Several decades of ice-penetrating radar surveys of the Greenland and Antarctic ice sheets have observed numerous widespread internal reflections. Analysis of this radiostratigraphy has produced valuable insights into ice sheet dynamics and motivates additional mapping of these reflections. Here we present a comprehensive deep radiostratigraphy of the Greenland Ice Sheet from airborne deep ice-penetrating radar data collected over Greenland by The University of Kansas between 1993 and 2013. To map this radiostratigraphy efficiently, we developed new techniques for predicting reflection slope from the phase recorded by coherent radars. When integrated along track, these slope fields predict the radiostratigraphy and simplify semiautomatic reflection tracing. Core-intersecting reflections were dated using synchronized depth-age relationships for six deep ice cores. Additional reflections were dated by matching reflections between transects and by extending reflection-inferred depth-age relationships using the local effective vertical strain rate. The oldest reflections, dating to the Eemian period, are found mostly in the northern part of the ice sheet. Within the onset regions of several fast-flowing outlet glaciers and ice streams, reflections typically do not conform to the bed topography. Disrupted radiostratigraphy is also observed in a region north of the Northeast Greenland Ice Stream that is not presently flowing rapidly. Dated reflections are used to generate a gridded age volume for most of the ice sheet and also to determine the depths of key climate transitions that were not observed directly. This radiostratigraphy provides a new constraint on the dynamics and history of the Greenland Ice Sheet.
Key points: Phase information predicts reflection slope and simplifies reflection tracingReflections can be dated away from ice cores using a simple ice flow modelRadiostratigraphy is often disrupted near the onset of fast ice flow.
Keywords: Greenland Ice Sheet; ice core; ice-penetrating dynamics; ice-sheet dynamics.