C23C-0809
Snow and firn density variability on the Greenland and Antarctic Ice Sheets from observations, the MAR regional climate model, and the RACMO firn model
Tuesday, 15 December 2015
Poster Hall (Moscone South)
Patrick M Alexander1,2, Lora Koenig3, Rajashree Datta2,4, Marco Tedesco2,5, Peter Kuipers Munneke6, Stefan Ligtenberg6, Xavier Fettweis7 and Michiel van den Broeke6, (1)NASA Goddard Institute for Space Studies, New York, NY, United States, (2)CUNY City College, New York, NY, United States, (3)National Snow and Ice Data Center, Boulder, CO, United States, (4)CUNY Graduate Center, New York, NY, United States, (5)Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, United States, (6)Utrecht University, Institute for Marine and Atmospheric Research, Utrecht, Netherlands, (7)University of Liège, Geography, Liège, Belgium
Abstract:
The density of snow and firn of the Greenland and Antarctic Ice Sheets (GrIS and AIS) is an important parameter in ice sheet surface mass balance (SMB). Snow and firn densities are needed to convert satellite- and airborne-derived snow thickness changes into surface mass changes. Moreover, density directly impacts SMB by influencing the amount of liquid water that can be stored in firn and snow at the ice sheet surface. Using recently updated density profiles from the SUMup community dataset, we examine spatial and temporal variations in measured densities over the GrIS and AIS, and evaluate modeled profiles from the Modèle Atmosphérique Régionale (MAR) RCM and the firn model of the Regional Atmospheric Climate Model (RACMO2). The MAR model tends to underestimate densities in the first meter of the snowpack over both ice sheets, although the biases are spatially variable. We provide results regarding the relationship between modeled biases and parameters such as the time and location of the sample profile, and climatology at the profile location. We also explore whether recent increases in surface air temperature and melting over the Greenland ice have led to changes in simulated density profiles.
