The Arctic sea ice cover is rapidly shrinking, but a direct, longer-term assessment of the ice thinning remains challenging. A new time series constructed from in situ measurements of sea ice thickness at the end of the melt season in Fram Strait shows a thinning by over 50% during [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. The modal and mean ice thickness along 79 • N decreased at a rate of 0.3 and 0.2 m yr −1 , respectively, with long-term averages of 2.5 and 3 m. Airborne observations reveal an east-west thickness gradient across the strait in spring but not in summer due to advection from more different source regions. There is no clear relationship between interannual ice thickness variability and the source regions of the ice. The observed thinning is therefore likely a result of Arctic-wide reduction in ice thickness with a potential shift in exported ice types playing a minor role.

The understanding of sea ice mass balance processes requires continuous monitoring of the seasonal evolution of the ice thickness. While autonomous ice mass balance (IMB) buoys deployed over the past two decades have contributed to scientists' understanding of ice growth and decay processes, deployment has been limited, in part, by the cost of such systems. Routine, basinwide monitoring of the ice cover is realistically achievable through a network of reliable and affordable autonomous instrumentation. This paper describes the development of a novel autonomous platform and sensor that replaces the traditional thermistor strings for monitoring temperature profiles in the ice and snow using a chain of inexpensive digital temperature chip sensors linked by a single-wire data bus. By incorporating a heating element into each sensor, the instrument is capable of resolving material interfaces (e.g., air-snow and ice-ocean boundaries) even under isothermal conditions. The instrument is small, low cost, and easy to deploy. Field and laboratory tests of the sensor chain demonstrate that the technology can reliably resolve material boundaries to within a few centimeters. The discrimination between different media based on sensor thermal response is weak in some deployments and efforts to optimize the performance continue.

In April 2017, we collected unique, extensive in situ data of sea ice and snow thickness. At 10 sampling sites, located under a CryoSat‐2 overpass, between Ellesmere Island and 87.1°N mean and modal total ice thicknesses ranged between 2 to 3.4 m and 1.8 to 2.9 m, respectively. Coincident snow thicknesses ranged between 0.3 to 0.47 m (mean) and 0.1 to 0.5 m (mode). The profile spanned the complete multiyear ice zone in the Lincoln Sea, into the first‐year ice zone farther north. Complementary snow thickness measurements near the North Pole showed a mean thickness of 0.31 m. Compared with scarce measurements from other years, multiyear ice was up to 0.75 m thinner than in 2004, but not significantly different from 2011 and 2014. We found excellent agreement with a commonly used snow climatology and with published long‐term ice thinning rates. There was reasonable agreement with CryoSat‐2 thickness retrievals.

There is mounting evidence that multiyear ice (MYI) is a unique component of the Arctic Ocean and may play a more important ecological role than previously assumed. This study improves our understanding of the potential of MYI as a suitable habitat for sea ice algae on a pan-Arctic scale. We sampled sea ice cores from MYI and first-year sea ice (FYI) within the Lincoln Sea during four consecutive spring seasons. This included four MYI hummocks with a mean chl a biomass of 2.0 mg/m 2 , a value significantly higher than FYI and MYI refrozen ponds. Our results support the hypothesis that MYI hummocks can host substantial ice-algal biomass and represent a reliable ice-algal habitat due to the (quasi-) permanent lowsnow surface of these features. We identified an ice-algal habitat threshold value for calculated light transmittance of 0.014%. Ice classes and coverage of suitable ice-algal habitat were determined from snow and ice surveys. These ice classes and associated coverage of suitable habitat were applied to pan-Arctic CryoSat-2 snow and ice thickness data products. This habitat classification accounted for the variability of the snow and ice properties and showed an areal coverage of suitable icealgal habitat within the MYI-covered region of 0.54 million km 2 (8.5% of total ice area). This is 27 times greater than the areal coverage of 0.02 million km 2 (0.3% of total ice area) determined using the conventional block-model classification, which assigns single-parameter values to each grid cell and does not account for subgrid cell variability. This emphasizes the importance of accounting for variable snow and ice conditions in all sea ice studies. Furthermore, our results indicate the loss of MYI will also mean the loss of reliable ice-algal habitat during spring when food is sparse and many organisms depend on ice-algae. K E Y W O R D SCryoSat-2, habitat classification, hockey stick regression, light transmittance, piecewise regression, sea ice algae, sea ice bio-optics, the Last Ice AreaThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.