dataesr/scientific-paragraphs-categorization huggingface dataset:
As three different radar systems were used, we treat each dataset independently and compare the model results obtained. We focus on three different scales which correspond to the differing spatial coverages of the three surveys over LDC. We also look at the NP site which was investigated in one of the surveys and was initially tagged as a site of interest for Oldest Ice  (Parrenin et al. , 2017). In Fig. 2 , we mark BELDC (75. 29917 Internal reflecting horizons (IRHs) were traced in each of the datasets in the two-way travel time domain. The depths of these IRHs were then calculated using the electromagnetic wave velocity in ice of 168. 5 m µs -1 as in  Winter et al. (2017)  and a firn correction of 10 m with an uncertainty of ±3 m  (Lilien et al. , 2021). Table  1  summarises the key characteristics of each dataset.
In order to date the IRHs, LDC is linked to the EDC ice core site through three independent radar transects, while NP is linked through one transect to EDC. Ages for the IRHs were then calculated by linearly interpolating the EDC agedepth timescale from AICC2012  (Bazin et al. , 2013) , where the IRHs are closest to the ice core site. As the depth difference between values in the AICC2012 dataset is 1. 65 m, there is no need for more complex interpolation, as the uncertainty is negligible relative to other factors. The age of each IRH is obtained by first calculating the average of the ages obtained from the three EDC-LDC radar intersections and then averaging with the EDC-NP intersection. It is this average age for each IRH that is input to the model. The depth uncertainty of each IRH arises from several contributions.
It was capable of transmitting 8 µs chirped pulses with 500 W peak power per channel at a pulse repetition frequency of 10 kHz  (Yan et al. , 2020). This system was operated with much reduced sensitivity because of the failure of the balloon carrying the antenna structure and the compact power generator housed close to the radar system. The generator failure led to a large secondary generator being mounted on a metal structure between the vehicle and the antenna arrays. A long power cable powered the system in the tracked vehicle, and radio-frequency cables were forced to route next to the generator. These complications forced the field team to reduce the peak power to less than 100 W for each channel and operate only four channels to reduce radio-frequency interference (RFI) issues. In the following, we will refer to data collected using this system as the LDC-VHF radar dataset.
The dataset consists of 12 transects covering Patches A and B with parallel lines. In this study, we used the seismic environment of the Section software from Paradigm Geophysical to trace 19 IRHs along the 12 radar transects and re-interpolated them to a 10 m horizontal spacing. A delay time of 1 µs was required during processing and was confirmed by matching the reflectivity pattern https://doi. org/10. 5194/tc-17-3461-2023 The Cryosphere, 17, 3461-3483, 2023 and bedrock reflection at the EDC end of the profile to those of the radar data presented in  Winter et al. (2017). The IRHs were then dated using the direct radar transect link from LDC to the EDC ice core site. These IRHs and bedrock reflections were traced and dated independently of  Lilien et al. (2021) , who focused only on the EDC-LDC transect.
There are two components which contribute to the isochrone age uncertainty. The first comes from the dating of the EDC ice core in AICC2012  (Bazin et al. , 2013 , Table  2 ). The second component, the depth uncertainty, includes four factors: 3 m firn depth uncertainty, 0. 44 % uncertainty in the wave speed in ice, 11 m human error in IRH tracing and the gradient uncertainty over the 178 m gap from the transect to EDC (1 to 6 m). The overall depth uncertainty ranges from 12 to 18 m from the shallowest to the deepest IRH. The calculated ages and uncertainties are shown in Table  3. The high vertical resolution of the radar data shows a layer of ice just above the bedrock where there is an abrupt change in the return power and lateral coherency of the radar signal. In this layer, there are no visible continuous IRHs, although the radar system is effective at these depths, as the signal-to-noise ratio is sufficiently high to detect continuous IRHs.
BAS/UCL ApRES During the 2016-2017 and 2017-2018 field seasons, the autonomous phase-sensitive radio-echo sounder (ApRES) was also used in two locations to explore englacial flow in a collaboration between BAS and University College London (UCL). Nicholls et al. (2015)  give an overview of the system, data processing workflow and applications that we simply summarise here for convenience. ApRES is a ground-based radar system capable of tracking temporal displacement in the position of IRHs. The position changes are transformed from travel time to depth following  Kingslake et al. (2016)  using the density profile measured at EDC and assuming it applies at LDC  (Le Meur et al. , 2018). Due to the particularities of basal ice in the area, ApRES was capable of detecting reflectivity events as close as 20 m from the bed in the two successive field seasons (Fig.
