John Imbrie (b. 1925) always had deep mathematical insight and facility. At Yale University he completed his PhD (1951) under Carl Dunbar working on Middle Devonian brachiopods where he employed a statistical technique—'reduced major axis regression'—to differentiate several subspecies. Later, in a study with Edwin Colbert at the American Museum of Natural History, he used the same technique to determine subtle, yet significant, variations in the growth patterns of Triassic Metoposaurid amphibians (1956). At about the same time as sedimentary facies analysis was becoming of increased interest, Imbrie sought to test what one might do with quantitative facies analysis by undertaking a decade-long study of the Lower Permian Florena Shale (Kansas) using multivariate cluster analysis to characterize different litho- and biofacies. Despite much hard work in the field and with a highdecibel desk calculator, the hoped for results were lackluster.
But neither the man nor the methods were wanting. The materials—fragmented, scattered invertebrate fossils imbedded in shales and limestones—permitted no more understanding than qualitative, eye-ball analysis. Even a late stage attack with the IBM computer at Columbia University merely groaned and brought forth similar mousey results.
What was needed was a problem whose material components (abundant planktonic microfossils) within well-characterized stratigraphic sequences (deep-sea Pleistocene cores) were suitably matched to the man's mind and his quantitative procedures. And, of course, the result was phenomenal: his empirical demonstration of the deep-sea data for the validity of Milankovitch Cycles as the forcing factors for large-scale global climate change. His scientific success was duly honored by awards, prizes, medals, and elections to distinguished honorary societies.
How did this happen?
On quantitative errors of two simplified unsteady models for simulating unidirectional nonlinear random waves on large scale in deep sea