Greenland surface mass balance simulated by a regional climate model and comparison with satellite derived data in 1990-1991

• Published in: Climate Dynamics
• Main Authors: Fettweis, Xavier, Gallée, Hubert, Lefebre, Filip, van Ypersele, Jean-Pascal
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science & Business Media B.V. 2005
• Subjects: Greenland; melt; regional modelling; Physical; chemical; mathematical & earth Sciences; Earth sciences & physical geography; Physique; chimie; mathématiques & sciences de la terre; Sciences de la terre & géographie physique; Ice Sheet
• Online Access: https://orbi.uliege.be/handle/2268/14755; https://orbi.uliege.be/bitstream/2268/14755/1/Fettweis-2005-Draft.pdf; https://doi.org/10.1007/s00382-005-0010-y

peer reviewed The 1990 and 1991 ablation seasons over Greenland are simulated with a coupled atmosphere-snow regional climate model with a 25-km horizontal resolution. The simulated snow water content allows a direct comparison with the satellite-derived melt signal. The model is forced with 6-hourly ERA-40 reanalysis at its boundaries. An evaluation of the simulated precipitation and a comparison of the modelled melt zone and the surface albedo with remote sensing observations are presented. Both the distribution and quantity of the simulated precipitation agree with observations from coastal weather stations, estimates from other models and the ERA-40 reanalysis. There are overestimations along the steep eastern coast, which are most likely due to the “topographic barrier effect”. The simulated extent and time evolution of the wet snow zone compare generally well with satellite-derived data, except during rainfall events on the ice sheet and because of a bias in the passive microwave retrieved melt signal. Although satellite-based surface albedo retrieval is only valid in the case of clear sky, the interpolation and the correction of these data enable us to validate the simulated albedo on the scale of the whole Greenland. These two comparisons highlight a large sensitivity of the remote sensing observations to weather conditions. Our high-resolution climate model was used to improve the retrieval algorithms by taking more fully into account the atmosphere variability. Finally, the good agreement of the simulated melting surface with the improved satellite signal allows a detailed estimation of the melting volume from the simulation.