You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 3 Next »

Description
Estimates future increases in sea level projected to occur due to increasing global mean temperature (GMT).

Input variables

  • Increase in global mean temperature (GMT) above base year (from Climate module)

Key assumptions
This module is based on a linear algorithm developed by Rahmstorf, based on extrapolating from increases in temperature and sea level that occurred from 1881-2001.

This approach was chosen because, according to Rahmstorf the "capability for calculating future sea-level changes...with present physics based models is very limited."

The key parameter values for the module are:

  • Baseline annual increase in sea level of 3.4 millimeters for each degree Celsius by which GMT in that year exceeds pre-industrial levels (C-LEARN uses this baseline parameter in all of its outputs).
  • User-specified parameter which enables adjustment of baseline annual increase to take into account faster or slower ice sheet melt (this parameter is adjustable in C-ROADS but not in C-LEARN).

    Parameter value of 1 doubles annual sea level increase per degree of increase in GMT to 6.8 mm per degree Celsius.

    Parameter value of -1 reduces annual sea level increase to 0 mm.

Note: For technical reasons, the sea level rise outputs in the launch version of the Collaboratorium are calcuated from a database that is separate from C-LEARN, but which employs identical assumptions.

Output variables

  • Cumulative increase in sea level above baseline year


Return to C-LEARN modules

  • No labels