Paleoclimatologists rely on ice cores extracted from polar ice sheets to reconstruct atmospheric conditions over hundreds of millennia. By measuring the isotopic composition of oxygen trapped in air bubbles, researchers can infer historical global temperatures. A common challenge in this field is the "diffusion effect," where gases migrate within the ice over time, potentially blurring the temporal resolution of the data. While recent computational models have attempted to correct for this migration, critics argue that these models assume a degree of homogeneity in the ice structure that rarely exists in nature. Specifically, the presence of micro-layers formed by seasonal melting and refreezing creates irregular barriers to gas movement. Therefore, a model that applies a uniform diffusion constant across an entire core may inadvertently smooth out rapid, short-term climatic shifts, such as the Younger Dryas stadial, that are crucial for understanding current climate sensitivity. Despite these limitations, ice core data remain the "gold standard" for long-term climate modeling, provided that the inherent uncertainty of the temporal mapping is acknowledged.