig. S3.3 for further plot details. 35 10 100 200 500 QS 600 800 1000 1200 1400 Depth [m] (a) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 500 QS 600 800 1000 1200 1400 Depth [m] (b) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 QS 500 750 1000 1250 1500 1750 2000 Depth [m] (c) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) Parameter sensitivity test for QS 36 10 100 200 500 QS 500 750 1000 1250 1500 1750 2000 Depth [m] (d) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 QS 2000 4000 6000 Depth [m] (e) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 500 QS 2000 4000 6000 Depth [m] (f) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 37 Figure S3.5: (Previous pages.) Parameter sensitivity tests for S-wave Q-factor QS. Only synthetic HVSRs from the BW and DSS (FW) models incorporating attenuation are included (as noted in Section 3.2.2). Rows (a) to (g) show the same scenarios as given in Fig. S3.3, QS,i, QS,l and QS,b separately varied between 10–500. All other model parameters are kept as for the simple-case scenarios (Table S3.2). Refer to Fig. S3.3 for further plot details. 38 10 100 200 500 QP 600 800 1000 1200 1400 Depth [m] (a) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 500 QP 600 800 1000 1200 1400 Depth [m] (b) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 QP 500 750 1000 1250 1500 1750 2000 Depth [m] (c) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) Parameter sensitivity test for QP 39 10 100 200 500 QP 500 750 1000 1250 1500 1750 2000 Depth [m] (d) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 QP 2000 4000 6000 Depth [m] (e) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 10 100 200 500 QP 2000 4000 6000 Depth [m] (f) 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 3 4 HVSR DSS (FW) 40 Figure S3.6: (Previous pages.) Parameter sensitivity tests for P-wave Q-factor QP. As in Fig. S3.5, only synthetic HVSRs from the BW and DSS (FW) models incorporating attenuation are included. Rows (a) to (g) show the same scenarios as given in Fig. S3.3, with QP,i,QP,l and QP,b separately varied between 10–500. All other model parameters are kept as for the simple-case scenarios (Table S3.2). Refer to Fig. S3.3 for further plot details. 41 1000 2000 3000 VS [m/s] 600 800 1000 1200 1400 1600 Depth [m] (d) hl = 100 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 600 800 1000 1200 1400 1600 Depth [m] (e) hl = 200 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 500 750 1000 1250 1500 1750 Depth [m] (f) hl = 300 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 48 1000 2000 3000 VS [m/s] 500 750 1000 1250 1500 1750 Depth [m] (g) hl = 400 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 500 750 1000 1250 1500 1750 2000 Depth [m] (h) hl = 500 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) Figure S3.9: (This and previous pages.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the simple-case scenario of a subglacial layer of unlithified sediments with hi= 1000 m. Refer to Fig. S3.8 for further plot details. 49 1000 2000 3000 VS [m/s] 1600 1800 2000 2200 2400 Depth [m] (a) hl = 10 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 1600 1800 2000 2200 2400 Depth [m] (b) hl = 20 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 1600 1800 2000 2200 2400 Depth [m] (c) hl = 50 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) hi = 2000 m Subglacial layer = unlithified sediment 50 1000 2000 3000 VS [m/s] 1600 1800 2000 2200 2400 2600 Depth [m] (d) hl = 100 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 1600 1800 2000 2200 2400 2600 Depth [m] (e) hl = 200 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 1500 1750 2000 2250 2500 2750 Depth [m] (f) hl = 300 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 51 1000 2000 3000 VS [m/s] 1500 1750 2000 2250 2500 2750 Depth [m] (g) hl = 400 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 1500 1750 2000 2250 2500 2750 3000 Depth [m] (h) hl = 500 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) Figure S3.10: (This and previous pages.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the simple-case scenario of a subglacial layer of unlithified sediments with hi= 2000 m. Refer to Fig. S3.8 for further plot details. 