Sea surface height measured by the Envisat radar altimeter over open ocean and from leads in sea ice are combined to generate a complete view of variability in the Nordic Seas, geographically and seasonally. The observed seasonal variability is decomposed using empirical orthogonal functions and is consistent with seasonal variations in steric and dynamic forcing. Wintertime increase in sea surface height on the east Greenland shelf is hypothesized to be caused by wind-forced downwelling, which provides direct evidence for the regional play of coastal dynamics. High levels of eddy kinetic energy around the sea ice edge in Fram Strait and off east Greenland and Svalbard are consistent with the interaction of the wind with the ice edge.

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.

We analyze data acquired by the CryoSat‐2 interferometric radar altimeter and demonstrate its novel capability to track topographic features on the Antarctic Ice Sheet. We map the perimeter and depth of a 260 km2 surface depression above an Antarctic subglacial lake (SGL) and, in combination with Ice, Cloud and land Elevation Satellite laser altimetry, chart decadal changes in SGL volume. During 2007–2008, between 4.9 and 6.4 km3 of water drained from the SGL, and peak discharge exceeded 160 m3 s−1. The flood was twice as large as any previously recorded and equivalent to ~ 10% of the meltwater generated annually beneath the ice sheet. The ice surface has since uplifted at a rate of 5.6 ± 2.8 m yr−1. Our study demonstrates the ability of CryoSat‐2 to provide detailed maps of ice sheet topography, its potential to accurately measure SGL drainage events, and the contribution it can make to understanding water flow beneath Antarctica.

a Centre for Polar Observation and Modelling, University College London, London, WC1E 6BT, UK b Met Office Hadley Centre, Exeter, EX1 3PB, UK c National Oceanography Centre, University of Southampton, Southampton, SO14 3ZH, UK d Centre for Polar Observation and Modelling, University of Reading, Reading, RG6 6AH, UK e The National Centre for Atmospheric Science (NCAS), University of Reading, Reading, RG6 6AH, UK f European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield, Reading RG2 9AX

Precise mappings of sea surface topography, slope, and gravity of the Arctic Ocean are derived from altimeter data collected by Envisat and ICESat. Both altimeters measured instantaneous sea surface height at leads in the sea ice. To reduce contamination by ice‐freeboard signal and tracker noise in Envisat height data, a retracking of the waveform data was performed. Analogous reprocessing of ICESat data was also done. Arctic mean sea surfaces (MSSs) were computed from Envisat data spanning 2002–2008 and ICESat data spanning 2003–2009. Farrell et al. (2012) used these “ICEn” MSSs to estimate mean dynamic topography (MDT). These same Envisat and ICESat data are used, in sea‐surface‐slope form, to compute the ARCtic Satellite‐only (ARCS‐2) altimetric marine gravity field. ARCS‐2 extends north to 86°N and uses GRACE/GOCE gravity data (GOCO02S) for its long‐wavelength (>260 km) components. Use of Envisat data improves the spatial resolution over that of existing Arctic marine gravity fields in many areas. ARCS‐2's spatial resolution aids in tracing tectonic fabric—e.g., extinct plate boundaries—over broad areas of the Arctic basin whose tectonic origin remains a mystery. ARCS‐2's precision is validated using NASA 2010/2011 Operation IceBridge (OIB) airborne gravimetry. ARCS‐2 and OIB gravity along with ICEn‐MSS results are employed to locate short‐wavelength errors approaching 1 m in current Arctic marine geoids (EGM2008). Precise OIB airborne gravity corroborates that such errors in current geoid/gravity models are widespread in Arctic areas lacking accurate surface gravity data. These geoid errors limit the spatial resolution at which MDT can be mapped.

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 km 3 and the winter volume by 1479 km 3 . This exceeds the decline in ice volume in the central Arctic from the PIOMAS model of 2644 km 3 in the autumn, but is less than the 2091 km 3 in winter, between the two time periods.

