[1] In order to explore changes and trends in the timing of Arctic sea ice melt onset and freezeup, and therefore melt season length, we developed a method that obtains this information directly from satellite passive microwave data, creating a consistent data set from 1979 through present. We furthermore distinguish between early melt (the first day of the year when melt is detected) and the first day of continuous melt. . For the entire Arctic, the melt season length has increased by about 20 days over the last 30 years. Largest trends of over 10 d decade À1 are seen for Hudson Bay, the East Greenland Sea, the Laptev/East Siberian seas, and the Chukchi/Beaufort seas. Those trends are statistically significant at the 99% level.

The Arctic-wide melt season has lengthened at a rate of 5 days decade

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Quantifying changes in Earth’s ice sheets and identifying the climate drivers are central to improving sea level projections. We provide unified estimates of grounded and floating ice mass change from 2003 to 2019 using NASA’s Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 satellite laser altimetry. Our data reveal patterns likely linked to competing climate processes: Ice loss from coastal Greenland (increased surface melt), Antarctic ice shelves (increased ocean melting), and Greenland and Antarctic outlet glaciers (dynamic response to ocean melting) was partially compensated by mass gains over ice sheet interiors (increased snow accumulation). Losses outpaced gains, with grounded-ice loss from Greenland (200 billion tonnes per year) and Antarctica (118 billion tonnes per year) contributing 14 millimeters to sea level. Mass lost from West Antarctica’s ice shelves accounted for more than 30% of that region’s total.

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[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.

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An enhancement of the NASA Team sea ice concentration algorithm overcomes the problem of a low ice concentration bias associated with surface snow effects that are particularly apparent in Southern Ocean sea ice retrievals. The algorithm has the same functional form as the NASA Team algorithm, but uses a wider range of frequencies (19-85 GHz). It accommodates ice temperature variability through the use of radiance ratios as in the original NASA Team algorithm, and has the added advantage of providing weather-corrected sea ice concentrations through the utilization of a forward atmospheric radiative transfer model. Retrievals of sea ice concentration with this new algorithm for both the Arctic and Antarctic do not reveal the deficiencies present in either the NASA Team or Bootstrap algorithms. Furthermore, quantitative comparisons with infrared AVHRR data show that the enhanced algorithm provides more accurate ice concentrations with much less bias than the other two algorithms.