Temporal Means and Variability of Arctic Sea Ice Melt and Freeze Season Climate Indicators Using a Satellite Climate Data Record

Information on the timing of Arctic snow and ice melt onset, sea ice opening, retreat, advance, and closing, can be beneficial to a variety of stakeholders. Sea ice modelers can use information on the evolution of the ice cover through the rest of the summer to improve their seasonal sea ice forecasts. The length of the open water season (as derived from retreat/advance dates) is important for human activities and for wildlife. Long-term averages and variability of these dates as climate indicators are beneficial to business strategic planning and climate monitoring. In this study, basic characteristics of temporal means and variability of Arctic sea ice climate indicators derived from a satellite-based climate data record from March 1979 to February 2017 melt and freeze seasons are described. Our results show that, over the Arctic region, anomalies of snow and ice melt onset, ice opening and retreat dates are getting earlier in the year at a rate of more than 5 days per decade, while that of ice advance and closing dates are getting later at a rate of more than 5 days per decade. These significant trends resulted in significant upward trends for anomalies of inner and outer ice-free periods at a rate of nearly 12 days per decade. Small but significant downward trends of seasonal ice loss and gain period anomalies were also observed at a rate of −1.48 and −0.53 days per decade, respectively. Our analyses also demonstrated that the means of these indicators and their trends are sensitive to valid data masks and regional averaging methods.

Spatially mapped reductions in the length of the Arctic sea ice season

Satellite data are used to determine the number of days having sea ice coverage in each year 1979-2013 and to map the trends in these ice-season lengths. Over the majority of the Arctic seasonal sea ice zone, the ice season shortened at an average rate of at least 5 days/decade between 1979 and 2013, and in a small area in the northeastern Barents Sea the rate of shortening reached over 65 days/decade. The only substantial non-coastal area with lengthening sea ice seasons is the Bering Sea, where the ice season lengthened by 5-15 days/decade. Over the Arctic as a whole, the area with ice seasons shortened by at least 5 days/decade is 12.4 × 10⁶ km², while the area with ice seasons lengthened by at least 5 days/decade is only 1.1 × 10⁶ km². The contrast is even greater, percentage-wise, for higher rates.

KEY POINTS

Sea ice seasons have shortened by at least 5 days/decade over most of the ArcticAcross 1.9 million km² ice seasons have shortened by at least 25 days/decadeCounter to most of the Arctic ice seasons have lengthened in the Bering Sea.

Denning-area fidelity and mitochondrial DNA diversity of female polar bears (Ursus maritimus) in the Barents Sea

Polar bears ( Ursus maritimus Phipps, 1774) show fidelity to general denning areas in subsequent reproductive events. Studying the level and spatio-temporal scale of denning-area fidelity is critical to determine the adaptability of polar bears to climate change. We used mark–recapture data in conjunction with mitochondrial DNA (mtDNA) data to investigate the level of fidelity of polar bears from the Barents Sea population to five maternal denning areas. There was no differentiation in mtDNA haplotype frequencies between denning areas. The fidelity of females to denning areas is at a local geographic scale and small groups of neighboring females (3–13) shared similar haplotypes with higher probability than expected by chance. The transmission of denning-area fidelity is supported by the short distances (≤60.0 km) observed between capture locations of six (out of eight) denning mother–daughter pairs. Moreover, our results suggested that some females (3 out of 13) used different denning areas in subsequent denning events. This behavioral plasticity implies that females are likely to be able to change denning locations if unsuitable ice conditions prevent them from reaching their preferred denning areas. We consider this plasticity an important attribute of polar bears when facing climate change.

Recent climate change in the Arctic and its impact on contaminant pathways and interpretation of temporal trend data

The Arctic has undergone dramatic change during the past decade. The observed changes include atmospheric sea-level pressure, wind fields, sea-ice drift, ice cover, length of melt season, change in precipitation patterns, change in hydrology and change in ocean currents and watermass distribution. It is likely that these primary changes have altered the carbon cycle and biological systems, but the difficulty of observing these together with sporadic, incomplete time series makes it difficult to evaluate what the changes have been. Because contaminants enter global systems and transport through air and water, the changes listed above will clearly alter contaminant pathways. Here, we review what is known about recent changes using the Arctic Oscillation as a proxy to help us understand the forms under which global change will be manifest in the Arctic. For Pb, Cd and Zn, the Arctic is likely to become a more effective trap because precipitation is likely to increase. In the case of Cd, the natural cycle in the ocean appears to have a much greater potential to alter exposure than do human releases of this metal. Mercury has an especially complex cycle in the Arctic including a unique scavenging process (mercury depletion events), biomagnifying foodwebs, and chemical transformations such as methylation. The observation that mercury seems to be increasing in a number of aquatic species whereas atmospheric gaseous mercury shows little sign of change suggests that factors related to change in the physical system (ice cover, permafrost degradation, organic carbon cycling) may be more important than human activities. Organochlorine contaminants offer a surprising array of possibilities for changed pathways. To change in precipitation patterns can be added change in ice cover (air-water exchange), change in food webs either from the top down or from the bottom up (biomagnification), change in the organic carbon cycle and change in diets. Perhaps the most interesting possibility, presently difficult to predict, is combination of immune suppression together with expanding ranges of disease vectors. Finally, biotransport through migratory species is exceptionally vulnerable to changes in migration strength or in migration pathway-in the Arctic, change in the distribution of ice and temperature may already have caused such changes. Hydrocarbons, which tend to impact surfaces, will be mostly affected by change in the ice climate (distribution and drift tracks). Perhaps the most dramatic changes will occur because our view of the Arctic Ocean will change as it becomes more amenable to transport, tourism and mineral exploration on the shelves. Radionuclides have tended not to produce a radiological problem in the Arctic; nevertheless one pathway, the ice, remains a risk because it can accrue, concentrate and transport radio-contaminated sediments. This pathway is sensitive to where ice is produced, what the transport pathways of ice are, and where ice is finally melted-all strong candidates for change during the coming century. The changes that have already occurred in the Arctic and those that are projected to occur have an effect on contaminant time series including direct measurements (air, water, biota) or proxies (sediment cores, ice cores, archive material). Although these 'system' changes can alter the flux and concentrations at given sites in a number of obvious ways, they have been all but ignored in the interpretation of such time series. To understand properly what trends mean, especially in complex 'recorders' such as seals, walrus and polar bears, demands a more thorough approach to time series by collecting data in a number of media coherently. Presently, a major reservoir for contaminants and the one most directly connected to biological uptake in species at greatest risk-the ocean-practically lacks such time series.