Remote sensing observations of the Arctic show recent and complex changes in tundra vegetation. For many decades a trend toward greener vegetation (‘Arctic greening’) was observed across the circumpolar region. Recently however, greater
variability in the extent of greening has been seen and decreases in vegetation (‘Arctic browning’) have been observed in some regions in some years. The drivers of this increased variability in greening versus browning among years and across the landscape
is currently poorly understood. Expansive changes in tundra vegetation could have strong implications for the surface energy balance and climate change in the Arctic, as well as impacts on permafrost thaw, carbon cycling, hydrological processes, vegetation
composition, and biota. This session solicits abstracts on the underlying drivers and the potential impacts of Arctic greening and browning, and abstracts that discuss the research needed to continue to advance our scientific understanding of this topic.
Invited Speaker: Uma Bhatt, University of Alaska Fairbanks
Conveners: Larry Hinzman, Natalie Boelman, Howie Epstein, April Melvin
Runoff from Greenland surface melt contributes a large fraction of the ice sheet’s ongoing mass loss, and surface melt-induced processes such as hydrofracture and ice cliff failure have the potential to lead to additional large future ice
losses from the Antarctic ice sheet. Our understanding of the factors driving surface melt at both poles, as well as how surface melt impacts ice dynamics, is limited by a short observation period, high spatial and temporal variability, and a complex set
of dynamics between the atmosphere, ocean, and ice sheet. Unraveling these complex relationships is necessary for advancing our ability to understand ice sheet mass balance and predict its future impact on sea level rise. Abstracts are requested for a session
on improving our understanding of ice sheet surface melt variability and dynamics, including how surface melt and surface melt-induced processes are observed, quantified, and modeled in the past, present and future.
Conveners: John Cassano, Sarah Das, Sridhar Anandakrishnan, Lauren Everett