Spatial and temporal variability of snowfall over Greenland from CloudSat observations

Abstract

<p><strong>Abstract.</strong> We use the CloudSat data record 2006–2016 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 meters 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 so-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 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 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, depending on the assumed snowpack density, and from CloudSat 23 ± 4.5 cm/yr. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned under-estimation during summer months.</p>

Using CloudSat‐CPR Retrievals to Estimate Snow Accumulation in the Canadian Arctic

“…Additional uncertainty also arises from any near‐surface precipitation occurring within CloudSat's radar blind zone in the lowest 1,440 m of the atmosphere, where ground interference impacts the quality of CloudSat's retrievals. A recent comparison over Greenland displays similar findings from issues arising as a result of ground clutter over alpine regions influencing CPR retrievals of snowfall in the lowest precipitating bin (Bennartz et al, ). The presence of ground clutter contamination contributing to physically improbable snowfall rates is also clearly visible in the secondary reflectivity maximum (between 20 and 30 dBZ) in Figure a from Kulie and Bennartz (), as well as in the unphysically high near‐surface reflectivities (nearing 30 dBZ) for multiple CloudSat overpasses across Greenland in Figure 7 from the same study.…”

“…However, we note a general underestimation of approximately 50% in CloudSat snow accumulation throughout December and January across all stations. A contributing factor to the underestimation noted in CloudSat's 2C‐SNOW‐PROFILE snowfall has been previously attributed to the inability of the CPR to capture low cumuliform snowfall which comprise about 36% of global snowfall occurrence, within CloudSat's blind zone in the lowest 1.5 km (Bennartz et al, ; Kulie & Milani, ). The impact of near‐surface snowfall on CloudSat estimate underestimation is further noted in a study by Maahn et al (), which showed (for a similar high‐latitude location in Antarctica) that CloudSat underestimates total annual snowfall by approximately 10% due to shallow cumulus snowfall occurring within the radar blind zone.…”

Satellite Observations of Snowfall Regimes over the Greenland Ice Sheet

“…. Two recent studies have used CloudSat's CPR to look at snowfall over the GIS in particular: Lenaerts et al (2019) focused on GIS snowfall frequency and leveraged the satellite observations to evaluate climate model output; and Bennartz et al (2019) used the radar measurements to provide the first in-depth, observationally based snowfall rate estimates of the GIS.…”

“…by surface return. Contamination is most prevalent in regions of steep, icy topography where the digital elevation map used to determine the surface level does not exactly match conditions at the time of the overpass (Bennartz et al, 2019). Palerme et al (2019) showed that the edges of the GIS are particularly prone to clutter in the R04 version of 2CSP, but the updated elevation map in R05 has reduced the number of contaminated pixels.…”

Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet

“…Several studies have used CloudSat for model evaluation by producing gridded snowfall climatologies (i.e., mean annual snowfall rates) across the Arctic and Antarctica (Behrangi et al, ; Bennartz et al, ; Milani et al, ; Palerme et al, ; Palerme, Claud,et al, ; Palerme, et al, ). These climatologies have coarse spatial scales (e.g., 1 to 2° pixel size) to facilitate direct comparison with global climate models (GCMs).…”