Estimating Antarctic ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

The Antarctic ice-sheet surface mass balance (SMB) is a significant contribution to sea level changes which may mitigate the rise in sea level in a warmer climate, but this term is still poorly known. The Antarctic SMB cannot be directly deduced from global climate models (GCMs) because of their too...

Full description

Bibliographic Details
Main Authors: Agosta, Cécile, Fettweis, Xavier, Gallée, Hubert
Format: Conference Object
Language:English
Published: 2014
Subjects:
Online Access:https://orbi.uliege.be/handle/2268/168472
https://orbi.uliege.be/bitstream/2268/168472/1/Agosta_IGS2014.pdf
Description
Summary:The Antarctic ice-sheet surface mass balance (SMB) is a significant contribution to sea level changes which may mitigate the rise in sea level in a warmer climate, but this term is still poorly known. The Antarctic SMB cannot be directly deduced from global climate models (GCMs) because of their too low resolution (~100 km) and their unadapted physic over cold and snow-covered areas. That is why the use of a regional climate models (RCM) specifically developed for polar regions is particularly relevant. We present here new estimations of the Antarctic SMB changes for the 20th and the 21st century at 40 km of resolution with the MAR (Modèle Atmosphérique Régional) RCM. Recent studies showed that large scale forcing from GCMs was the main source of uncertainty for RCM-deduced SMB, thus we first present a carefully analysis of the CMIP5 GCMs (used in the AR5 IPCC report) compared to the ERA-Interim reanalysis over the Antarctic region, from which we could select the less biased large scale forcing for MAR. We thus show the Antarctic SMB evolution as modeled with MAR forced by ACCESS1-3 for RCP 4.5 and 8.5 greenhouse gaz scenarios. We evaluate our outputs by comparing MAR forced by ACCESS1-3 and ERA-Interim for the 1980-2000 period to more than 2700 quality-controlled observations and to surface meteorological data from the READER database. We then give SMB changes estimations for the 21st century together with an analysis of uncertainties coming from the MAR model, the GCM forcing and the greenhouse gaz scenarios.