We follow the standard ApRES uncertainty estimation technique described in  Brennan et al. (2014)  and  Nicholls et al. (2015) , where phase uncertainty depends on signal-to-noise ratio. The uncertainty inversely relates to signal-to-noise ratio and is lower in the basal unit than in the ice above it, which is unusual as it typically decreases with depth. The presence of stagnant ice is revealed by a comparison of ApRES data from the two locations. For the ApRES-LDC site, the magnitude of the vertical velocity decreases rapidly and reaches close to zero at a depth of 2000 m. In the top 2000 m of the ice column, we have a high density of ApRES data points, and our uncertainty is smaller than at the EDC site. If we assume that the absolute value of vertical velocity is decreasing monotonically with depth, it follows that vertical velocity in the bottom section of the column must be smaller than at the EDC, and ice towards the base must be nearly or totally stagnant.
Distribution of the basal unit Here, we investigate the extent of the potentially stagnant basal unit at LDC which was observed in the radar surveys. Features comparable to what we now refer to as the basal unit are visible in many radar datasets over Antarctica (often referred to as echo-free zone, e. g. Drews et al. , 2009). However, in our region of interest, discussions so far only include a description from the HiCARS airborne radar data  (Cavitte, 2017)  and observations from a single radar line in the LDC-VHF radar survey  (Lilien et al. , 2021). Figure  4a  shows the https://doi. org/10. 5194/tc-17-3461-2023 The Cryosphere, 17, 3461-3483, 2023 depth of the top of the basal unit for the whole LDC-VHF dataset which was traced in this study. Generally, the top of the basal unit is deeper towards the northeast and EDC.
Relevance of including a stagnant ice layer in model and comparison to observations Observations from radar surveys show that there appears to be a basal unit at LDC of unknown properties and origin. ApRES measurements show that the internal deformation of the ice sheet in the LDC area, as described by its vertical velocity profile, is better explained when an extensive stagnant basal layer is present. Our model determines the age distribution of the ice column, constrained by radar-observed IRHs. In this section, we assess the relevance of the 1D numerical model, which allows for a layer of stagnant ice vs. a model with the observed bedrock as the lower age constraint, as in  Parrenin et al. (2017). We apply this analysis to the LDC-VHF dataset, as we have mapped the basal unit extent of this area (Sect.
4. 2). Figure  5   Figure  6  shows the reliability index (σ r , Eq. 5) across all four areas of interest that we investigate in this study. The reliability index is less than 2 in most of the surveyed area and even less than 1 over LDC and NP, which indicates that the model fits to within 1σ of the IRH age constraints. In order to compare the output of the 1D stagnant ice model to observations, in Fig. 3  we also show the vertical velocity profile determined according to the 1D model for the closest points to the ApRES measurements in the DE-LORES and LDC-VHF datasets. The vertical velocities include not only ice vertical compaction and compression but also surface thinning or thickening and the vertical component of the along-surface advection. As the 1D model and ApRES data integrate over different time spans, we compare the shape functions that do not depend on those processes, which change with time, despite our pseudo-steady assumption.
We normalise the vertical velocities to the value at 150 m, which is below the depth of firn compaction. We can see from Fig. 3  that the model fits the observations well at both ApRES sites. One possible reason for the different p values for the ApRES fit and 1D model could be the different constraints used. For the ApRES data at EDC, the deepest return excluding the basal reflection was at 2145 m,  whereas the deepest IRHs traced in the radar surveys was 2826 m. Having deeper constraints for the 1D model significantly affects the non-linear portion of the thinning function and therefore the p value  (Parrenin et al. , 2017). Figure  4b  displays the depth of the top of the modelled stagnant ice layer for the LDC-VHF dataset. This depth is equal to the mechanical ice thickness H m (Fig. 1 ).
