Uncertainty in the Pan‐Arctic Ice‐Ocean Modeling and Assimilation System (PIOMAS) Arctic sea ice volume record is characterized. A range of observations and approaches, including in situ ice thickness measurements, ICESat retrieved ice thickness, and model sensitivity studies, yields a conservative estimate for October Arctic ice volume uncertainty of 1.35 × 103 km3 and an uncertainty of the ice volume trend over the 1979–2010 period of 1.0 × 103 km3 decade–1. A conservative estimate of the trend over this period is −2.8 × 103 km3 decade–1. PIOMAS ice thickness estimates agree well with ICESat ice thickness retrievals (<0.1 m mean difference) for the area for which submarine data are available, while difference outside this area are larger. PIOMAS spatial thickness patterns agree well with ICESat thickness estimates with pattern correlations of above 0.8. PIOMAS appears to overestimate thin ice thickness and underestimate thick ice, yielding a smaller downward trend than apparent in reconstructions from observations. PIOMAS ice volume uncertainties and trends are examined in the context of climate change attribution and the declaration of record minima. The distribution of 32 year trends in a preindustrial coupled model simulation shows no trends comparable to those seen in the PIOMAS retrospective, even when the trend uncertainty is accounted for. Attempts to label September minima as new record lows are sensitive to modeling error. However, the September 2010 ice volume anomaly did in fact exceed the previous 2007 minimum by a large enough margin to establish a statistically significant new record.
[1] Several new data sets reveal that thinning and speedup of Jakobshavn Isbrae continue, following its recent rapid increase in speed as its floating ice tongue disintegrated. The present speedup rate of $5% a À1 over much of the fast-moving region appears to be a diffusive response to the initial much larger speedup near the front. There is strong seasonality in speed over much of the fast-flowing main trunk that shows a good inverse correlation with the seasonally varying length of a short (typically $6 km) floating ice tongue. This modulation of speed with ice front position supports the hypothesis that the major speedup was caused by loss of the larger floating ice tongue from 1998 to 2003. Analysis of image time series suggests that the transient winter ice tongue is formed when sea ice bonds glacier ice in the fjord to produce a nearly rigid mass that almost entirely suppresses calving. Major calving only resumes in late winter when much of this ice clears from the fjord. The collapse of the ice tongue in the late 1990s followed almost immediately after a sharp decline in winter sea-ice concentration in Disko Bay. This decline may have extended the length of the calving season for several consecutive years, leading to the ice tongue's collapse.
A year/long ice camp centered around a Canadian icebreaker frozen in the arctic ice pack successfully collected a wealth of atmospheric, oceanographic, and cryospheric data.
Arctic marine mammals (AMMs) are icons of climate change, largely because of their close association with sea ice. However, neither a circumpolar assessment of AMM status nor a standardized metric of sea ice habitat change is available. We summarized available data on abundance and trend for each AMM species and recognized subpopulation. We also examined species diversity, the extent of human use, and temporal trends in sea ice habitat for 12 regions of the Arctic by calculating the dates of spring sea ice retreat and fall sea ice advance from satellite data (1979–2013). Estimates of AMM abundance varied greatly in quality, and few studies were long enough for trend analysis. Of the AMM subpopulations, 78% (61 of 78) are legally harvested for subsistence purposes. Changes in sea ice phenology have been profound. In all regions except the Bering Sea, the duration of the summer (i.e., reduced ice) period increased by 5–10 weeks and by >20 weeks in the Barents Sea between 1979 and 2013. In light of generally poor data, the importance of human use, and forecasted environmental changes in the 21st century, we recommend the following for effective AMM conservation: maintain and improve comanagement by local, federal, and international partners; recognize spatial and temporal variability in AMM subpopulation response to climate change; implement monitoring programs with clear goals; mitigate cumulative impacts of increased human activity; and recognize the limits of current protected species legislation.
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