HOW MUCH DATA DO WE NEED TO RECONSTRUCT PALEOELEVATION FROM PALEOCLIMATE DATA? (Invited Presentation)

The vast majority of paleoelevation estimates use paleoclimate data to infer elevation. In particular, to estimate paleoelevation from paleoclimate data, we are often interested in determining a reasonable baseline or average climate value (e.g. temperature or δ¹⁸O of precipitation) for a particular point in time. However, the data generated for paleoelevation studies are often collected at temporal resolutions of 0.5 myr/sample or even lower, which is substantially lower than the timescales of many significant paleoclimate changes, such as those that resulting from orbital variations (10 kyr – 100 kyr) and/or rapid carbon cycle perturbations. In addition, the recognition that autogenic processes can create aliasing and incompleteness of some terrestrial paleoclimate records means there may be limits to the temporal resolution that can be achieved, regardless of sampling density (e.g. Foreman and Straub, 2017), and this aliasing has the potential to skew records away from a “true” average climate value. In this talk, I’ll use data from the Bighorn Basin that includes a high temporal resolution record (~14 kyr/sample) spanning two Early Eocene hyperthermals to examine the effects of different resolution sampling on estimates of “average” climate, and then examine how that in turn affects paleoelevation estimates.

Foreman, B.Z. & Straub, K.M. 2017. Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records. Science Advances, v.3 (9).