It follows the same trend as the observed basal unit (Fig. 4a ), with the deeper values occurring where the bedrock is also deeper. Comparing Fig. 4a  and b , it is clear that the depths of the observed basal unit and the top of the modelled stagnant ice are similar. Figure  7a  shows the modelled age of a single radar transect in the LDC-VHF dataset. From this, we can see that although the stagnant ice depth does not exactly match that of the observed basal unit, there is a remarkably close relationship between them, given that these values were modelled and observed independently. Figure  7b  shows the difference between the modelled stagnant ice and the observed basal unit depths. Throughout most of the radar survey, the stagnant ice thickness is larger by an average of 40 m, with a standard deviation of ±20 m.
This corresponds to an average difference of approximately 1. 5 % relative to the total ice thickness with a standard deviation of < 1 %. The locations with larger differences correspond to the areas where the basal unit appeared to thin when tracing. We should note here that tracing the top of the basal unit in the LDC-VHF radar dataset is ambiguous due to the diffuse nature of the boundary between coherent and incoherent radar returns; different manual interpretations of where this top boundary is can differ by tens of metres.
Modelled stagnant ice and melting Our model uses an inverted mechanical ice thickness H m (Fig. 2 ) to infer either a basal melt rate or a layer of stagnant ice. In Fig. 8 , we show the results of the stagnant ice thickness or basal melt rate for the four areas of interest covhttps://doi. org/10. 5194/tc-17-3461-2023 The Cryosphere, 17, 3461-3483, 2023 ered by the radar surveys (see Sect. 3). From the HiCARS dataset (Fig. 8a ), we see that the model predicts a layer of stagnant ice on the LDC bedrock relief. There is significant melting predicted around the edges of the LDC relief, especially on the western side of LDC and across the Concordia trench (Fig. 2a ), where Fig. 6a  shows that the model is less reliable. These areas are more subject to horizontal flow, implying that the 1D assumption is not valid in that case.
There is a low melt rate on the plateau around EDC which agrees with the findings of the EPICA drill project (EPICA mem-bers, 2004;  Parrenin et al. , 2007; Tison et al. , 2015; Passalacqua et al. , 2017 Passalacqua et al. , , 2018)). In Fig. 8b  and c , we zoom into the LDC area. The DE-LORES and LDC-VHF radar datasets confirm that there is stagnant ice in this region. Both datasets show stagnant ice thicknesses up to ∼ 250 m. The DELORES dataset shows that the stagnant ice layer thins to near 0 m at the edge of the LDC relief, while the LDC-VHF dataset shows that near the Oldest Ice sites at Patch A and Patch B (MYIC and BELDC) the minimum thickness of the stagnant layer remains around 100 m. In contrast to LDC, at NP, the mechanical thickness H m obtained from the model is remarkably similar to the observed bedrock depth from the radar H obs , indicating a lack of melting or stagnant ice (Fig.
Accumulation rate and p parameter In Fig. 9 , we show the modelled temporally averaged iceequivalent accumulation rate for each area considered. At LDC, we can see that the accumulation rate is generally around 19 mm yr -1. Looking at Fig. 9a , the HiCARS dataset shows that the accumulation rate is higher in surface depressions (dashed red circles) than in the surrounding areas. This is likely because snow is blown into the depressions from areas with higher surface elevation  (Cavitte et al. , 2018). The accumulation at NP (Fig. 9d ) is around 20 mm yr -1 , slightly higher than at LDC. Figure  10  shows how the Lliboutry profile p parameter (Eq. 3) varies across the four surface areas surveyed by the radar systems. The p parameter is quite high at LDC, with values between 5 and 8. Around the edges of LDC, Fig.
Model results at EDC In order to evaluate the accuracy of the model as a predictor for ice core properties, we look at the modelled results for EDC. There were three radar transects in the LDC DE-LORES dataset, one transect in the NP DELORES data and one transect in the LDC-VHF radar dataset which pass close to the EDC drill site. Table  4  shows the model age result at the points of closest approach to EDC for each radar transect. https://doi. org/10. 5194/tc-17-3461-2023 The Cryosphere, 17, 3461-3483, 2023 The three LDC DELORES transects all start at approximately the same point, ∼ 338-368 m southeast of EDC, whereas the NP DELORES transect begins 404 m northeast of EDC. This difference can explain why the total ice thickness is 3141 m for the NP transect but ranges from 3200-3239 m for the LDC transects.
The closest point to EDC in the LDC-VHF dataset is 178 m away, with a total ice thickness of 3239 m. The deepest ice which could be dated in the EDC ice core was at 3189 m depth, where the age inferred from the climatic signals is 801 ± 9. 6 ka  (Bazin et al. , 2013). At this depth, the modelled ages range from 1013±86 to 1016 ± 86 ka for the DELORES dataset, and the age was found to be 996 ± 78 ka for the LDC-VHF dataset.
