Quantifying Asymmetries in Flood Area and Population Exposure Between
Sea Level Fingerprints of Melting From the Antarctic and Greenland Ice
Sheets
Abstract
Recent advances in modeling 21st-century sea level rise (SLR) and its
associated societal outcomes have demonstrated that the spatial pattern
of SLR combined with highly variable population density along global
coastlines exert a strong control on its impacts. Here, we extend this
research by examining differential costs arising from two sources of SLR
that exhibit distinct spatial ”fingerprints” - mass flux from the
Antarctic (AIS) and Greenland (GrIS) Ice Sheets. To do this, we employ
the DSCIM-Coastal data and modeling platform to quantify flood extents
and population exposure to inundation from sea level changes associated
with an ensemble of Ice Sheet Model Intercomparison Product projections
between 2015 and 2100 CE. We also introduce the Social Cost of Ice Sheet
Melt (SC-ISM) metric and calculate this for both AIS and GrIS melt
scenarios. Due to the distinct sea level fingerprints of the two ice
sheets, we find that mass flux from the AIS floods a larger area and
would inundate a greater (present-day) population than an equivalent
mass flux from the GrIS and yields a substantially higher SC-ISM. Across
a suite of future climate scenarios, the SC-ISM associated with AIS melt
is ~30% higher than that of GrIS, driven largely by
differential SLR rates along the North Atlantic coastline. However, for
either source, SC-ISM normalized by local GDP shows strongly
disproportionate impacts, with low-income regions experiencing a
significantly greater economic burden than high-income regions.