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Mass Balance of the Greenland Ice Sheet: Can Modern Observation Methods Reduce the Uncertainty?

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Abstract:

The future contribution to sea level change from the large ice sheets in Greenland and Antarctica is composed of two terms: (i) a background trend determined by the past climate and dynamic history of the ice sheets on a range of time scales (decadal, millennial or even longer); and (ii) a rise/fall related to future climate change, whether due to anthropogenic effects or natural climate variability. The accelerating development of remote sensing techniques for monitoring ice sheet behaviour, and the use of high-resolution general circulation models to estimate temperature and precipitation changes are likely to result in improved estimates of the sensitivity of ice sheet mass balance to climate change and thereby to narrow down the uncertainty of contribution (ii). Contribution (i) is much more difficult to assess, because the mass balance displays large temporal variability on year-to-year and even on decadal time scales that masks the long-term trend. So, although modern remote sensing techniques enable accurate measurement of ice sheet surface elevation change, the mass changes derived from such measurements, even if performed over a period of several years, might just reflect a statistical fluctuation around the long-term background trend, which we must know in order to assess the future ice sheet contribution to sea level change on century and longer time scales. The measured volume changes must therefore be evaluated on the background of short- and long-term accumulation rates (e.g. determined from ice cores and high-resolution ice radar) and dynamic model studies of ice sheet evolution on century, millennial and longer time scales. The problems are illustrated by using the Greenland ice sheet as an example.

Keywords: Mass-balance measurements; glacier maps; hydropower production; map comparisons

Document Type: Research Article

DOI: https://doi.org/10.1111/j.0435-3676.1999.00101.x

Affiliations: Danish Center for Remote Sensing, Technical University of Denmark, Lyngby, Denmark

Publication date: 1999-12-01

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