Airborne Investigation of Quasi-Specular Ku-Band Radar Scattering for Satellite Altimetry Over Snow-Covered Arctic Sea Ice

Claude De Rijke-Thomas*, Jack C. Landy, Robbie Mallett, Rosemary C. Willatt, Michel Tsamados, Joshua King

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Surface-based Ku-band radar altimetry investigations indicate that the radar signal is typically backscattered from well above the snow–sea ice interface. However, this would induce a bias in satellite altimeter sea ice thickness retrievals not reflected by buoy validation. Our study presents a mechanism to potentially explain this paradox: probabilistic quasi-specular radar scattering from the snow–ice interface. We introduce the theory for this mechanism before identifying it in airborne Ku-band radar observations collected over landfast first-year Arctic sea ice near Eureka, Canada, in spring 2016. Based on synthetic aperture radar (SAR) data, this study area likely represents the level first-year sea ice across the Arctic. Radar backscatter from the snow and ice interfaces was estimated by coaligning laser scanner and radar observations with in situ measurements. On average, four to five times more radar power was scattered from the snow–ice interface than the air–snow interface over first-year ice. However, return power varied by up to 20 dB between consecutive radar echoes, particularly from the snow–ice interface, depending on local slope and roughness. Measured laser-radar snow depths were more accurate when radar returns were specular, but there was no systematic bias between airborne and in situ snow depths. The probability and strength of quasi-specular returns depend on the measuring height above and slope distribution of sea ice, so these findings have implications for satellite altimetry snow depth and freeboard estimates. This mechanism could explain the apparent differences in Ku-band radar penetration into snow on sea ice when observed from the range of a surface-, airborne-, or satellite-based sensor.
Original languageEnglish
Article number2004919
Pages (from-to)1-19
Number of pages19
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume61
Early online date22 Sept 2023
DOIs
Publication statusPublished - 2023
Externally publishedYes

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