Satellite Observations of Precipitation Regimes over the Greenland Ice Sheet

Due to the rapidly warming Arctic environment, the Greenland Ice Sheet (GIS) is shrinking. Predicting the future mass balance of the GIS requires an in depth understanding of the cloud types that produce snowfall and the synoptic systems with which they are associated. Previous analysis using ground-based remote sensing instruments at Summit Station showed two distinct regimes of snowfall events: snowfall produced by mixed-phase clouds and snowfall produced by ice clouds. Above Summit Station, these two regimes have distinct characteristics, including cloud geometric depth, snowfall rate, air mass source and trajectory, and associated large scale flow patterns.

The work presented here utilizes the active sensors aboard NASA A-Train satellites to expand this analysis over the entire GIS. The two-channel LIDAR aboard CALIPSO is particularly sensitive to cloud liquid water, and, despite winter darkness and underlying icy surfaces, can discriminate between mixed-phase and fully-glaciated clouds. The millimeter-wavelength cloud profiling radar (CPR) aboard CloudSat is able to simultaneously determine if snowfall is present beneath the cloud. We leverage A-Train derived data products (2B-CLDCLASS-LIDAR, 2B-FLXHR-LIDAR, 2C-PRECIP-COLUMN, and 2C-SNOW-PROFILE) to composite case studies over Summit Station, comparing results from the ground-based and space-borne sensors. We then look over the full GIS, dividing snowfall events into the two regimes and documenting their frequency in time and space and approximating the snowfall rate and accumulation each produce. We use the ERA-I v5 reanalysis product to examine the synoptic scale patterns that dominate for the two regimes.