Abstract

Abstract. Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.

Highlights

  • Projected 21st century increase in the Antarctic surface mass balance (SMB) due to higher snowfall rates is expected to partly compensate for eustatic sea-level rise (SLR) due to opposite changes in almost all other components affecting global sea level (Agosta et al, 2013; Ligtenberg et al, 2013; Lenaerts et al, 2016)

  • Mean SLP differences for ARPEGE simulations driven by NorESM1-M (ARP–NOR-20) and MIROC-ESM (ARP–MIR-20) historical sea surface conditions (SSCs) can be seen respectively in Fig. 2b and c

  • This study presented the first general evaluation of the capability of the atmosphere general circulation model (AGCM) ARPEGE to reproduce atmospheric general circulation of the high southern latitudes and the surface climate of the Antarctic Ice Sheet

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Summary

Introduction

Projected 21st century increase in the Antarctic surface mass balance (SMB) due to higher snowfall rates is expected to partly compensate for eustatic sea-level rise (SLR) due to opposite changes in almost all other components affecting global sea level (Agosta et al, 2013; Ligtenberg et al, 2013; Lenaerts et al, 2016). Most of the coupled atmosphere–ocean global circulation models (AOGCMs or CGCMs), such as those participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al, 2012), struggle to reproduce the seasonal cycle of SIE around Antarctica, and very few of them were able to reproduce the positive trend observed at the end of the 20th century (Turner et al, 2013) This is problematic because Krinner et al (2014) showed that atmospheric model simulations of the Antarctic climate are very sensitive to the prescribed sea surface conditions (SSCs), that is sea surface temperatures (SSTs) and sea ice concentration (SIC). It is expected that the signal due to the current anthropogenic climate change will take over the natural variability of Antarctic climate by the middle of the twentyfirst century (Previdi and Polvani, 2016). Favier et al (2017) and Lenaerts et al (2019) provide more complete reviews of the current understanding of the regional climate and surface mass balance of Antarctica and of the key processes that determine their evolution

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