Abstract:
We present here a new helicopter-borne glacier thickness survey in Khumbu Himal, Nepal, flown by the British Antarctic Survey in 2019. The data consist of raw and processed radio echo sounding radargrams and associated survey measurements acquired using a mono-pulse dipole radar known as 'DELORES', and geolocated glacier thickness interpreted from these radargrams. Mountain glaciers provide an important service in sustaining river flows for large populations downstream of High Mountain Asia, but these glaciers are retreating, and their future is highly uncertain. Glacier thickness measurements are vital for accurate mapping of the remaining ice reserve and for predicting where and how fast it will decline under climate change, but such measurements are severely lacking in this region due to the difficulties of surveying in remote, high-altitude settings. We report on a uniquely extensive new glacier thickness dataset for 17 glaciers in the Khumbu Himal around Everest that our team from the British Antarctic Survey collected using a novel, low-frequency helicopter-borne radar. We succeeded in mapping ice thickness with a precision of around +/-7% for thicknesses of up to 445 m and spanning a total of 119 line-km. This approximately doubles the length of previous thickness surveys in High Mountain Asia.
This research is supported by the following NERC fundings:
- NERC International Opportunities Fund - Bedmap Himalayas - Reconnaissance (NE/L013258/1)
- Polar Expertise - Supporting Development (NE/R000107/1 and NEB1348)
- The Big Thaw (NE/X005267/1 and NEB2165)
Keywords:
Airborne, Glacier, Himalayas, Radar, Thickness
Pritchard, H., King, E., Goodger, D., Boyle, D., Goldberg, D., Recinos, B., & Orr, A. (2025). Raw and processed helicopter-borne radio-echo sounding ice thickness data from the glaciers of the Khumbu Himal, Nepal (2019) (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/e39647f5-fb72-4d16-acbd-9784ed2167b8
| Access Constraints: | This dataset is under embargo until the publication of the associated paper. |
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| Use Constraints: | Data supplied under Open Government Licence v3.0 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2025-06-23 |
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| Dataset Progress: | In Work |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | Dr Hamish D Pritchard |
| Role(s) | Technical Contact, Metadata Author, Investigator |
| Organisation | British Antarctic Survey |
| Name | Dr Edward King |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Mr David J Goodger |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Mr Douglas Boyle |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Dr Daniel N Goldberg |
| Role(s) | Investigator |
| Organisation | University of Edinburgh |
| Name | Dr Beatriz Recinos |
| Role(s) | Investigator |
| Organisation | University of Edinburgh |
| Name | Dr Andrew Orr |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Parent Dataset: | N/A |
| Reference: | * Associated paper: Pritchard, H.D., King, E.C., Goodger, D.J., Boyle, D., Goldberg, D., Recinos, B., Orr, A. and Regmi, D. (in prep) Towards Bedmap Himalayas: a new airborne glacier thickness survey in Khumbu Himal, Nepal. * Related datasets The clutter model was written in python and is available here: Recinos, B., Goldberg, D. N., Boyle, D., & Pritchard, H. (2025). bearecinos/radar-declutter: First radar-declutter release (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.15488954 A wiki is available at https://github.com/bearecinos/radar-declutter/wiki. The ground survey data cited here are already archived at the Polar Data Centre of the British Antarctic Survey, reference NE/L013258/1: Pritchard, H. (2017). Ground-penetrating radar data from Lirung and Langtang Glaciers, Nepal, 2015 (Version "1.0") [Data set]. Polar Data Centre; British Antarctic Survey, Natural Environment Research Council; Cambridge, CB3 0ET, UK.. https://doi.org/10.5285/b14057b1-1951-45a0-a055-7d0d17102263 The associated paper of the ground penetrating radar survey gives some additional details: Pritchard HD, King EC, Goodger DJ, McCarthy M, Mayer C, Kayastha R. Towards Bedmap Himalayas: development of an airborne ice-sounding radar for glacier thickness surveys in High-Mountain Asia. Annals of Glaciology. 