Significant Spatial Variability in Radar‐Derived West Antarctic Accumulation Linked to Surface Winds and Topography

Abstract

Across the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances (<25 km), complicating the derivation of ice sheet mass changes from altimetry and reducing how accurately field measurements can be spatially extrapolated. However, current atmospheric reanalyses have grid spacings (>25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine‐scale accumulation product from airborne snow radar observations by superimposing along‐track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large‐scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability (σrelative>40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p<0.01), confirming that subgrid‐scale accumulation variability is driven by snow redistribution by wind.

Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys

“…The magnitude of the correlation coefficient, however, is dependent on the length scale used to calculate the standard deviation. Dattler et al (2019) find a similar behavior between σ accumulation rate and σ MSWD. Visual inspection of Fig.…”

“…We then use this age to calculate spatially varying accumulation rates 315 along the entire segment as outlined by Medley et al (2015). In such a manner, we force the large-scale mean accumulation rates to those prescribed by MERRA-2 but allow for small-scale variability derived from the snow radar horizon picks in the absence of independent estimates of firn depth-age profiles (Dattler et al, 2019).…”

“…Therefore, there is no simple relationship 325 between surface slope, wind direction and snow accumulation rates. Previous work used the Mean Slope in the mean Wind Direction (MSWD) for studying relationships between surface slope and spatial variability in snow accumulation rates (e.g., Das et al, 2013;Dattler et al, 2019;Scambos et al, 2012). MSWD is defined as the scalar dot product between the surface slope with the mean wind direction (Scambos et al, 2012).…”

“…Previous Antarctic studies have reported relationships between surface slope, roughness and snow accumulation rates (e.g., Arcone et al, 2012;Dattler et al, 2019;Fahnestock et al, 2000;Grima et al, 2014;Hamilton, 2004;King et al, 2004). To better understand potential correlations between altimetry elevation biases and geophysical parameters of the ice surface, we are specifically studying the spatial and temporal variability of surface roughness and accumulation rate over the ICESat-2 validation site at 88° S. We use repeat high-resolution airborne data consisting of laser altimetry, snow and Ku-band radar and natural color imagery acquired as 55 part of the National Aeronautics and Space Administration's (NASA) Operation IceBridge (OIB) mission to analyze spatial and temporal variability in surface roughness, slope, accumulation rate, and Ku-band radar backscatter along a 1400 km circle around 88° S (Fig.…”

Reconciling the surface temperature–surface mass balance relationship in models and ice cores in Antarctica over the last two centuries

“…Winds can also impact surface accumulation over shorter spatial scales (10s of meters to kilometers) when they flow over surface topography. As surface winds flow over surface topography, they typically erode the windward side and deposit on the leeward side, thus reworking the SMB record spatially (Black and Budd, 1964;Budd, 1971;Dattler et al, 2019). If winds are very persistent in direction and speed, wind redistribution of the snow pack can create fields of dunes (Frezzotti et al, 2002b;Arcone et al, 2012a;Das et al, 2013) or blue ice areas (Spaulding et al, 2012).…”