SOSIce

Sea level rise has become a challenge facing society due particularly to the ice sheets that are contributing more significantly than previously anticipated. The mass loss of the ice sheets is due to increased surface melt runoff and outflow of ice associated with current climate warming. Here, we propose to improve our understanding of the dynamic component. Indeed, the ice discharge modulated by changes in ice velocity and thickness changes remains the largest uncertainty in the current and future contribution of the ice sheets to sea level rise. Quantifying and understanding the past/present/future contribution of the ice sheets to sea level rise under the current warming climate requires answering fundamental questions as: How has the ice velocity, thickness and so discharge of outlet glaciers changed on sub-annual to decadal time scales? What are the main and most important external forcing that are controlling changes in glacier ice discharge into the ocean? How can we use ice dynamic observations of the recent past to teach numerical ice flow model and get more precise projection of sea level rise? Until recently the answers to those questions were limited, mainly because the ice sheet observations were spatially incomplete and temporarily sparse, resulting in averaged products to maximize spatial coverage at the expense of temporal information. However, in the last few years, we entered a new era of spaceborne ice sheet observations with the launch of the ESA’s CryoSat-2 in 2010, USGS’ Landsat-8 in 2013 and ESA’s four Sentinel-1 & 2 between 2014 & 2016. Used in the synergistic manner, these satellites offer the first chance for sustained, continuous data acquisition over the ice sheets to map ice motion and elevation. Taking the opportunity offered by these new satellites, the SOSIce project will reconstruct at high temporal and spatial resolution the ice flow for the largest glaciers of Greenland and Antarctica to refine mass balance estimates and improve the forecasting skills of the numerical ice flow models. We have envisioned this work in 3 successive steps: derive time series of the (1) dynamical and geometrical structure of the glaciers from these new sensors, (2) assimilate them into the state-of-the-art ice flow model Elmer/Ice, and (3) disseminate our results using public data archive for the scientific community. By taking advantage of the continuous observations and by assimilating them in an model, we will follow the ice sheet evolution in a fundamentally new way compared to current approaches. Significant technical and scientific issues would be solved from the results of this project, including securing the capacity to process large quantities of data for ice sheet studies, better understanding of the underlying physical processes causing increased in glacier ice discharge, improving ice-sheet model initialization before computing projections, and precisely reassessing the sea-level budget. This project will set very good grounds to initiate an international, scientific collaborative effort to facilitate the growth and establishment of the novel and rapidly growing field of remote sensing of the cryosphere over large datasets.