52 1000 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 Depth [m] (a) hl = 10 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 Depth [m] (b) hl = 20 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 Depth [m] (c) hl = 50 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) hi = 3000 m Subglacial layer = unlithified sediment 53 1000 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 3600 Depth [m] (d) hl = 100 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 3600 Depth [m] (e) hl = 200 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 2500 2750 3000 3250 3500 3750 Depth [m] (f) hl = 300 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 54 1000 2000 3000 VS [m/s] 2500 2750 3000 3250 3500 3750 Depth [m] (g) hl = 400 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 2500 2750 3000 3250 3500 3750 4000 Depth [m] (h) hl = 500 m 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) Figure S3.11: (This and previous pages.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the simple-case scenario of a subglacial layer of unlithified sediments with hi= 3000 m. Refer to Fig. S3.8 for further plot details. 55 2000 3000 VS [m/s] 0 200 400 600 800 1000 Depth [m] (a) hl = 100 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 0 200 400 600 800 1000 1200 Depth [m] (b) hl = 200 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 0 250 500 750 1000 1250 1500 Depth [m] (c) hl = 500 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) hi = 500 m Subglacial layer = sedimentary rock 56 2000 3000 VS [m/s] 0 500 1000 1500 2000 Depth [m] (d) hl = 1000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 0 500 1000 1500 2000 2500 3000 Depth [m] (e) hl = 2000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 0 1000 2000 3000 4000 Depth [m] (f) hl = 3000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 57 2000 3000 VS [m/s] 2000 3000 4000 5000 6000 Depth [m] (g) hl = 4000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 2000 3000 4000 5000 6000 7000 Depth [m] (h) hl = 5000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) Figure S3.14: (This and previous pages.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the simple-case scenario of a subglacial layer of sedimentary rocks with hi= 2000 m. Refer to Fig. S3.12 for further plot details. 64 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 3600 Depth [m] (a) hl = 100 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 2600 2800 3000 3200 3400 3600 Depth [m] (b) hl = 200 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 2500 2750 3000 3250 3500 3750 4000 Depth [m] (c) hl = 500 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) hi = 3000 m Subglacial layer = sedimentary rock 65 2000 3000 VS [m/s] 2500 3000 3500 4000 4500 Depth [m] (d) hl = 1000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 2500 3000 3500 4000 4500 5000 5500 Depth [m] (e) hl = 2000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 3000 4000 5000 6000 Depth [m] (f) hl = 3000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 66 2000 3000 VS [m/s] 3000 4000 5000 6000 7000 Depth [m] (g) hl = 4000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) 2000 3000 VS [m/s] 3000 4000 5000 6000 7000 8000 Depth [m] (h) hl = 5000 m 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0 1 2 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 HVSR DSS (FW) Figure S3.15: (This and previous pages.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the simple-case scenario of a subglacial layer of sedimentary rocks with hi= 3000 m. Refer to Fig. S3.12 for further plot details. 67 1000 2000 3000 VS [m/s] 0 250 500 750 1000 1250 1500 1750 2000 Depth [m] hi = 1000 m (a) 0 1000 2000 0 20 40 60 80 100 120 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 500 1000 1500 2000 2500 3000 Depth [m] hi = 2000 m (b) 0 1000 2000 0 20 40 60 80 100 120 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 500 1000 1500 2000 2500 3000 3500 4000 Depth [m] hi = 3000 m (c) 0 1000 2000 0 20 40 60 80 100 120 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0.1 1 10 50 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) Complex-case scenario = firn layer 68 Figure S3.16: (Previous page.