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We estimate the snow depth and snow freeboard of Antarctic sea ice using a comprehensive retrieval method (referred to as CryoSat-2 Waveform Fitting for Antarctic sea ice, or CS2WFA) consisting of a physical waveform model and a waveform-fitting process that fits modeled waveforms to CryoSat-2 data. These snow depth and snow freeboard estimates are combined with snow, sea ice, and sea water density values to calculate the sea ice thickness and volume over an 11+ year span between 2010 and 2021. We first compare our snow freeboard, snow depth, and sea ice thickness estimates to other altimetry- and ship-based observations and find good agreement overall in both along-track and monthly gridded comparisons. Some discrepancies exist in certain regions and seasons that are theorized to come from both sampling biases and the differing assumptions in the retrieval methods. We then present an 11+ year time series of sea ice thickness and volume both regionally and pan-Antarctic. This time series is used to uncover intra-decadal changes in the ice cover between 2010 and 2021, showing small, competing regional thickness changes of less than 0.5 cm yr−1 in magnitude. Finally, we place these thickness estimates in the context of a longer-term, snow freeboard-derived, laser–radar sea ice thickness time series that began with NASA's Ice, Cloud, and land Elevation Satellite (ICESat) and continues with ICESat-2 and contend that reconciling and validating this longer-term, multi-sensor time series will be important in better understanding changes in the Antarctic sea ice cover.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

We present an analysis of Arctic sea ice topography using high-resolution, three-dimensional surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009 to 2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by ice type to estimate the topographic variability across first-year and multi-year ice regimes. \ud \ud The results demonstrate that Arctic sea ice topography exhibits significant spatial variability, mainly driven by the increased surface feature height and volume (per unit area) of the multi-year ice that dominates the Central Arctic region. The multi-year ice topography exhibits greater interannual variability compared to the first-year ice regimes, which dominates the total ice topography variability across both regions. The ice topography also shows a clear coastal dependency, with the feature height and volume increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. A strong correlation between ice topography and ice thickness (from the IceBridge sea ice product) is found, using a square-root relationship. The results allude to the importance of ice deformation variability in the total sea ice mass balance, and provide crucial information regarding the tail of the ice thickness distribution across the western Arctic. Future research priorities associated with this new data set are presented and discussed, especially in relation to calculations of atmospheric form drag.

We evaluate Operation IceBridge (OIB) ‘quick-look’ (QL) snow depth on sea ice retrievals using in situ measurements taken over immobile first-year ice (FYI) and multi-year ice (MYI) during March of 2014. Good agreement was found over undeformed FYI (-4.5 cm mean bias) with reduced agreement over deformed FYI (-6.6 cm mean bias). Over MYI, the mean bias was -5.7 cm but 54% of retrievals were discarded by the OIB retrieval process as compared to only 10% over FYI. Footprint scale analysis revealed a root mean square error (RMSE) of 6.2 cm over undeformed FYI with RMSE of 10.5 cm and 17.5 cm in the more complex deformed FYI and MYI environments. Correlation analysis was used to demonstrate contrasting retrieval uncertainty associated with spatial aggregation and ice surface roughness.

Seasonal forecasts of the September 2012 Arctic sea ice thickness and extent are conducted starting from 1 June 2012. An ensemble of forecasts is made with a coupled ice-ocean model. For the first time, observations of the ice thickness are used to correct the initial ice thickness distribution to improve the initial conditions. Data from two airborne campaigns are used: NASA Operation IceBridge and SIZONet. The model was advanced through April and May using reanalysis data from 2012 and for June–September it was forced with reanalysis data from the previous seven summers. The ice extent in the corrected runs averaged lower in the Pacific sector and higher in the Atlantic sector compared to control runs with no corrections. The redicted total ice extent is 4.4 +/� 0.5 M km2, 0.2 M km2 less than that made with the control runs but 0.8 M km2 higher than the observed September extent

Sea ice plays an important role in the global climate system by impacting the energy balance of the Earth as well as affecting the oceanic and atmospheric circulations. Recently, large changes have been observed in the Earth's areal coverage of sea ice. However, little is currently known about sea ice thickness particularly at the scales needed for climate research. Spaceborne remote sensing provides the necessary global scale of coverage, but the retrieval of sea ice thickness from space has not been possible until recently with the launch of satellite altimeters of high accuracy and precision. The Ice, Cloud, and land Elevation Satellite (ICESat) is one such laser altimeter with the potential to retrieve the height of the snow plus ice layer above the water level, or sea ice freeboard. The combination of sea ice freeboard data with snow depth retrievals and the assumption of hydrostatic balance allows for the determination of sea ice thickness. The goal of this study is to use data from ICESat to provide sea ice thickness values at the global scale and high spatial resolution needed for climate studies. The work presented in this thesis includes the validation and improvement of ICESat data products, development and validation of sea ice freeboard retrieval algorithms using the ICESat data products, and the development of a method to combine ICESat freeboard retrievals with a snow depth data set to determine sea ice thickness at the 70 m spatial resolution of ICESat. The ICESat data set is used to study sea ice thickness, heat exchange, and ice production in the Arctic Ocean for the 2003-2008 time period. Despite the thinning of the Arctic sea ice cover over the 2003-2008 time period, mean ice growth rates for consecutive fall and winter measurement periods remained relatively constant. An increased ice growth rate which may be expected from a thinner ice cover appeared to be balanced by warmer temperatures. An increased ocean-atmosphere heat flux is also observed due to the thinning of the sea ice cover.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice-ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.