An increasing amount of freshwater has been stored in the Arctic Ocean over the past few decades. Satellite measurements of sea surface height reveal a spin-up of the Beaufort Gyre in the western Arctic that is associated with changes in the wind field, and is estimated to have led to the additional storage of about 8,000 km3 of freshwater. The Arctic Ocean’s freshwater budget comprises contributions from river runoff, precipitation, evaporation, sea-ice and exchanges with the North Pacific and Atlantic1. More than 70,000 km3 of freshwater2 are stored in the upper layer of the Arctic Ocean, leading to low salinities in upper-layer Arctic sea water, separated by a strong halocline from warm, saline water beneath. Spatially and temporally limited observations show that the Arctic Ocean’s freshwater content has increased over the past few decades, predominantly in the west3,4,5. Models suggest that wind-driven convergence drives freshwater accumulation6. Here we use continuous satellite measurements between 1995 and 2010 to show that the dome in sea surface height associated with the western Arctic Beaufort Gyre has been steepening, indicating spin-up of the gyre. We find that the trend in wind field curl—a measure of spatial gradients in the wind that lead to water convergence or divergence—exhibits a corresponding spatial pattern, suggesting that wind-driven convergence controls freshwater variability. We estimate an increase in freshwater storage of 8,000±2,000 km3 in the western Arctic Ocean, in line with hydrographic observations4,5, and conclude that a reversal in the wind field could lead to a spin-down of the Beaufort Gyre, and release of this freshwater to the Arctic Ocean.

Sea ice decline is iconic of climate change in the Arctic. Sea ice reductions represent the integrated changes which are taking place in both the ocean and atmosphere. Arctic surface temperature is also warming. The presence of sea ice determines the accessibility of the Arctic Ocean and its presence can also affect European and global climate.

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.

This article reviews some of the major lines of recent scientific progress relevant to the choice of global climate policy targets, focusing on changes in understanding since publication of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). Developments are highlighted in the following major climate system components: ice sheets; sea ice; the Atlantic Meridional Overturning Circulation; tropical forests; and accelerated carbon release from permafrost and ocean hydrates. The most significant developments in each component are identified by synthesizing input from multiple experts from each field. Overall, while large uncertainties remain in all fields, some substantial progress in understanding is revealed.

Satellite radar altimetry provides data to monitor winter Arctic sea-ice thickness variability on interannual, basin-wide scales. When using this technique an assumption is made that the peak of the radar return originates from the snow/ice interface. This has been shown to be true in the laboratory for cold, dry snow as is the case on Arctic sea ice during winter. However, this assumption has not been tested in the field. We use data from an airborne normal-incidence Ku-band radar altimeter and in situ field measurements, collected during the CryoSat Validation Experiment (CryoVEx) Bay of Bothnia, 2006 and 2008 field campaigns, to determine the dominant scattering surface for Arctic snow-covered sea ice. In 2006, when the snow temperatures were close to freezing, the dominant scattering surface in 25% of the radar returns appeared closer to the snow/ice interface than the air/snow interface. However, in 2008, when temperatures were lower, the dominant scattering surface appeared closer to the snow/ice interface than the air/snow interface in 80% of the returns.

ICESat and Envisat altimetry data provide measurements of the instantaneous sea surface height (SSH) across the Arctic Ocean, using lead and open water elevation within the sea ice pack. First, these data were used to derive two independent mean sea surface (MSS) models by stacking and averaging along‐track SSH profiles gathered between 2003 and 2009. The ICESat and Envisat MSS data were combined to construct the high‐resolution ICEn MSS. Second, we estimate the 5.5‐year mean dynamic topography (MDT) of the Arctic Ocean by differencing the ICEn MSS with the new GOCO02S geoid model, derived from GRACE and GOCE gravity. Using these satellite‐only data we map the major features of Arctic Ocean dynamical height that are consistent with in situ observations, including the topographical highs and lows of the Beaufort and Greenland Gyres, respectively. Smaller‐scale MDT structures remain largely unresolved due to uncertainties in the geoid at short wavelengths.