2020;61(81):35-45. doi:10.1017/aog.2020.29 * References: Farinotti, D., D. J. Brinkerhoff, J. J. Fürst, P. Gantayat, F. Gillet-Chaulet, M. Huss, P. W. Leclercq, H. Maurer, M. Morlighem, A. Pandit, A. Rabatel, R. Ramsankaran, T. J. Reerink, E. Robo, E. Rouges, E. Tamre, W. J. J. van Pelt, M. A. Werder, M. F. Azam, H. Li and L. M. Andreassen (2021). "Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)." Frontiers in Earth Science 8. Gades, A. M., H. Conway and N. Nereson (2000). Radio echo-sounding through supraglacial debris on Lirung and Khumbu Glaciers, Nepal Himalayas. Debris-Covered Glaciers, Washington, USA, IAHS. Gardner, A., M. Fahnestock and T. Scambos (2022). MEaSUREs ITS_LIVE Regional Glacier and Ice Sheet Surface Velocities, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center. GlaThiDa Consortium. (2020). "Glacier Thickness Database 3.1.0. World Glacier Monitoring Service." from https://www.gtn-g.ch/glathida/. Jarvis, A., H. I. Reuter, A. Nelson and E. Guevara. (2008). "Hole-filled SRTM for the globe Version 4,." from http://srtm.csi.cgiar.org. King, E. C. (2020). "The precision of radar-derived subglacial bed topography: a case study from Pine Island Glacier, Antarctica." Annals of Glaciology 61(81): 154-161. Macheret, Y. Y., M. Y. Moskalevsky and E. V. Vasilenko (1993). "Velocity of radio waves in glaciers as an indicator of their hydrothermal state, structure and regime." Journal of Glaciology 39(132): 373-384. Millan, R., J. Mouginot, A. Rabatel and M. Morlighem (2022). "Ice velocity and thickness of the world's glaciers." Nature Geoscience 15(2): 124-129. Moribayashi, S. (1978). "Transverse Profiles of Khumbu Glacier Obtained by Gravity Observation Glaciological Expedition of Nepal, Contribution No. 46." Journal of the Japanese Society of Snow and Ice 40(Special): 21-25. Pritchard, H. D., E. C. King, D. J. Goodger, M. McCarthy, C. Mayer and R. Kayastha (2020). "Towards Bedmap Himalayas: development of an airborne ice-sounding radar for glacier thickness surveys in High-Mountain Asia." Annals of Glaciology 61(81): 35-45. Pritchard, H.D., King, E.C., Goodger, D.J., Boyle, D., Goldberg, D., Recinos, B., Orr, A. and Regmi, D. (in review) Towards Bedmap Himalayas: a new airborne glacier thickness survey in Khumbu Himal, Nepal. Earth System Science Data. Rowan, A. and D. Egholm. (2021). "Simulated ice thickness, supraglacial debris thickness and subglacial topography for Khumbu Glacier, Nepal, using the iSOSIA ice-flow model - VERSION 2.0 (Version 2.0)." from https://doi.org/10.5285/f62a1b8a-5a4c-451a-8dfb-28600b4049e8. Shean, D. (2017). High Mountain Asia 8-meter DEM Mosaics Derived from Optical Imagery, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center. |
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| Quality: | With the combination of our 3 kHz radar pulse repetition frequency, the average flying speed while surveying of ~10 m s-1 (36 km h-1) and the trace stacking and horizontal interpolation of our data processing, the horizontal sampling in our ice thickness survey averages 1.15 m (max 3.0 m, SD 0.27 m) along flightlines. However, the horizontal resolution of the bed target is limited by the Fresnel zone (effective radar footprint) of our transmitted pulses. At a frequency of 7 MHz and with the typical range of the glacier bed from the radar (~100-600 m, mean of ~160 m), the Fresnel zone has a radius of approximately 30-80 m (mean ~40 m). In the vertical, the range resolution of the picked surface and bed is nominally a quarter wavelength (~7 m), but the 'optimal vertical resolution' (the resolvable range to a single discrete, prominent reflector (King 2020)) is ~1 m, and the 'practical vertical precision' for such horizons is ~2 m at this frequency (Pritchard, King et al. 2020). This implies that the practical vertical precision in thickness is the combination in quadrature of these two precisions, i.e., ~2.8 m. The absolute accuracy of the thickness is subject to the accuracy of our assumed radar velocity in ice (0.168m/ns) with which we convert two-way radar travel times to ice thicknesses, and this is somewhat dependent on the unknown and potentially variable depth-averaged glacier water content. A range of velocities from 0.165 to 0.172 m/ns has, for example, been employed for temperate and cold ice above and below the equilibrium line of an alpine glacier (Macheret, Moskalevsky et al. 1993). This range of velocities implies a difference in ice thickness of approximately +/-2% for our survey (equivalent to a change in mean thickness from 139 m when using a velocity of 0.168 m ns-1 to between 137 m and 142 m for the reasonable range of velocities). Given the dependence on water content, this could be manifest as a thickness bias that varies broadly with altitude, with our results potentially too thick by up to 2% at lower (warmer) altitudes, too thin by up to 2% at higher (colder) altitudes. Potentially more significant bias (e.g., tens of metres) could result from mistaking a non-bed reflection horizon for the bed, which we sought to avoid with our clutter modelling. To assess the consistency of our picked thickness measurements, we quantified the difference in thickness at 79 flightline crossovers. The mean absolute crossover difference was 9 m and the mean relative difference was 7% of thickness (median 6 m and 5%) (Table 