Arctic sea ice freeboard from AltiKa and comparison with CryoSat‐2 and Operation IceBridge

Abstract

Satellite radar altimeters have improved our knowledge of Arctic sea ice thickness over the past decade. The main sources of uncertainty in sea ice thickness retrievals are associated with inadequate knowledge of the snow layer depth and the radar interaction with the snow pack. Here we adapt a method of deriving sea ice freeboard from CryoSat‐2 to data from the AltiKa Ka band radar altimeter over the 2013–14 Arctic sea ice growth season. AltiKa measures basin‐averaged freeboards between 4.4 cm and 6.9 cm larger than CryoSat‐2 in October and March, respectively. Using airborne laser and radar measurements from spring 2013 and 2014, we estimate the effective scattering horizon for each sensor. While CryoSat‐2 echoes penetrate to the ice surface over first‐year ice and penetrate the majority (82 ± 3%) of the snow layer over multiyear ice, AltiKa echoes are scattered from roughly the midpoint (46 ± 5%) of the snow layer over both ice types.

Satellite‐observed drop of Arctic sea ice growth in winter 2015–2016

“…The interannual variability of ice mass balance from radar altimetry may be impacted by the currently unknown interannual variability of the snow depth and its potential influence on freeboard retrieval [ Ricker et al , ; Armitage and Ridout , ]. The partially high thickness and volume uncertainties reflect these error sources, and together with the short observation record, they compromise the statistical significance of the thickness and volume anomalies.…”

“…The SMOS retrieval, on the other hand, can contribute valuable information, especially in regions with uncertain snow depth estimates. We also note that CS2 thickness retrievals, which alone contribute to the MYI thickness, may be substantially biased in regions with a thick snow cover due to snow volume scattering [ Kwok , ; Ricker et al , ; Armitage and Ridout , ]. Both retrievals leave a data gap between mid‐April and October due to the limitation of the CS2 and SMOS thickness retrieval algorithms during the melt season [ Ricker et al , ].…”

The NASA Eulerian Snow on Sea Ice Model (NESOSIM): Initial model development and analysis

“…Armitage andRidout, 2015, Guerreiro et al, 2016;Kwok and Markus, 2017), although this approach is still in its infancy and has limited temporal coverage.…”

Evaluation of Operation IceBridge quick‐look snow depth estimates on sea ice

“…However, in 2009 as a result of the introduction of NASA's Operation IceBridge (OIB), high-resolution airborne estimates of snow depth on sea ice over both, seasonal first-year ice (FYI) and multiyear ice (MYI) in the western Arctic, have become available during the months of March and April [Koenig et al, 2010;Kurtz et al, 2013]. This expansive data set has been used to characterize Arctic distributions of snow on sea ice [Kurtz and Farrell, 2011;Webster et al, 2014], validate satellite retrieval products [Brucker and Markus, 2013;Maass et al, 2015;Armitage and Ridout, 2015] and initialize sea ice forecasting models [Lindsay et al, 2012].…”