Evaluation of Synoptic Snowfall on the Antarctic Ice Sheet Based on CloudSat, In-Situ Observations and Atmospheric Reanalysis Datasets

Abstract

Snowfall data are vital in calculating the surface mass balance of the Antarctic Ice Sheet (AIS), where in-situ and satellite measurements are sparse at synoptic timescales. CloudSat data are used to construct Antarctic snowfall data at synoptic timescales to compensate for the sparseness of synoptic snowfall data on the AIS and to better understand its surface mass balance. Synoptic CloudSat snowfall data are evaluated by comparison with daily snow accumulation measurements from ten automatic weather stations (AWSs) and the fifth generation of the European Centre for Medium-Range Weather Forecasts climate reanalysis (ERA5) snowfall. Synoptic snowfall data were constructed based on the CloudSat measurements within a radius of 1.41 • . The results show that reconstructed CloudSat snowfall at daily and two-day resolutions cover about 28% and 29% of the area of the AIS, respectively. Daily CloudSat snowfall and AWS snow accumulation have similar trends at all stations. While influenced by stronger winds, >73.3% of extreme snow accumulation events correspond to snowfall at eight stations. Even if the CloudSat snowfall data have not been assimilated into the ERA5 dataset, the synoptic CloudSat snowfall data are almost identical to the daily ERA5 snowfall with only small biases (average root mean square error and mean absolute error < 3.9 mm/day). Agreement among the three datasets suggests that the CloudSat data can provide reliable synoptic snowfall data in most areas of the AIS. The ERA5 dataset captures a large number of extreme snowfall events at all AWSs, with capture rates varying from 56% to 88%. There are still high uncertainties in ERA5. Nevertheless, the result suggests that ERA5 can be used to represent actual snowfall events on the AIS at synoptic timescale.CloudSat has recently become the most useful tool for directly measuring solid precipitation (i.e., snowfall) on the AIS [9]. The cloud profiling radar (CPR) system onboard CloudSat enables the direct observation of precipitation throughout the atmosphere and can measure light precipitation [10,11]. The CloudSat snowfall retrieval products have been used to reconstruct annual and seasonal snowfall on the AIS [12][13][14][15][16]. Monthly CloudSat snowfall data have been examined by snow accumulation measurements from automatic weather stations (AWSs) [17]. However, there are few attempts to use ground-based measurements (e.g., micro-rain radar (MRR)) to examine the CloudSat snowfall over the AIS at shorter timescales [5,18,19] because there is currently no precipitation gauge network and few continuous snowfall measurements for the AIS [5,20]. CloudSat provides a possible way to solve these problems.CloudSat has a 16-day repeat period covering regions from 82 • N to 82 • S. The density of radar footprints increases with the rise of latitude. The daily overpass frequency of radar measurements for each grid box is between 0.3 and 1.3 days over continental Antarctica at a resolution of 1 • latitude × 1.5 • longitude [17]. Such a temporal resolution is enha...

The AntSMB dataset: a comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

“…For annually resolved archives (ice core, stake, and stake network measurements), the duration of records included in this dataset should be at least 10 years but smaller than 1000 years. For the multi-year-averaged observations, the included records for the average span more than 3 years, which is the minimum number of years for an accurate estimation of the mean local SMB with an uncertainty of smaller than 10 % (Magand et al, 2007).…”

“…Thirdly, the different kinds of record are quality-checked to the highest degree possible and then included in the dataset. (1) To ensure the multi-year-averaged SMB data are reliable at each site, we select the data determined by the anthropogenic radionuclides and volcanic horizons with errors of smaller than 10 % or stake measurements for more than 3 years, as suggested by Magand et al (2007). The records with dating based both on stable isotopes and chemical markers and on natural radionuclides are reliable (Magand et al, 2007) and thus included in the dataset.…”

“…Due to logistical constraints in the harsh environment, gaps in the spatial coverage of SMB measurements are still large, and long-term samplings are also scarce (Favier et al, 2013). As a result, substantial caveats have been encountered when quantifying SMB at the ice sheet scale by using simple interpolation of these observations (Magand et al, 2007;Genthon et al, 2009). Climate models and various atmospheric reanalysis products provide an important choice of how to assess SMB for large areas.…”

“…Vaughan and Russell (1997) performed pioneering work to compile all multi-year-averaged SMB field measurement data over the AIS, and this compilation was introduced in detail by Vaughan et al (1999). However, according to Magand et al (2007), this dataset includes a lot of unreliable data and should be used with caution. To improve this, Favier et al (2013) updated the database using the new field measurements carried out during 1999-2012, through quality control proposed by Magand et al (2007).…”

“…However, according to Magand et al (2007), this dataset includes a lot of unreliable data and should be used with caution. To improve this, Favier et al (2013) updated the database using the new field measurements carried out during 1999-2012, through quality control proposed by Magand et al (2007). Recently, several compilations of SMB measurements at an annual resolution have been published (e.g., Mayewski and Dixon, 2013;Altnau et al, 2015;Thomas et al, 2017;Montgomery et al, 2018).…”