Oldest Ice site prospects around Dome C Two deep ice core drilling campaigns are currently ongoing around the LDC area, so we focus on the age modelling results at the two sites. We define the maximum age as the age where the age density is sufficient for palaeoclimatic reconstructions with the measurement sensitivities currently achievable, set at 20 kyr m -1  (Fischer et al. , 2013; Van Liefferinge and Pattyn, 2013). At locations where there is basal melting, the maximum age is the age at the depth of the observed bedrock H obs. Figure  11  shows the maximum age for each of the radar datasets around Dome C. Over the LDC bedrock relief, the maximum age is spatially homogeneous with values around 1. 5 Ma (Fig. 11b ). Around the southern and western edges of the LDC relief where melting was predicted (Fig.
Age and age density predictions at BELDC and MYIC Both the DELORES and LDC-VHF radar transects are collected very close to the new BELDC drill site, at distances of 21 and 37 m, respectively. Therefore, using the model results, we can infer the potential properties of the core (see Table  5 ). The inverted mechanical ice thickness H m is 2546 ± 30 and At BELDC, the maximum ages at 20 kyr m -1 are 1. 43 ± 0. 16 Ma at 2484 m from the DELORES dataset and 1. 47 ± 0. 13 at 2504 m for the LDC-VHF dataset. Below the depth of this maximum age and above the stagnant ice, the remaining ice thickness is 62 and 67 m, respectively. Potentially, this older ice could still be useful for palaeoclimatic studies, if it is not too folded or disturbed. The age density of 1. 2 Ma ice is 13. 2 kyr m -1 at a depth of 2469 m and 12.
2 kyr m -1 at a depth of 2486 m, respectively. Figure  13  shows the age profiles at BELDC from our two radar datasets, with the Lilien et al. (  2021 ) results for comparison. The age depth profiles of our results (DELORES, orange, and LDC-VHF, blue) are almost superimposed at depths shallower than 2200 m, showing that there is little variation in the predictions of ice age in this area. At depths below this (inset of Fig. 13 ), the profiles start to diverge. The  Lilien et al. (2021)  (grey) and DELORES profiles (orange) are within each other's uncertainty ranges. The LDC-VHF profile (blue) predicts a slightly younger age at a given depth. For comparison, we show the age-depth profile determined using the model which does not allow for a stagnant ice layer (black line). The profile obtained from modelling with no stagnant layer clearly deviates from the IRH constraints (blue circles) at depths > 2200 m, supporting the conclusion that the inclusion of a stagnant ice layer in the model is more appropriate at LDC (Sect.
4. 3). Table  5  also shows the model results for the MYIC drill site. With the exception of total ice thickness H obs , this site shows more consistent values between the DELORES and LDC-VHF datasets than are calculated at BELDC. The average values for all characteristics highlighted are within unhttps://doi. org/10. 5194/tc-17-3461-2023 The Cryosphere, 17, 3461-3483, 2023 certainties for the two drill sites. An analogous age-depth profile figure for MYIC can be found in the Supplement (Fig. S1 ).
,  2013), so it is assumed to be identical to that inferred from the EDC ice core for all radar datasets. Of the available ice core records, EDC provides the most suitable accumulation record for the LDC and NP sites, as its proximity implies that it shares similar local conditions. Moreover, unlike the Vostok ice core, for example, where there is significant horizontal flow so deeper ice originates from further upstream than the shallower ice, EDC is relatively unaffected by local factors. EDC is ∼ 35 km from LDC and ∼ 10 km from NP, so the accumulation rates are not drastically different (Fig. 9 ;  Le Meur et al. , 2018). The oldest ice found at EDC was 800 ka; therefore, information on the accumulation variation r(t) is limited to ice younger than this. Inferring accumulation variations from marine sediment cores (Lisiecki and https://doi.
