Retrieval of Snow Depth on Arctic Sea Ice From Surface-Based, Polarimetric, Dual-Frequency Radar Altimetry

  • Rosemary Willatt*
  • , Julienne C. Stroeve
  • , Vishnu Nandan
  • , Thomas Newman
  • , Robbie Mallett
  • , Stefan Hendricks
  • , Robert Ricker
  • , James Mead
  • , Polona Itkin
  • , Rasmus Tonboe
  • , David N. Wagner
  • , Gunnar Spreen
  • , Glen Liston
  • , Martin Schneebeli
  • , Daniela Krampe
  • , Michel Tsamados
  • , Oguz Demir
  • , Jeremy Wilkinson
  • , Matthias Jaggi
  • , Lu Zhou
  • Marcus Huntemann, Ian A. Raphael, Arttu Jutila, Marc Oggier
*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Abstract Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry-derived sea ice thickness. During winter of the MOSAiC Expedition, the “KuKa” dual-frequency, fully polarized Ku- and Ka-band radar was deployed in “stare” nadir-looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dual-frequency, dual-polarization and waveform shape, and compared to independent snow depth measurements. Novel dual-polarization approaches yielded r2 values up to 0.77. Mean snow depths agreed within 1 cm, even for data sub-banded to CryoSat-2 SIRAL and SARAL AltiKa bandwidths. Snow depths from co-polarized dual-frequency approaches were at least a factor of four too small and had a r2 0.15 or lower. r2 for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters.
Original languageEnglish
Article numbere2023GL104461
JournalGeophysical Research Letters
Volume50
Issue number20
Number of pages11
ISSN0094-8276
DOIs
Publication statusPublished - 2023

Keywords

  • Sea ice
  • Snow
  • Radar
  • Altimetry
  • Polarimetric
  • Climate

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