Ice Sheet Mass Balance and Sea Level: A Science Plan
presented as an ISMASS contribution at the International Glaciological Society Conference in Newcastle-upon-Tyne, UK, July 27-31, 2009
by C. J. van der Veen and ISMASS
The dynamic response of ice sheets is currently understood to be due to the coupling of four component processes, each corresponding to a specific region of an ice sheet. They are surface mass balance, ice shelf, basal, and englacial processes. Of these four, only englacial processes have the capacity to transmit stress from one area to another, and as such will play the pivotal role in determining how sea level rise can result from grounded ice moving seaward.
The two least well understood scientific issues relating to englacial processes are presently 1) how horizontal stresses are transferred within ice, and what level of detail in the stress balance is required to adequately capture the transfer, and 2) how well must the ice rheology be represented to predict the dynamical evolution of ice with the desired precision. It should also be noted that description of englacial boundary conditions requires advances in understanding of surface, basal, and shelf processes. Hence model uncertainty will remain high until advances in all four processes are made.
The importance of ice sheet modeling efforts has been magnified by recent reports suggesting that sea level rise remains the most poorly constrained and potentially catastrophic impact of climate change. As such, this document has been prepared to coordinate and focus scientific inquiry in the coming years. First, three scientific questions of great significance are posed. Englacial processes and the closely related numerical schemes for addressing them will be pivotal to advancement on the questions, but the other three component processes will play a role as well. The questions are:
In this contribution, the scientific background for each of the questions is presented. This is followed with a “roadmap” for studying the questions that is consistent with the best available data.