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  • 标题:Autonomous ice sheet surface mass balance measurements from cosmic rays
  • 本地全文:下载
  • 作者:Ian M. Howat ; Santiago de la Peña ; Darin Desilets
  • 期刊名称:The Cryosphere
  • 印刷版ISSN:1994-0416
  • 电子版ISSN:1994-0424
  • 出版年度:2018
  • 卷号:12
  • 期号:6
  • 页码:2099-2108
  • DOI:10.5194/tc-12-2099-2018
  • 出版社:Copernicus Publications
  • 摘要:Observations of mass accumulation and net balance on glaciers and ice sheets are sparse due to the difficulty of acquiring manual measurements and the lack of a reliable remote-sensing method. The methodology for recording the water-equivalent accumulation of snowfall using the attenuation of fast neutrons generated by cosmic ray impacts was developed in the 1970s and has been employed in large-network snowpack monitoring but has yet to be applied to glaciers and ice sheets. In order to assess this potential method, we installed a cosmic ray neutron-sensing device at Summit Camp, Greenland, in April 2016. Hourly neutron count was recorded for ∼ 24 months and converted to water-equivalent thickness after correcting for variability in atmospheric pressure and incoming cosmic radiation. The daily accumulation estimates are analysed for noise level and compared to manual surface core and snow stake network measurements. Based on measurements of up to 56 cm of water equivalent, we estimate the sensor's precision to be better than 1 mm for water-equivalent thicknesses less than 14 cm and better than 1 cm in up to 140 cm, or approximately 0.7 %. Our observations agree with the surface core measurements to within their respective errors, with temporary biases that are explained by snow drifting, as supported by comparison to the snow stake network. Our observations reveal large temporal variability in accumulation on daily to monthly scales, but with similar annual totals. Based on these results, cosmic ray sensing represents a potentially transformative method for acquiring continuous in situ measurements of mass accumulation that may add constraint to glacier and ice sheet mass balance estimates from meteorological models and remote sensing.
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