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the complex-case end-member scenario incorporating a surficial firn layer (Text S3.4). For each hi= [1000, 2000, 3000] m, VS-depth profiles and synthetic HVSRs for an ice-basement configuration (black lines) and including a 500 m-thick subglacial layer of unlithified sediments with VS,l = 200 m/s (green lines) are shown respectively on rows (a), (b) and (c), with either a uniform ice profile (solid lines), including a firn layer with monotomicallyincreasing parameters with depth (dashed lines), additionally including a 20 m-thick ice slab (dashed-dotted lines), or instead approximated as a single, uniform, low-VSsurface layer (dotted lines). The red insets highlight the different firn layer scenarios. The vertical gray lines denote the expected resonance frequencies (Eq. 3.1 in main text) from the uniform, low-VSfirn layer, with f0(solid line), f1(dashed line) and f2(dashed line). 69 1000 2000 3000 VS [m/s] 0 250 500 750 1000 1250 1500 1750 2000 Depth [m] hi = 1000 m (a) 1500 2000 600 800 1000 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 500 1000 1500 2000 2500 3000 Depth [m] hi = 2000 m (b) 1500 2000 1200 1400 1600 1800 2000 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 500 1000 1500 2000 2500 3000 3500 4000 Depth [m] hi = 3000 m (c) 1500 2000 1800 2000 2200 2400 2600 2800 3000 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 10 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 8 HVSR DSS (FW) Complex-case scenario = basal ice 70 Figure S3.17: (Previous page.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the complex-case end-member scenario incorporating variations in basal ice sheet properties (Text S3.4). Rows (a), (b) and (c) correspond to VS-depth profiles and synthetic HVSRs for the same set of hiand configurations (black and green lines) as in Fig. S3.16, with either a uniform ice profile (solid lines), an ice sheet layer with the velocity-depth gradient given by Llorens et al. (2020), additionally including a 200 m-thick basal debris unit (dashed-dotted lines), or instead with a single, uniform, low-VSbasal ice layer as suggested by Yan et al. (2018) (dotted lines). The red insets highlight the basal ice scenarios. 71 1000 2000 3000 VS [m/s] 0 1000 2000 3000 Depth [m] hi = 1000 m (a) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 1000 2000 3000 4000 Depth [m] hi = 2000 m (b) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DSS (FW) 1000 2000 3000 VS [m/s] 0 1000 2000 3000 4000 5000 Depth [m] hi = 3000 m (c) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR BW 0.01 0.1 1 5 Frequency [Hz] 0.0 0.5 1.0 1.5 HVSR RWE (R0) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DFA (FW) 0.01 0.1 1 5 Frequency [Hz] 0 2 4 6 HVSR DSS (FW) Complex-case scenario = sedimentary layering (i) 72 Figure S3.18: (Previous page.) Synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models for the complex-case end-member scenario incorporating simultaneous subglacial layering of unlithified sediments and sedimentary rocks (Text S3.4). For each hi in rows (a), (b) and (c), VS-depth profiles and synthetic HVSRs are shown for a 200 m-thick layer of unlithified sediments with set VS,l = 200 m/s and a 2000 m-thick layer of sedimentary rocks with varying VS,l between 1200–3000 m/s are included, either separately (black and colored dash-dotted lines, respectively) or simultaneously (colored dashed lines). An ice-basement configuration is also shown for reference (black solid lines). 73 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 06/01/2012 - 11/01/2012 SIPL BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 27/01/2010 - 01/02/2010 ST01 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 01/01/2011 - 06/01/2011 ST02 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 80 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 27/01/2010 - 01/02/2010 ST03 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 27/01/2010 - 01/02/2010 ST04 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 26/01/2011 - 31/01/2011 ST08 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 81 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 20/01/2010 - 25/01/2010 ST09 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 21/01/2010 - 26/01/2010 ST10 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 11/01/2011 - 16/01/2011 ST13 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 82 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 18/01/2010 - 23/01/2010 ST14 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 