Long-Term Observations for Monitoring of the Cryosphere

  • John E. Walsh
Chapter

Abstract

Variations of the cryosphere over decadal-to-century timescales are assessed by a survey of data on sea ice, snow cover, glaciers and ice sheets, permafrost and lake ice. The recent variations are generally consistent across the different cryospheric variables, especially when placed into the context of variations of temperature and precipitation. The recent warming over northern land areas has been accompanied by a decrease of snow cover, particularly during spring; the retreat of mountain glaciers is, in an aggregate sense, compatible with the observed warming; permafrost extent and lake ice duration show similar variations in areas for which data are available. Corresponding trends are not apparent, however, in data for some regions such as eastern Canada, nor in hemispheric sea ice data, especially for winter. The data also suggest an increase of snowfall over high latitudes, including the Antarctic ice sheet.

Estimates of both the climatic and the statistical significance of the recent variations are hampered by data inhomogeneities, the shortness of the records of many variables and the absence of central archives for data on several variables. The potential of monitoring by satellite remote sensing has been realized with several variables (extent of sea ice, snow cover). Other cryospheric variables (snow depth, ice sheet elevation, lake ice, mountain glaciers) may be amenable to routine monitoring by satellites pending advances in instrumentation, modifications of satellite orbit, and further developments in signal detection algorithms. The survey of recent variations leads to recommendations concerning the use of historical data, in situ measurements, and remote sensing applications in the monitoring of the cryosphere.

Keywords

Snow Cover Snow Depth Surface Albedo Areal Coverage Permafrost Temperature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media Dordrecht 1996

Authors and Affiliations

  • John E. Walsh
    • 1
  1. 1.Department of Atmospheric SciencesUniversity of IllinoisUrbanaUSA

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