Year: 2025
Type: article
Abstract: . Perennial firn aquifers (PFAs) are year-round bodies of liquid water within firn, which modulate meltwater runoff to crevasses, potentially impacting ice-shelf and ice-sheet stability. Recently identified in the Antarctic Peninsula (AP), PFAs form in regions with both high surface melt and snow accumulation rates, and are expected to expand due to the anticipated increase in melt and snowfall. Using a firn model to predict future Antarctic PFAs for multiple climatic forcings is computationally expensive. To overcome this, we developed an XGBoost emulator, a fast machine learning model, to approximate a firn model. The PFA emulator was trained with simulations from the firn densification model IMAU-FDM, forced by three emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of the combined regional climate model (RCM) RACMO2.3p2 and general circulation model (GCM) CESM2. Using a scenario and spatial blocking evaluation approach, we found that the emulator successfully explains at least 89 % of PFA presence and meltwater storage variance. Using the PFA emulator, we predict future PFAs (2015–2100) for nine additional forcings from the RCMs MAR and HIRHAM in combination with five GCMs. Under SSP1-2.6 and SSP2-4.5, PFAs remain mostly restricted to the AP. For SSP5-8.5, PFAs expand to Ellsworth Land in West Antarctica, and Enderby Land in East Antarctica. For climatic forcings from RACMO and MAR, we find that liquid water input (melt and rain) and snow accumulation are good predictors for PFA occurrence. However, HIRHAM predicts considerably less surface melt and accumulation for a given temperature than MAR and RACMO do, resulting in less realistic PFA predictions. Overall, our findings show that PFAs will likely expand in a warmer Antarctica, irrespective of the emission scenario.
Source: The cryosphere
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,574
OpenAlex ID: W4415647155
