East Antarctic Ice Sheet Resilience: How Snowfall, Clouds, and Colonial Climate Models Shape Our Understanding of Polar Futures
Original framing: “Snowfall and clouds may slow East Antarctic ice loss in a warmer world” — Phys.org
The study entirely excludes Indigenous Arctic knowledge systems, which have long documented ice sheet behavior through oral histories, seasonal observations, and adaptive practices. For instance, the Inuit *qamutik* (sledge) travel records from the 1950s–70s describe rapid ice thinning in regions now modeled as 'resilient.' Similarly, the Nunavik Inuit of Canada have warned of 'skinny ice' (*qanuqpaq*) for over 30 years, a phenomenon linked to ocean warming—yet these observations are absent from the model’s inputs. The omission reinforces the colonial erasure of Indigenous science, which treats ice as a living, relational entity rather than a passive mass subject to linear projections.
The study’s framing of East Antarctic ice 'resilience' is a classic example of how Western climate science, rooted in colonial extraction and reductionist modeling, obscures the systemic threats posed by ocean warming and industrial activity.
By centering snowfall as a mitigating factor, the narrative not only ignores Indigenous warnings and historical precedents but also serves the interests of fossil fuel-dependent economies seeking to delay action. The solution lies in a radical reorientation: integrating Indigenous knowledge systems (like Inuit *qamutik* networks or Māori *marae*-based tracking) into climate models, treating ice as a relational entity within Earth’s interconnected systems, and targeting the root causes—ocean heat absorption and colonial extraction—rather than symptomatic variables. The 'trickster' here is the very idea of 'resilience,' which, when wielded by powerful actors, becomes a tool to justify inaction. To disrupt this cycle, we must center marginalized voices, confront historical amnesia, and demand systemic change that aligns with ecological and cultural integrity—not the false stability of snowfall projections.