Future projected changes in drivers, AEWE and their impacts on surface melt, firn and ocean melting of ice shelves.
Workpackage 4 of the PICANTE project.
In this workpackage we will explore the impact of AEWE using multi-model ensembles of regional climate models, novel satellite observations, and high-resolution process-based modelling to quantify the impacts of AEWE for the past, present and future.
We will explore the changes in trends and variability in the large-scale and weather-system drivers of AEWE identified in WP1 and WP3 using large ensembles of projections, as well as a storyline approach.
To determine the detailed response of Antarctic meteorological extremes to future circulation changes we will examine output from a novel multi-model ensemble of RCM projections at 11-km resolution from present-day to 2100 developed by the PolarRES project (led by project partner Mooney).
We will explore the impact of AEWE on surface melt using novel methods of measuring ice sheet surface runoff and accumulation from satellite observations to create surface mass balance time series over the ice shelves from 2011 to present.
We will perform the first systematic assessment of the role of AEWE on firn evolution using the community firn model, to understand the direct and cumulative impact of past and current AEWE. We will simulate future firn evolution using this model, to assess future ice shelf viability. This will be the first time that a firn model will be used to make future projections.
We will also explore the impact of AEWE on ocean melting of ice shelves in West Antarctica. Wind anomalies are known to influence ice-shelf melting at interannual and decadal timescales, but the effect of much shorter-term extreme events is not known. For the AEWE identified in workpackage 1, we will use existing ocean simulations of the Amundsen Sea, and new high temporal resolution simulations, to explore their impact on ocean temperatures and ice-shelf melting, and to quantify the contribution of these extreme events to anomalies on longer timescales.