Pritchard et al. (2026) Towards Bedmap Himalayas: a new airborne glacier thickness survey in Khumbu Himal, Nepal

Identification

• Journal: Earth system science data
• Year: 2026
• Date: 2026-01-07
• Authors: Hamish D. Pritchard, Edward C. King, David J. Goodger, Douglas Boyle, Daniel Goldberg, Beatriz Recinos, Andrew Orr, Dhananjay Regmi
• DOI: 10.5194/essd-18-199-2026

Research Groups

• British Antarctic Survey, Cambridge, UK
• University of Cambridge, Cambridge, UK
• School of GeoSciences, University of Edinburgh, Edinburgh, UK
• Himalayan Research Centre, Kathmandu, Nepal

Short Summary

This study presents a new, extensive dataset of glacier thickness for eleven glaciers in the Khumbu Himal, Nepal, collected using a novel helicopter-borne radar system. This dataset, spanning 119 line-kilometres, approximately doubles the existing thickness measurements in High Mountain Asia and reveals significant systematic biases in current glacier thickness models, highlighting the need for improved model calibration.

Objective

• To generate a new, extensive, and precise glacier thickness dataset for the Khumbu Himal, Nepal, using a novel helicopter-borne low-frequency radar system.
• To assess the performance of existing global and regional glacier thickness models against this new observational dataset to identify biases and improve model skill for more accurate ice reserve estimations and future ice loss projections in High Mountain Asia.

Study Configuration

• Spatial Scale: Eleven glaciers in the Khumbu Himal, Nepal (Everest area), within the upper Dudh Koshi river basin, covering a total area of 240 km². The survey covered 119 line-kilometres, with measurements taken at surface altitudes ranging from 4670 m to 6311 m.
• Temporal Scale: Airborne radar survey conducted from 27 October to 6 November 2019. Model comparisons were made against products representing years 2000–2010 (Farinotti), 2011 (Rowan), and 2017/2018 (Millan).

Methodology and Data

• Models used:
  • Data processing: Custom-developed terrain clutter model for distinguishing bed signals from surface scattering.
  • Comparison: Rowan (plastic ice flow law, observed surface slope, estimated basal shear stress), Millan (shallow-ice-approximation, observed surface slope and flow rate), Farinotti (ensemble of up to five thickness models including mass conservation and empirical approaches).
• Data sources:
  • Primary: Helicopter-borne low-frequency (7 MHz center frequency) mono-pulse dipole radar system (custom-built, 20 m antennas) for ice thickness measurements.
  • Geolocation: Dual-frequency GPS units on the radar frame, backed up by single-frequency GPS from GoPro cameras.
  • Ancillary: Digital Elevation Models (DEMs), Randolph Glacier Inventory (RGI) for glacier outlines, ITS_LIVE for glacier surface velocities.
  • Validation: Previous ground-based radar surveys (Gades et al., 2000; Pritchard et al., 2020) and a terrestrial gravity survey (Moribayashi, 1978).

Main Results

• A total of 119 line-kilometres of ice thickness data were successfully collected across eleven glaciers in the Khumbu Himal, approximately doubling the combined length of all previous thickness surveys in High Mountain Asia.
• Measured ice thicknesses reached up to 445 m, with a precision estimated at approximately ±7% (±10 m for the mean thickness of 136 m) and a horizontal resolution of approximately 40 m.
• The developed terrain clutter model effectively aided in distinguishing true glacier bed reflections from complex terrain clutter in the radargrams.
• Comparison with existing glacier thickness models (Rowan, Millan, Farinotti) revealed widespread systematic biases:
  • Mean biases were small across the entire dataset (11 m thick bias for Millan, 5 m thin bias for Farinotti), but individual glacier biases were substantial (e.g., 55 m thick bias for Millan on Lhotse Glacier, 50 m thin bias for Farinotti on Khumbu Glacier).
  • Models consistently overestimated the thickness of thin ice and underestimated the thickness of thick ice.
  • Biases showed coherent spatial patterns, indicating that models struggle to accurately represent ice distribution in complex, steep, and rapidly changing Himalayan glaciers, particularly in their lower, often stagnant, tongues.

Contributions

• Provides a uniquely extensive and high-precision observational dataset of glacier thickness for the Khumbu Himal, a region critically lacking such data, significantly advancing the understanding of ice reserves in High Mountain Asia.
• Demonstrates the efficacy of a novel, portable, low-frequency helicopter-borne radar system and an accompanying terrain clutter model for surveying remote, high-altitude, and debris-covered mountain glaciers.
• Offers a crucial benchmark for validating and improving existing glacier thickness models, revealing their systematic biases and limitations in complex glaciological settings.
• Facilitates more accurate estimations of current glacier ice reserves and more reliable projections of future ice loss, which are vital for water resource management for downstream populations.

Funding

• Natural Environment Research Council (NERC) grants (NE/X005267/1 and NE/R000107/1).
• British Antarctic Survey (BAS) capital funding.

Citation

@article{Pritchard2026Towards,
  author = {Pritchard, Hamish D. and King, Edward C. and Goodger, David J. and Boyle, Douglas and Goldberg, Daniel and Recinos, Beatriz and Orr, Andrew and Regmi, Dhananjay},
  title = {Towards Bedmap Himalayas: a new airborne glacier thickness survey in Khumbu Himal, Nepal},
  journal = {Earth system science data},
  year = {2026},
  doi = {10.5194/essd-18-199-2026},
  url = {https://doi.org/10.5194/essd-18-199-2026}
}