The only negative anomalies were observed in the Western (North American) Arctic (11.9%) and the Sea of Okhotsk (1.8%). Financial support for the Arctic Report Card is provided by the Arctic Research Program in the NOAA Climate Program Office. It is clear that the record delay in freezing of the sea ice cover in the fall of 2016 is associated with unprecedentedly warm air and ocean surface temperatures.
Temperature anomalies for coastal locations in Greenland were warmer in the north (see essay on Greenland ice sheet). Record winter temperature conditions in the Arctic were primarily a response to southerly winds pushing warm air from mid-latitudes into the Arctic. In winter 2016, higher geopotential heights in the central Arctic split the polar vortex in two.
SCE anomalies over the North American sector of the Arctic were strongly negative in all three months: new record low anomalies were set for April and May, and the third lowest values in the NOAA dataset were observed in June. Snow cover duration deviations (SCD) (Figure 2.2) derived from NOAA's Daily Interactive Multi-Sensor Snow and Ice Mapping System (IMS) snow cover product (Helfrich et al., 2007) show an earlier onset of snow cover in autumn over much of the Arctic (defined as land areas north of 60° N), excluding Scandinavia. The anomaly of the number of days in which surface melting occurred with respect to the period 19812010 peaked in the northeastern region (Figure 3.1b).
Monthly change in total mass (in Gigatonnes) of the Greenland ice sheet between April 2002 and April 2016, estimated from GRACE measurements.
15/16 MAM 2016 JJA
Narsarsuaq 1961,61.2, 45.4
Nord
Ilulissat
Tasiilaq
Aasiaat
Prins Christian Sund
Nuuk
Summit
Monthly mean sea ice extent in March 2016 (left) and September 2016 (right) illustrate the respective maximum winter and minimum summer extents. Sea ice extent has decreasing trends in all months and in almost all regions, with the exception of the Bering Sea during winter (Meier et al., 2014). Sea ice age is another key descriptor of sea ice cover condition.
Coverages in (c) are presented as fractions or percentages of total sea ice coverage. Observations of sea ice thickness and volume from multiple sources have revealed continued reductions in Arctic sea ice extent over the past decade (Kwok and Rothrock 2009; Laxon et al. 2013; Kwok and Cunningham 2015; Lindsay and Schweiger, 2015). The European Space Agency's CryoSat2 satellite has been measuring sea ice surface (from which sea ice thickness and volume are derived) since 2010 (Tilling et al., 2015).
Blue indicates regional thinner and red thicker sea ice in 2016 than the five-year average. Solar warming of the ocean's surface layer is influenced by the distribution of sea ice (with more solar warming in ice-free areas), cloud cover, water color, and stratification in the upper ocean (river inflow influences the last two). In the Chukchi Sea, this trend coincides with decreasing trends in summer sea ice extent.
Woodgate, 2016: Variability, trends and predictability of seasonal sea ice retreat and advance in the Chukchi Sea. In particular, spring sea ice melt and retreat are strong drivers of primary production in the Arctic Ocean and adjacent seas due to enhanced light availability (Barber et al. 2015, Leu et al. 2015) . The recent decline in Arctic sea ice extent (see the essay on sea ice) has contributed substantially to shifts in primary productivity in the open waters of the Arctic Ocean.
However, it is clear that the response of primary production to sea ice loss was both seasonally and spatially dependent (e.g. Tremblay et al. 2015). In addition to the primary production of phytoplankton, sea ice algal production is also important to consider in the overall Arctic Ocean system. In the central Arctic Ocean where primary productivity is relatively low, sea ice algae can contribute up to 60% of total primary production (mainly due to low pelagic primary productivity).
Region Trend, 2003-2016
Mann- Kendall
2016 Anomaly from a 2003-2015 (%)
Schuur 1 , G. Hugelius 2
This permafrost carbon is the remains of plants, animals, and microbes accumulated in frozen soil over hundreds to thousands of years (Schuur et al. 2008). The northern permafrost zone holds twice as much carbon as currently in the atmosphere (Schuur et al. 1a) (Schuur et al., 2015). a) Soil organic carbon pools (up to 3 m depth) for the northern circumpolar permafrost zone.
The base layer shows a permafrost distribution, with a continuous area in the north having permafrost throughout (>90%), and discontinuous areas further south with permafrost at some, but not all, locations (<90%) (Schuur et al. 2015 ). One of the most recent analyzes of carbon exchange measurements in the tundra ecosystem (excluding high latitude forests, fens, marshes and marshes) over the past decades is available in Belshe et al., 2013. Positive ecosystem exchange values indicate a net release of carbon into the atmosphere (Belshe et al. 2013).
Positive ecosystem exchange values indicate a net release of carbon to the atmosphere (Belshe et al. 2013). As a result, it is already recognized that accelerating climate change is leading to significant range expansion and contraction, evolutionary change and extinction for hosts, parasites and diseases across the Arctic (e.g. Kutz et al., 2013; Meltofte et al., 2013). Ultimately, these disturbances have consequences for wildlife and humans at high latitudes (e.g., Dudley et al., 2015).
Most shrew species have a wide continental distribution, with regional differences corresponding to major geographic barriers (e.g. Hope et al., 2012). As the climate warmed, these species rapidly shifted their ranges northward to follow their preferred set of environmental conditions, a trend that will continue in the coming decades (Hope et al., 2013). The future viability of Arctic biodiversity will depend on sensitivity to environmental thresholds and relative ability to persist in the face of change, reflecting both resilience and ecological plasticity (Araujo et al., 2015).
Islands tend to have fewer species with limited ranges, lower genetic variability and a reduced ability to respond to change (Pauls et al., 2013). Host parasite systems provide a generalizable reference for understanding and documenting ecological changes (e.g. Kutz et al., 2014). Finally, high-resolution, full-system models have been advocated for the Arctic (Roberts et al. 2010).
However, in the context of policy-maker involvement, simpler models (of medium complexity) (Eby et al. 2013) could also be useful, with the advantage of being much smaller. From the beginning, SEARCH recognized the need to focus on synthesis (Morison et al. 1998).