This could mean our age predictions for BELDC are overestimated at depths up to 300 m above the bed where the relationship becomes less exponential. Further uncertainty is added when considering the 198 ± 44 m modelled stagnant ice thickness at BELDC and whether it can be included in this area of reduced thinning at the base of the ice sheet. The 1D nature of this model means that effects due to horizontal flow are not considered. Along the Dome C divide, this is a reasonable assumption. However, where ice flows along the Concordia trench as seen in the HiCARS radar dataset, the model becomes less reliable (Fig. 6a ). The HiCARS radar dataset, as a result of being airborne, has a lower spatial resolution than the other datasets, and regions with faster ice flow can make IRHs difficult to trace.
Over Concordia trench there appear to be some anomalies in the modelled maximum age (Fig. 11a ) which are due to discontinuities in the traced IRHs. Figure  6  shows that the reliability index (Eq. 5) is less than 2 in most of the surveyed area and even less than 1 over LDC and NP; therefore, our assumptions seem to be appropriate for areas close to the dome. In order to account for horizontal flow, we suggest that a 2. 5D model would be most appropriate, as a pseudo-steady geometry could be maintained, and a Lagrangian/semi-Lagrangian tracer scheme would not be required. Sutter et al. (2021)  showed that it is possible to use a non-pseudo-steady model, though it is more challenging as it requires more detailed knowledge of boundary conditions and temporal accumulation variations. Currently the spatial resolution for this type of model is also too low to take into account the scales of the processes discussed here, the small scale bedrock relief and high spatial radar resolution datasets, for example.
Radar dataset limitations In Sect. 4. 6, we look at the radar data sites that pass closest to EDC, which includes four DELORES transects and one LDC-VHF transect. The most accurate estimate of the ice thickness at EDC is 3273 ± 5 m  (Parrenin et al. , 2007) , determined using the length of the core and the drilling cable and accounting for hole inclination. In this study, the total ice thicknesses in Table  4  come directly from the bedrock interface traced in each radar dataset and agree well with  Lilien et al. (2021) , who independently traced the bedrock depth in the LDC-VHF dataset as 3238 m. They suggested that the difference between the radar measured bedrock return and the drill hole bottom measured could be due to factors such as "off-nadir reflection, debris in the ice, small differences in topography over the 178 m offset, and uncertainty in firnair content and wave speed".
The DELORES dataset is also shallower than expected, probably for similar reasons. The depth distribution of the IRHs traced in each dataset is quite different. Both the HiCARS and DELORES datasets have dated IRHs from ∼ 10 ka (∼ 300 m depth). Whereas for the LDC-VHF dataset, it was only possible to trace IRHs below 1000 m because of the length of the transmission chirp (8 µs), which blanks the upper parts of the ice sheet such that the first observable IRH is much older (73. 3 ka). The age of the oldest dateable IRH is limited by the radar transect linking LDC to the EDC ice core for dating. The basal melting along the divide between EDC and LDC (Fig. 8a ) means that deep IRHs are either discontinuous or completely melted in some places. Therefore, IRHs over 500 ka can only be discontinuously traced from LDC to EDC, as done by  Lilien et al.
(2021). In this study, the same method was used to trace four further discontinuous IRHs in the DELORES radar data; however, the uncertainty was too high for them to be considered here. Cavitte et al. (2021)  traced seven deep IRHs in the HiCARS dataset which could not be linked to EDC. They used the  Parrenin et al. (2017)  model to date the IRHs and found that, at LDC, their oldest IRH was ∼ 700 ka. A new age-depth profile from an ice core at LDC, such as at BELDC or MYIC, would mean that deeper IRHs could be continuously traced to an ice core record for dating. Having deeper dated IRHs would help to constrain the model at lower depths, giving a more accurate thinning function, and would therefore yield more accurate model results for the whole LDC area. The ability to observe the internal structure of the basal unit in the radar data is relatively new  (Cavitte, 2017; Lilien et al.
They suggested that since this deepest ice was almost at the melting point, there could be a mechanism of chemical sorting acting on the impurities. Bell et al. (2011)  presented radargrams which they interpreted as refrozen ice at the base of the Dome A ice sheet. The appearance of the radar data of the basal unit at Dome C is very different to Dome A, as IRH fragments are visible. However, ice with entrapment of basal debris, partly containing refrozen ice (e. g. from regelation in the past), cannot be ruled out as a source of stagnant ice, as it could be that the Dome A radar system was not able to pick up weaker, fragmented signals. The upper part of the EFZ observed by  Drews et al. (2009)  at EDML seems to have been a signature of the radar, related to sub-resolution changes in physical properties, as the  Ruth et al.