regional greenland accumulation variability from operation icebridge airborne accumulation radar
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2017
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Abstract
The mass balance of the Greenland Ice Sheet (GrIS) in a warming climate is of
critical interest to scientists and the general public in the context of
future sea-level rise. An improved understanding of temporal and spatial
variability of snow accumulation will reduce uncertainties in GrIS mass
balance models and improve projections of Greenland's contribution to
sea-level rise, currently estimated at 0.089 ± 0.03 m by 2100. Here we
analyze 25 NASA Operation IceBridge accumulation radar flights totaling
> 17 700 km from 2013 to 2014 to determine snow accumulation in the GrIS
dry snow and percolation zones over the past 100–300 years. IceBridge
accumulation rates are calculated and used to validate accumulation rates
from three regional climate models. Averaged over all 25 flights, the RMS
difference between the models and IceBridge accumulation is between
0.023 ± 0.019 and 0.043 ± 0.029 m w.e. a−1, although each
model shows significantly larger differences from IceBridge accumulation on a
regional basis. In the southeast region, for example, the Modèle
Atmosphérique Régional (MARv3.5.2) overestimates by an average of
20.89 ± 6.75 % across the drainage basin. Our results indicate that
these regional differences between model and IceBridge accumulation are large
enough to significantly alter GrIS surface mass balance estimates. Empirical
orthogonal function analysis suggests that the first two principal components
account for 33 and 19 % of the variance, and correlate with the Atlantic
Multidecadal Oscillation (AMO) and wintertime North Atlantic Oscillation
(NAO), respectively. Regions that disagree strongest with climate models are
those in which we have the fewest IceBridge data points, requiring additional
in situ measurements to verify model uncertainties.
| Reference Key |
lewis2017theregional
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|---|---|
| Authors | ;G. Lewis;E. Osterberg;R. Hawley;B. Whitmore;H. P. Marshall;J. Box |
| Journal | journal of applied polymer science |
| Year | 2017 |
| DOI |
10.5194/tc-11-773-2017
|
| URL | |
| Keywords |
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