Key observational indicators of climate change in the Arctic, most spanning a 47 year period demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion thatincreasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near-coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO 2 uptake, with counterbalancing increases in shoulder season and winter CO 2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no.

As assessed over the period of satellite observations, October 1978 to present, there are downward linear trends in Arctic sea ice extent for all months, largest at the end of the melt season in September. The ice cover is also thinning. Downward trends in extent and thickness have been accompanied by pronounced interannual and multiyear variability, forced by both the atmosphere and ocean. As the ice thins, its response to atmospheric and oceanic forcing may be changing. In support of a busier Arctic, there is a growing need to predict ice conditions on a variety of time and space scales. A major challenge to providing seasonal scale predictions is the 7-10 days limit of numerical weather prediction. While a seasonally ice-free Arctic Ocean is likely well within this century, there is much uncertainty in the timing. This reflects differences in climate model structure, the unknown evolution of anthropogenic forcing, and natural climate variability. In sharp contrast to the Arctic, Antarctic sea ice extent, while highly variable, has increased slightly over the period of satellite observations. The reasons for this different behavior remain to be resolved, but responses to changing atmospheric circulation patterns appear to play a strong role.

Abstract. New sea ice motion fields available from remotely sensed data are potentially useful for assessing and improving models of the polar ice pack. Here we investigate the error characteristics of the observed ice motions relative to drifting buoys and a dynamicthermodynamic ice model. A data assimilation approach is then used to assess the potential of the motion data for reducing model biases, as well as the potential of the model to serve as an interpolation tool to generate improved ice motion data sets. Special Sensor Microwave/Imager (SSM/I) derived and model simulated ice motions for the years 1988 through 1993 are compared with ice displacement observations from drifting buoys. Variability and biases are summarized for seasonal and regional means. SSM/I motions are assimilated into the model using an optimal interpolation method that accounts for the modeled and SSM/I motion error variances and the number and distribution of the SSM/I motions. Modeled and SSM/I-derived motions are found to have comparable mean errors, with some notable regional and seasonal differences. Assimilation substantially reduces the error standard deviation and improves the correlation of the simulated motions relative to the buoy observations, but some biases remain. In the model framework used here, assimilation of the SSM/I data substantially alters average ice thickness in some regions of the Arctic and affects ice mass outflow through the Fram Strait but has a small effect on mean ice concentration. The assimilation yields an increase in the spatial and temporal variability in ice deformation. The observations are particularly suited for improving the simulation of specific synoptic events, where substantial differences can occur between simulated and observed ice transport.

ABSTRACT. With rapid and accelerated Arctic sea-ice loss, it is beneficial to update and baseline historical change on the regional scales from a consistent, intercalibrated, long-term time series of sea-ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation. In this paper, monthly sea-ice extents (SIEs) derived from a passive microwave sea-ice concentration climate data record for the period of 1979-2015, are used to examine Arcticwide and regional temporal variability of sea-ice cover and their decadal trends for 15 regions of the Arctic. Three unique types of SIE annual cycles are described. Regions of vulnerability within each of three types to further warming are identified. For the Arctic as a whole, the analysis has found significant changes in both annual SIE maximum and minimum, with −2.41 ± 0.56% per decade and −13.5 ± 2.93% per decade change relative to the 1979-2015 climate average, respectively. On the regional scale, the calculated trends for the annual SIE maximum range from +2.48 to −10.8% decade −1 , while the trends for the annual SIE minimum range from 0 to up to −42% decade −1 .

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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.

Summer sea ice in the Arctic has shown a significant downward trend of 8% per decade since the late 1970s, leading to a reduction of approximately 20% in sea ice extent in September (when the annual minimum occurs) (Stroeve et al., 2005). The past three summers (2002–2004) have been among the lowest on record, and 2002 was the extreme minimum. Despite decreasing summer extents, the sea ice extent has typically rebounded to near‐normal levels during the winter season, yielding an annual average trend of only −3%. This is not surprising since as temperatures drop below freezing, sea ice quickly forms.