Understanding the Role of Wind in Reducing the Surface Mass Balance Estimates over East Antarctica

Friday, 19 December 2014: 5:00 PM
Indrani Das1, Theodore A Scambos2, Lora Koenig3, Timothy T Creyts4, Robin E Bell1, Michiel R van den Broeke5, Jan Lenaerts6 and John Drysdale Paden7, (1)Lamont -Doherty Earth Observatory, Palisades, NY, United States, (2)Univ Colorado, Boulder, CO, United States, (3)NASA, Greenbelt, MD, United States, (4)Columbia University-LDEO, Palisades, NY, United States, (5)Utrecht University, Utrecht, Netherlands, (6)IMAU (Utrecht University), Utrecht, Netherlands, (7)University of Kansas, Lawrence, KS, United States
Accurate quantification of surface snow-accumulation over Antarctica is important for mass balance estimates and climate studies based on ice core records. An improved estimate of surface mass balance must include the significant role near-surface wind plays in the sublimation and redistribution of snow across Antarctica. We have developed an empirical model based on airborne radar and lidar observations, and modeled surface mass balance and wind fields to produce a continent-wide prediction of wind-scour zones over Antarctica. These zones have zero to negative surface mass balance, are located over locally steep ice sheet areas (>0.002) and controlled by bedrock topography. The near-surface winds accelerate over these zones, eroding and sublimating the surface snow. This scouring results in numerous localized regions (≤ 200 km2) with reduced surface accumulation. Each year, tens of gigatons of snow on the Antarctic ice sheet are ablated by persistent near-surface katabatic winds over these wind-scour zones. Large uncertainties remain in the surface mass balance estimates over East Antarctica as climate models do not adequately represent the small-scale physical processes that lead to mass loss through sublimation or redistribution over the wind-scour zones.

In this study, we integrate Operation IceBridge's snow radar over the Recovery Ice Stream with a series of ice core dielectric and depth-density profiles for improved surface mass balance estimates that reflect the mass loss over the wind-scour zones. Accurate surface mass balance estimates from snow radars require spatially variable depth-density profiles. Using an ensemble of firn cores, MODIS-derived surface snow grain size, modeled accumulation rates and surface temperatures from RACMO2, we assemble spatially variable depth-density profiles and use our mapping of snow density variations to estimate layer mass and net accumulation rates from snow radar layer data. Our study improves the quantification of regional surface mass balance and should improve the mass balance rates using mass budget methods.