Remote Sensing (Jun 2022)

Arctic Sea-Ice Surface Elevation Distribution from NASA’s Operation IceBridge ATM Data

  • Donghui Yi,
  • Alejandro Egido,
  • Walter H. F. Smith,
  • Laurence Connor,
  • Christopher Buchhaupt,
  • Dexin Zhang

DOI
https://doi.org/10.3390/rs14133011
Journal volume & issue
Vol. 14, no. 13
p. 3011

Abstract

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In this paper, we characterize the sea-ice elevation distribution by using NASA’s Operation IceBridge (OIB) Airborne Topographic Mapper (ATM) L1B data over the Arctic Ocean during 94 Spring campaigns between 2009 and 2019. The ultimate objective of this analysis is to better understand sea-ice topography to improve the estimation of the sea-ice freeboard for nadir-looking altimeters. We first introduce the use of an exponentially modified Gaussian (EMG) distribution to fit the surface elevation probability density function (PDF). The characteristic function of the EMG distribution can be integrated in the modeling of radar altimeter waveforms. Our results indicate that the Arctic sea-ice elevation PDF is dominantly positively skewed and the EMG distribution is better suited to fit the PDFs than the classical Gaussian or lognormal PDFs. We characterize the elevation correlation characteristics by computing the autocorrelation function (ACF) and correlation length (CL) of the ATM measurements. To support the radar altimeter waveform retracking over sea ice, we perform this study typically on 1.5 km ATM along-track segments that reflect the footprint diameter size of radar altimeters. During the studied period, the mean CL values range from 20 to 30 m, which is about 2% of the radar altimeter footprint diameter (1.5 km).

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