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  • 标题:Glaciological measurements and mass balances from Sperry Glacier, Montana, USA, years 2005–2015
  • 本地全文:下载
  • 作者:Adam M. Clark ; Daniel B. Fagre ; Erich H. Peitzsch
  • 期刊名称:Earth System Science Data (ESSD)
  • 印刷版ISSN:1866-3508
  • 电子版ISSN:1866-3516
  • 出版年度:2017
  • 卷号:9
  • 期号:1
  • 页码:47-61
  • DOI:10.5194/essd-9-47-2017
  • 出版社:Copernicus
  • 摘要:Glacier mass balance measurements help to provide an understanding of the behavior of glaciers and their response to local and regional climate. In 2005 the United States Geological Survey established a surface mass balance monitoring program on Sperry Glacier, Montana, USA. This project is the first quantitative study of mass changes of a glacier in the US northern Rocky Mountains and continues to the present. The following paper describes the methods used during the first 11 years of measurements and reports the associated results. From 2005 to 2015, Sperry Glacier had a cumulative mean mass balance loss of 4.37 m w.e. (water equivalent). The mean winter, summer, and annual glacier-wide mass balances were 2.92, −3.41, and −0.40 m w.e. yr−1 respectively. We derive these cumulative and mean results from an expansive data set of snow depth, snow density, and ablation measurements taken at selected points on the glacier. These data allow for the determination of mass balance point values and a time series of seasonal and annual glacier-wide mass balances for all 11 measurement years. We also provide measurements of glacier extent and accumulation areas for select years. All data have been submitted to the World Glacier Monitoring Service and are available at doi:10.5904/wgms-fog-2016-08. This foundational work provides valuable insight about Sperry Glacier and supplies additional data to the worldwide record of glaciers measured using the glaciological method. Future research will focus on the processes that control accumulation and ablation patterns across the glacier. Also we plan to examine the uncertainties related to our methods and eventually quantify a more robust estimate of error associated with our results.
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