1). We also compared our airborne survey results to previous ground-based radar surveys on Khumbu (Gades, Conway et al. 2000) and Ngozumpa glaciers (Pritchard, King et al. 2020). On Khumbu Glacier, seven radar cross profiles were surveyed in 1999 over the glacier tongue below the Khumbu Icefall, totalling 3.3 km in length (Gades, Conway et al. 2000). Of these, two lines crossed within ~200 m horizontally of two of our successfully surveyed cross profiles. While the earlier ground-based survey achieved profile lengths of ~500 m each, spanning most of the glacier width, we were only able to pick the bed over around 70 m of our profiles at each location. Although these surveys differ in date, method and exact location, the thicknesses reported by both surveys are similar: we measured maximum thicknesses of 445 m close to line P and 440 m close to line BC, compared to maxima of ~370 +/- 20 m (line P) and 440 +/- 20 m (line BC) in the previous study (Pritchard, King et al. 2020). A thickness of inferior or egual to 450 +/- 70 m close to these lines was also observed by a terrestrial gravity survey in 1976 (Moribayashi 1978). ____________________________________________ Crossover summary | Mean | SD | Median | Max | ____________________________________________ Relative difference (%) | 7% | 7% | 5% | 30% | ____________________________________________ Absolute difference (m) | 9 | 9 | 6 |51 | ____________________________________________ Table 1 | Statistics thickness differences at 79 flightline crossovers. On Ngozumpa Glacier, we also compared our airborne survey results to an earlier ground-based radar survey that collected 5.1 line-km of data in 2016 (Pritchard, King et al. 2020). We used the ground survey in some cases to help avoid erroneous bed picks in the airborne survey radargrams, where clutter 'horizons' made bed detection ambiguous, but the thickness distributions of these datasets are otherwise independent. For four zones where both surveys have extensive, though non-identical, coverage (Table 2, Figure 10), this comparison shows close similarity between both the means (-13 m to +8 m difference, with a weighted mean difference of ~0.2 m) and standard deviations (2-7 m difference) of thickness in these zones. The variation in sign of the thickness differences between these datasets suggests that there is no systematic bias between the surveys. In summary, this assessment suggests that our survey data suffer from little systematic bias (typically < 2%) and have a precision that we estimate as around +/-7% of thickness (+/-10 m for the mean thickness of 136 m). Local inaccuracies can reach ~30% of ice thickness. ______________________________________________________________________________ Data source | Mean thickness (m) | Standard Deviation | n | Thickness difference (m)(%)| ______________________________________________________________________________ Zone 1 - ground | 345 | 28 |612 |0| Zone 1 - air |345 |21 |578 |0| Zone 2 - ground |258 |13 |471 |+8 (3%)| Zone 2 - air |266 |15 |1727 |+8 (3%)| Zone 3 - ground |174 |15 |133 |0| Zone 3 -air |174 |13 |475 |0| Zone 4 - ground |140 |12 |262 |-13 (10%)| Zone - air |127 |10 |996 |-13 (10%)| _________________________________________________________________________________ Table 2 | Comparison of thickness statistics between samples of ground-based (Pritchard, King et al. 2020) and airborne survey results from zones 1-4 on Ngozumpa Glacier. (Note that we combine the results from this ground survey with those from our airborne survey in our Khumbu Himal thickness dataset (this data archive)). |
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| Lineage/Methodology: | A full description of this project can be found in Pritchard et al. (in review). * Airborne survey* We used a wide band mono-pulse dipole radar with a centre frequency of 7 MHz (Pritchard, King et al. 2020) for this survey. Between 27th October and 6th November 2019, we deployed our radar platform to survey the glaciers of Nepal's Khumbu Himal (Everest area) in the upper Dudh Koshi river basin. Our survey flights covered >200 line-km spanning altitudes of 3700 m to 6700 m (Pritchard et al., in review). Based on the findings of Pritchard, King et al. (2020), we designed our survey patterns to include multiple glacier cross profiles because these are less prone to ambiguity between radar returns from the glacier bed and valley side walls. Our flightlines typically followed a continuous zig-zag path with crossings spaced at ~800 m over each glacier trunk for the up-glacier survey limb, with these crossings subsequently linked by a central glacier long-profile on descent. To minimise radar spreading losses, surveys were flown with the radar platform as close as safely possible to the glacier surface, typically a few metres to tens of metres given the considerable roughness