01/01/2013 - 06/01/2013 UPTW BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 01/01/2014 - 06/01/2014 WAIS BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 83 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 23/01/2010 - 28/01/2010 DNTW BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 27/01/2010 - 01/02/2010 ST07 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR 27/01/2010 - 01/02/2010 ST12 BW 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR RWE (R0) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DFA (FW) 0.05 0.1 1 3 Frequency [Hz] 0 1 2 3 HVSR DSS (FW) 84 Figure S3.21: (Previous pages.) Extending the comparison in Fig. 3.5 in the main text of synthetic HVSRs from the BW, RWE (R0), DFA (FW) and DSS (FW) forward models against observed HVSRs, and additionally including stations DNTW, ST07 and ST12 (which exhibited poor-quality HVSRs, as discussed in Section 3.4.1). Refer to Fig. 3.5 for plot details and to Text S3.6 and Table S3.3 regarding the forward modeling strategy and parameterizations used to generate the synthetic HVSRs. Note that numerical irregularities can be seen at higher frequencies for the non-BW models due to the use of modal summation to SW modes, as discussed in Text S3.2. 85 0.05 0.1 1 3 Frequency [Hz] 0 1 2 HVSR 01/01/2018 - 06/01/2018 QSPA 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 P061 0.05 0.1 1 3 Frequency [Hz] 0 1 2 HVSR 01/01/2018 - 06/01/2018 AGO3 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 SWEI 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 CCD 0.05 0.1 1 3 Frequency [Hz] 0 1 2 HVSR 01/01/2018 - 06/01/2018 ST06 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 UPTW 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 BEBP 0.05 0.1 1 3 Frequency [Hz] 0 1 2 HVSR 01/01/2018 - 06/01/2018 ST13 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 KOLR 0.05 0.1 1 3 Frequency [Hz] 01/01/2018 - 06/01/2018 DNTW DecNovOctSepAugJulJunMayAprMarFebJan Further Closer Coastal proximity 86 Figure S3.22: (Previous page.) Seasonal trends in observed median HVSRs for the same set of stations considered in Fig. 3.7 in the main text, but for different yearly recording periods. Nearly all stations had at least 2 years of available data with the exception of station ST01, which was deployed for only 1 year and is therefore excluded. Refer to Fig. 3.7 for further plot details. 87 100 200 300 400 500 hl [m] hi = 500 m Unlithified sediment 1000 2000 3000 4000 5000 hl [m] Sedimentary rock 100 200 300 400 500 hl [m] hi = 1000 m 1000 2000 3000 4000 5000 hl [m] 100 200 300 400 500 hl [m] hi = 2000 m 1000 2000 3000 4000 5000 hl [m] 100 200 300 400 500 hl [m] hi = 3000 m 1000 2000 3000 4000 5000 hl [m] 0.8636 0.0069 Shift in f mod 0 [Hz] 0.8693 0.1040 Shift in f mod 0 [Hz] 0.4108 0.0017 Shift in f mod 0 [Hz] 0.4055 0.0550 Shift in f mod 0 [Hz] 0.1922 0.0004 Shift in f mod 0 [Hz] 0.1788 0.0280 Shift in f mod 0 [Hz] 0.1219 0.0002 Shift in f mod 0 [Hz] 0.1060 0.0188 Shift in f mod 0 [Hz] 88 Figure S3.23: (Previous page.) 2-D surface plots showing the sensitivity of fmod 0in synthetic HVSRs (using the BW model to hland VS,l under the simple-case scenarios assuming a single subglacial layer. Each row corresponds to a set hi, whilst the columns denote a subglacial layer of either unlithified sediments or sedimentary rock. Surfaces are color-mapped according to the shift in fmod 0relative to an ice-basement configuration. The hatched overlay suggests a minimum sensitivity to determining peak frequency shifts in observed HVSRs, given by the lower-bound uncertainty in f0(Eq. 3.1) from a plausible lower-bound ice sheet VS= 1800 m/s (Text S3.3) and the median uncertainty in Antarctic ice thickness from BedMachine (35 m). A peak prominence of 0.3 was used to identify clear peaks, explaining the irregular surface mapped for the peak behavior from the sedimentary rocks scenario compared to the unlithified sediments scenario (as noted in Section 3.3.1). 89 BIBLIOGRAPHY Anthony, R. E., Aster, R. C., Wiens, D., & Nyblade, e. a., A. (2015). The seismic noise environment of antarctica. Seismological Research Letters,86(1), 89–100. https://doi.org/ 10.1785/0220140109 Anthony, R. E., Ringler, A. T., DuVernois, M., Anderson, K. R., & Wilson, D. C. (2021). 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