Estimates of past climatic conditions are commonly made by inferring the magnitude of ELA depression in mountainous areas. This, however, requires that “present and past glaciers can be approximately standardized for size, shape, and surrounding topography, and the same ELA determination method can be used for both time periods.”¹ Inferring past climate from glacial evidence also requires that we can accurately relate glacial deposits among different basins. While that may be straightforward for LGM-scale advances, it is much more difficult for smaller ones such as the Recess Peak type in the Sierra Nevada. To account for the factors mentioned above, and provide a new method for inter-relating glacial deposits, we developed a set of tools to simulate, in 2D, the response of alpine glaciers to climate change. These consist of (1) a snow- and energy-balance model to predict the net annual accumulation of snow in high-relief terrain and (2) a vertically integrated ice-flow model that simulates the growth and decay of glaciers as the surface boundary conditions change. Together these models allow us to predict the distribution of glaciers under a wide variety of climatic conditions, as well as their sensitivity to parameters that are difficult to estimate for existing glaciers, let alone those long since vanished.

Applying these models to the area surrounding Bishop Creek, California yields new and intriguing information about the extensive glacial deposits of the region. The modern precipitation distribution is preserved in differences in glacial extent between basins. Sensitivity of terminus position to climate change is low for Tahoe-age glaciers in Bishop Creek but reasonably large for the only slightly smaller Tioga maximum advances. Significant differences in the distribution of glaciers can exist between different climatic conditions that yield the same extent for a given reference glacier. AARs of simulated glaciers are typically ~2/3, but can be considerably higher under cold, dry conditions. Of the multitude of potential applications for such modeling, we find most exciting the ability to produce detailed maps predicting glacial extent under specific climatic conditions, thereby revealing where and why glacial deposits may be preserved.

1. T.C. Meierding (1982). Quaternary Research 18: 289-310.