of the glacier surfaces in this area. Reaching the highest section of the survey (Everest's Western Cwm), however, required a spiralling rather than direct ascent over the Khumbu Icefall and so achieved multiple glacier crossings at a wider range of ground clearances. To ensure dense radar sampling, we flew these glacier profiles as slowly as was practicable (typically ~10 m s-1 (36 km h-1)). Transit flights to and from the glaciers were at higher speeds of up to ~40 m s-1 (140 km h-1). *Raw radar data * We collected a raw radar data file for each survey flight. The filename format gives the date and time of file creation as yyyymmddhhmmss.hdf5, e.g., 20191103021438.hdf5. File contents: Each file contains two channels of radar data as recorded by the digitiser in the radar receiver system. Channel A is amplified, Channel B unamplified. For each channel, there are multiple Traces, numbered sequentially (e.g., Trace00001). Each trace records a series of radar receiver signed voltages as a measure of returning signal strength. Channel metadata: The total duration of each trace (and therefore its range, in number of samples) is given by the NoOfSamples parameter in the channel metadata. Each sample has a duration of 2 nanoseconds, hence a trace with 10152 samples is 20304 ns long (a range of around 1700 m in ice, or 3000 m in air). The 'SampleRate' parameter gives the timeout time (in seconds) for the receiver to wait to detect a returning pulse before assuming that triggering has failed and moving on to the next set. Each trace represents the averaged voltages of the number of independent radar pulses given by the 'Stacks' parameter. 'Repeats' is an internal system parameter that sets the number of samples to store before writing to disk. The GPS time is recorded along with the corresponding file start and end 'system' times for the onboard computer, to allow the system timestamps to be synchronised to the GPS data in post processing. Trace metadata: In each file, Trace00001 metadata shows the number format (Type) and the precise system date and time (yyyy,mm,dd,hh,mm,ss.ssssss). The 'GGA' string reports the GPS time at completion of this trace as hhmmss.s (e.g., 082520.8) and the GPS position at that time (ddmm.mmmmm, N/S, dddmm.mmmmm, E/W) (e.g., 2748.34269,N,08641.95129,E means 27deg 48.34269' N, 086deg 41.95129' E). A new system time and GPS time and position is then stored for every 1000th subsequent trace, hence for trace 1001, 2001 etc. This is because GPS data could not be written to disk at the same rate as the trace creation. High frequency, high precision GPS times and positions were stored internally on the GPS, however, and matched to trace times in post-processing. GPS survey data We provide our processed, high frequency, high precision GPS survey data in csv format. Each file contains a Precise Point Position (PPP) differentially processed GPS position and height for each radar trace. The filename format (e.g., 3NOV19F2_coords.csv): gives the date of data collection as ddmmyy (e.g., 3rd November 2019) and the flight number for that day (e.g., flight 2). The records contain an X-coordinate, Y-coordinate and altitude for each trace, all in metres. The coordinate system is UTM45N (Zone 45R) with geodetic datum WGS84. *Processed radar data * The details of our radar processing chain are described in Pritchard et al. (in review). For each processed radar line there are three files: - Files with extension ".SGY" are in SEG-Y format (see e.g., https://library.seg.org/seg-technical-standards) and contain the processed radargrams. - Files with extension "_BED.PCK" are text files of picked bed locations from the radargrams in the ReflexW format. PCK text file column headers are: *col1: trace number *col2: distance along profile (m) *col3: set to 0 *col4: bed pick coordinate x UTM45R (m) *col5: bed pick coordinate_y UTM45R (m) *col6: bed pick elevation (m) *col7: bed pick coordinate x UTM45R (m) *col8: bed pick coordinate_y UTM45R (m) *col9: bed pick elevation (m) *col10: bed pick radar range (ns) *col11: bed pick radar range (m) *col12: bed pick radar voltage (v) - Files with extension ".PFL.txt" are text files recording the processing flow from proprietary software ReflexW that we used to process that line (to interpret this, refer to the freely available software manual and associated guides: https://www.sandmeier-geo.de/guides-and-videos.html. The filename format (e.g., 3NOV19F2_P32): gives the date of data collection as ddmmyy (e.g., 3rd November 2019), the flight number for that day (e.g., flight 2) and the processing step for each file (e.g., 32). Clutter model used to support bed picking in the processed radargrams We developed and employed a radar clutter model to help identify and avoid picking terrain clutter in our radargrams (see 'Related datasets' from the