Satellite records show a decline in ice extent over more than three decades, with a record minimum in September 2012. Results from the Pan‐Arctic Ice‐Ocean Modelling and Assimilation system (PIOMAS) suggest that the decline in extent has been accompanied by a decline in volume, but this has not been confirmed by data. Using new data from the European Space Agency CryoSat‐2 (CS‐2) mission, validated with in situ data, we generate estimates of ice volume for the winters of 2010/11 and 2011/12. We compare these data with current estimates from PIOMAS and earlier (2003–8) estimates from the National Aeronautics and Space Administration ICESat mission. Between the ICESat and CryoSat‐2 periods, the autumn volume declined by 4291 km3 and the winter volume by 1479 km3. This exceeds the decline in ice volume in the central Arctic from the PIOMAS model of 2644 km3 in the autumn, but is less than the 2091 km3 in winter, between the two time periods.

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Abstract. The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center.

Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air-ice and ice-ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air-ice and ocean-ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

[1] We utilize satellite laser altimetry data from NASA's Ice, Cloud, and land Elevation Satellite (ICESat) combined with passive microwave measurements to analyze basin-wide changes in Antarctic sea ice thickness and volume over a 5 year period from [2003][2004][2005][2006][2007][2008]. Sea ice thickness exhibits a small negative trend while area increases in the summer and fall balanced losses in thickness leading to small overall volume changes. Using a 5 year time series, we show that only small ice thickness changes of less than À0.03 m/yr and volume changes of À266 km 3 /yr and 160 km 3 /yr occurred for the spring and summer periods, respectively. These results are in stark contrast to the much greater observed losses in Arctic sea ice volume and illustrate the different hemispheric changes of the polar sea ice covers in recent years. The uncertainties in the calculated thickness and volume trends are large compared to the observed basin-scale trends. This masks the determination of a long-term trend or cyclical variability in the sea ice cover. It is found that lengthening of the observation time series along with better determination of the interannual variability of sea ice and snow densities will allow for a more statistically significant determination of long-term sea ice thickness and volume trends in the Southern Ocean.

Abstract.We develop a physical model capable of simulating the mean echo power of CryoSat-2 SAR-and SARInmode waveforms over sea-ice-covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surface elevation of both sea ice floes and leads. The physical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of lookup tables and a bounded trust region Newton least-squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retracking methods, which are here shown to be sensitive to the combined effect of bandwidth-limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement; however consistent assumptions about the snow depth and density of sea ice were not used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform-fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. The purpose of the comparison is to highlight the physical basis between differences in the retracking methods. For three IceBridge campaign periods from March 2011 to March 2013, mean differences (CryoSat-2 -IceBridge) of 0.144 and 1.351 m are found between the freeboard and thickness retrievals, respectively, using a 50 % sea ice floe threshold retracker, while mean differences of 0.019 and 0.182 m are found when using the waveform-fitting method. This suggests the waveformfitting technique is capable of better reconciling the sea ice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions.

Snow plays a key role in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from cold air temperatures, slowing sea ice growth. From spring to summer, the albedo of snow determines how much insolation is absorbed by the sea ice and underlying ocean, impacting ice melt processes. Knowledge of the contemporary snow depth distribution is essential for estimating sea ice thickness and volume, and for understanding and modeling sea ice thermodynamics in the changing Arctic. This study assesses spring snow depth distribution on Arctic sea ice using airborne radar observations from Operation IceBridge for 2009-2013. Data were validated using coordinated in situ measurements taken in March 2012 during the Bromine, Ozone, and Mercury Experiment (BROMEX) field campaign. We find a correlation of 0.59 and root-mean-square error of 5.8 cm between the airborne and in situ data. Using this relationship and IceBridge snow thickness products, we compared the recent results with data from the 1937, 1954-1991 Soviet drifting ice stations. The comparison shows thinning of the snowpack, from 35.1 6 9.4 to 22.2 6 1.9 cm in the western Arctic, and from 32.8 6 9.4 to 14.5 6 1.9 cm in the Beaufort and Chukchi seas. These changes suggest a snow depth decline of 37 6 29% in the western Arctic and 56 6 33% in the Beaufort and Chukchi seas. Thinning is negatively correlated with the delayed onset of sea ice freezeup during autumn.

[1] We show the first results of a large-scale survey of snow depth on Arctic sea ice from NASA's Operation IceBridge snow radar system for the 2009 season and compare the data to climatological snow depth values established over the 1954-1991 time period. For multiyear ice, the mean radar derived snow depth is 33.1 cm and the corresponding mean climatological snow depth is 33.4 cm. The small mean difference suggests consistency between contemporary estimates of snow depth with the historical climatology for the multiyear ice region of the Arctic. A 16.5 cm mean difference (climatology minus radar) is observed for first year ice areas suggesting that the increasingly seasonal sea ice cover of the Arctic Ocean has led to an overall loss of snow as the region has transitioned away from a dominantly multiyear ice cover.