Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars

• Published in: The Cryosphere
• Main Authors: N. Souverijns, A. Gossart, S. Lhermitte, I. V. Gorodetskaya, J. Grazioli, A. Berne, C. Duran-Alarcon, B. Boudevillain, C. Genthon, C. Scarchilli, N. P. M. van Lipzig
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2018
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Antarctic; The Antarctic; Antarc*; Antarctica; Ice Sheet; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-12-3775-2018; https://doaj.org/article/9fb63e1da2a844d684e579c4ad20fcc6

In situ observations of snowfall over the Antarctic Ice Sheet are scarce. Currently, continent-wide assessments of snowfall are limited to information from the Cloud Profiling Radar on board the CloudSat satellite, which has not been evaluated up to now. In this study, snowfall derived from CloudSat is evaluated using three ground-based vertically profiling 24 GHz precipitation radars (Micro Rain Radars: MRRs). Firstly, using the MRR long-term measurement records, an assessment of the uncertainty caused by the low temporal sampling rate of CloudSat (one revisit per 2.1 to 4.5 days) is performed. The 10–90th-percentile temporal sampling uncertainty in the snowfall climatology varies between 30 % and 40 % depending on the latitudinal location and revisit time of CloudSat. Secondly, an evaluation of the snowfall climatology indicates that the CloudSat product, derived at a resolution of 1 ∘ latitude by 2 ∘ longitude, is able to accurately represent the snowfall climatology at the three MRR sites (biases < 15 %), outperforming ERA-Interim. For coarser and finer resolutions, the performance drops as a result of higher omission errors by CloudSat. Moreover, the CloudSat product does not perform well in simulating individual snowfall events. Since the difference between the MRRs and the CloudSat climatology are limited and the temporal uncertainty is lower than current Climate Model Intercomparison Project Phase 5 (CMIP5) snowfall variability, our results imply that the CloudSat product is valuable for climate model evaluation purposes.