Understanding surface melt in Antarctica and implications for future ice sheet evolution

• Main Author: Yaowen Zheng
• Format: Thesis
• Language: unknown
• Published: 2024
• Subjects: Climate change science not elsewhere classified; Geophysics not elsewhere classified; Glaciology; Other earth sciences not elsewhere classified; Surface melt; Antarctica; Sea level rise; Antarctic Ice Sheet; Climate change; Positive Degree Day; Ice sheet modelling; Ice shelf collapse; IPCC; School: School of Geography; Environment and Earth Sciences; Unit: Antarctic Research Centre; 370699 Geophysics not elsewhere classified; 370902 Glaciology; 370299 Climate change science not elsewhere classified; 379999 Other earth sciences not elsewhere classified; 190503 Effects of climate change on Antarctic and sub-Antarctic environments (excl. social impacts); 190502 Climate variability (excl. social impacts); 280107 Expanding knowledge in the earth sciences; Degree Discipline: Geophysics; Degree Name: Doctor of Philosophy; Degree Level: Doctoral; Antarc*; Antarctic; Greenland; Ice Sheet; Ice Shelf; Ice Shelves
• Online Access: https://doi.org/10.26686/wgtn.25481320; https://figshare.com/articles/thesis/Understanding_surface_melt_in_Antarctica_and_implications_for_future_ice_sheet_evolution/25481320

Global mean sea level (GMSL) is projected to continue rising this century, potentially impacting up to 1 billion people by 2050 (Lee et al., 2023). Antarctica, as the Earth’s largest ice reservoir with a sea level equivalent volume of around 58 meters (Morlighem et al., 2020), could significantly impact the magnitude of future sea level rise. However, how much sea level rise will be caused by the Antarctic Ice Sheet (AIS) is highly uncertain (Rintoul et al., 2018), partly because of unclear future stability of Antarctic ice shelves. Surface melt has been identified as a crucial factor contributing to ice shelf collapse (Rott et al., 1996; van den Broeke, 2005; Trusel et al., 2015) through mechanisms of hydrofracturing (Lai et al., 2020). Projections have shown that the magnitude of surface melt will increase and the melt extent will be widespread (Trusel et al., 2015; Gilbert and Kittel, 2021). However, the distribution of future surface melt is not well known at high spatial resolutions. This is because climate models that employ comprehensive surface energy balance (SEB) schemes are too computationally expensive to run at fine resolutions (van den Broeke et al., 2023). By contrast, temperature-index models, such as the positive degree-day (PDD) model, are computationally efficient and have been utilized for snowmelt estimation for more than 90 years (Rango and Martinec, 1995), offering an alternative approach for future melt projections. However, the PDD parameters commonly used for AIS modelling are typically based on those derived for the Greenland Ice Sheet. An assessment of the viability of the PDD modelling approach for AIS surface melt projections has not yet been conducted, and the accuracy of the PDD model in estimating surface melting on the AIS remains unclear. This thesis first comprehensively assesses the PDD model for estimating surface melt on the AIS. The results from the assessment show that a PDD model with spatially-uniform parameters, when compared to estimates of surface melt days from ...