Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux
AffiliationUniv Arizona, Dept Geosci, Tucson, AZ 85721 USA
MetadataShow full item record
PublisherAMER METEOROLOGICAL SOC
CitationMitrovica, J. X., Hay, C. C., Kopp, R. E., Harig, C., & Latychev, K. (2018). Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux. Journal of Climate, 31(9), 3701-3709.
JournalJOURNAL OF CLIMATE
Rights© 2018 American Meteorological Society.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractIt has been known for over a century that the melting of individual ice sheets and glaciers drives distinct geographic patterns, or fingerprints, of sea level change, and recent studies have highlighted the implications of this variability for hazard assessment and inferences of meltwater sources. These studies have computed fingerprints using simplified melt geometries; however, a more generalized treatment would be advantageous when assessing or projecting sea level hazards in the face of quickly evolving patterns of ice mass flux. In this paper the usual fingerprint approach is inverted to compute site-specific sensitivity kernels for a global database of coastal localities. These kernels provide a mapping between geographically variable mass flux across each ice sheet and glacier and the associated static sea level change at a given site. Kernels are highlighted for a subset of sites associated with melting from Greenland, Antarctica, and the Alaska-Yukon-British Columbia glacier system. The latter, for example, reveals an underappreciated sensitivity of ongoing and future sea level change along the U.S. West Coast to the geometry of ice mass flux in the region. Finally, the practical utility of these kernels is illustrated by computing sea level predictions at a suite of sites associated with annual variability in Greenland ice mass since 2003 constrained by satellite gravity measurements.
Note6 month embargo, April 2018
VersionFinal published version
SponsorsHarvard University; NASA [NNX17AE17G, NNX17AE18G, 80NSSC17K0698]; NSF [ICER-1663807]