A benchmark dataset of in situ Antarctic surface melt rates and energy balance

• Published in: Journal of glaciology Vol. 66; no. 256; pp. 291 - 302
• Main Authors: Jakobs, Constantijn L., Reijmer, Carleen H., Smeets, C. J. P. Paul, Trusel, Luke D., van de Berg, Willem Jan, van den Broeke, Michiel R., van Wessem, J. Melchior
• Format: Journal Article
• Language: English
• Published: Cambridge Cambridge University Press 01.04.2020
• Subjects: Antarctic glaciology; Antarctic ice sheet; Benchmarks; Climate models; Datasets; Energy balance; Enthalpy; Foehn; Glaciation; Humidity; Ice; Ice sheets; Ice shelves; ice/atmosphere interactions; Land ice; melt-surface; Polar environments; Radiation; Radiation absorption; Regional climates; Sea level; Sensible heat; Sensors; Short wave radiation; snow/ice surface processes; Stability; Summer; Temperature; Turbulent fluxes; Viability; Weather stations; Antarctica
• ISSN: 0022-1430; 1727-5652
• DOI: 10.1017/jog.2020.6

Abstract Surface melt on the coastal Antarctic ice sheet (AIS) determines the viability of its ice shelves and the stability of the grounded ice sheet, but very few in situ melt rate estimates exist to date. Here we present a benchmark dataset of in situ surface melt rates and energy balance from nine sites in the eastern Antarctic Peninsula (AP) and coastal Dronning Maud Land (DML), East Antarctica, seven of which are located on AIS ice shelves. Meteorological time series from eight automatic and one staffed weather station (Neumayer), ranging in length from 15 months to almost 24 years, serve as input for an energy-balance model to obtain consistent surface melt rates and energy-balance results. We find that surface melt rates exhibit large temporal, spatial and process variability. Intermittent summer melt in coastal DML is primarily driven by absorption of shortwave radiation, while non-summer melt events in the eastern AP occur during föhn events that force a large downward directed turbulent flux of sensible heat. We use the in situ surface melt rate dataset to evaluate melt rates from the regional atmospheric climate model RACMO2 and validate a melt product from the QuikSCAT satellite.