Spatial and temporal variability of snowfall over Greenland from CloudSat observations

Abstract

Abstract. We use the CloudSat 2006–2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z–S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z–S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34±7.5 cm yr−1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z–S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30 cm yr−1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24 cm yr−1, depending on the assumed snowpack density and from CloudSat 23±4.5 cm yr−1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months.

Snowfall distribution and its response to the Arctic Oscillation: an evaluation of HighResMIP models in the Arctic using CPR/CloudSat observations

“…Since the reanalyses routinely assimilate water vapor from satellite observations, this integrated accumulation is well constrained by independent satellite observations and provides a strong constraint on the net snowfall over the ice sheet. This result is further supported by Boening et al (2012), who show remarkable consistency between estimates of recent Antarctic snowfall variability derived from reanalyses and CloudSat and completely independent ice sheet mass estimates from the Gravity Recovery and Climate Explorer (GRACE) satellite.…”

The Prevalence of Precipitation from Polar Supercooled Clouds

“…The impact of ground-based versus space-borne effective hmin (typically ~0.3 and ~1.2 km, respectively) on surface precipitation occurrence was estimated at both sites to be roughly ±10 percentage points, suggesting hydrometeor nucleation, growth, evaporation, or sublimation within this "blind zone" (not shown; cf. Bennartz et al, 2019;Castellani et al, 2015;Maahn et al, 2014). We note that the impact of the blind zone between the surface and ground-based hmin on precipitation occurrence using high radar sensitivities, similar to those used here, is absent from the literature to our knowledge and merits a dedicated study.…”

The Precipitation Imaging Package: Assessment of Microphysical and Bulk Characteristics of Snow

“…However, other studies have indicated 30-40% spaceborne radar overestimates compared to ground measurements, with results strongly geographically and latitudinally dependent [9]. Additionally, the presence of orography adversely impacts both ground and space-based radars, resulting in underestimation biases >70% [25,26]. In situ ground-based observations of snowfall accumulation also suffer from relatively large uncertainties, as intercomparisons have shown that gauges are biased low, with as much as 50% of the accumulation missed when unshielded and 12-27% with a single perimeter fence [27][28][29].…”