Reference section). The details of our clutter modelling are described in Pritchard et al. (in review). *Geolocated ice thicknesses* We provide a csv file of our final, geolocated ice thickness values interpreted from the survey data, along with associated data columns discussed in Pritchard et al. (in review). Filename: Pritchard_BedmapHimalayas_picked_ice_thickness.csv Column definitions: - trajectory_id: Code identifying the survey data file used for each point, by survey date (e.g., 6NOV19 refers to the 6th November 2019), flight number from that day (e.g., F2 is flight 2) and processing step (e.g., P93). - survey: Either "Helicopter October/November 2019" or "Ground March/April 2015/16", referring to the 2019 airborne survey reported here (Pritchard et al., in review) or an earlier (2015/16) ground-based reconnaissance survey (Pritchard et al., 2020). - land_ice_thickness (m): Surveyed ice thickness (m). - Shean_surface_altitude_DEM (m): Surface elevation from a Digital Elevation Model (Shean et al., 2017) (m above WGS 84). - bedrock_altitude (m): Shean_surface_altitude_DEM (m) (where available) minus land_ice_thickness (m) (m above WGS 84). - Millan_land_ice_thickness (m): Ice thickness (m) from model product Millan et al. (2022). - Millan_thickness_uncertainty (m): Uncertainty in ice thickness (m) from model product Millan et al. (2022). - Rowan_land_ice_thickness (m): Ice thickness (m) from model product Rowan and Egholm (2021). - Farinotti_land_ice_thickness (m): Ice thickness (m) from model product Farinotti et al. (2021). - Millan_ice_difference (m): Difference in ice thickness (m) between our surveyed measurements (land_ice_thickness (m)) and Millan et al. (2022) modelled thickness. - Rowan_ice_difference (m): Difference in ice thickness (m) between our surveyed measurements (land_ice_thickness (m)) and Rowan et al. (2021) modelled thickness. - Farinotti_ice_difference (m): Difference in ice thickness (m) between our surveyed measurements (land_ice_thickness (m)) and Farinotti et al. (2021) modelled thickness. - Gardner_surface_flow_rate (m/year): Surface flow rate (m per year) from Gardner et al. (2022). - Gardner_surface_flow_rate_dvdt (m/year/decade): Change in surface flow rate (m per year per decade) from Gardner et al. (2022). - Jarvis_surface_slope (degrees): Surface slope (degrees) from Jarvis et al. (2008). - Farinotti (percent): Farinotti et al. (2021) modelled ice thickness as a % of our surveyed measurements (land_ice_thickness (m)). - Millan (percent):Millan et al. (2021) modelled ice thickness as a % of our surveyed measurements (land_ice_thickness (m)). - latitude (degree_north): Latitude (DD.DDDDDD). - longitude (degree_east):Longitude (DD.DDDDDD). |
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| Temporal Coverage: | |
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| Start Date | 2019-10-27 |
| End Date | 2019-11-06 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 27.83 |
| Northernmost | 28.1 |
| Longitude | |
| Westernmost | 86.5 |
| Easternmost | 87 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Data Resolution: | |
| Latitude Resolution | N/A |
| Longitude Resolution | N/A |
| Horizontal Resolution Range | 1 meter - < 30 meters |
| Vertical Resolution | N/A |
| Vertical Resolution Range | 10 meters - < 30 meters |
| Temporal Resolution | N/A |
| Temporal Resolution Range | N/A |
| Location: | |
| Location | Nepal |
| Detailed Location | Khumbu Himal |
| Location | Nepal |
| Detailed Location | Upper Dudh Khosi river basin |
| Source(s): |
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| Data Collection: | Instrumentation: -The wide band mono-pulse dipole radar (centre frequency of 7 MHz) that we used in this survey was built by the British Antarctic Survey and is known as 'DELORES'. -We processed the radar data in Reflex-Win Version 10.1. -The clutter model was written in python and is described and archived here:Recinos, B., Goldberg, D. N., Boyle, D., & Pritchard, H. (2025). bearecinos/radar-declutter: First radar-declutter release (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.15488954 |
| Distribution: | |
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| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 107 GB |
| Distribution Format | HDF |
| Fees | N/A |
| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 16 MB |
| Distribution Format | ASCII |
| Fees | N/A |
| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 4.57 GB |
| Distribution Format | N/A |
| Fees | N/A |
| Data Storage: | This data consists of: * Raw radar data: 61 files in .hdf5 format totalling 107 GB. * Processed radargrams: 27 files in SEG-Y format totalling 4.62 GB. * Bed picks: 27 text files totalling 13 MB * Processing flow metadata: 27 text files totalling 21 KB * Processed GPS data: 8 files in .csv format totalling 16 MB. |