GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet
Authors: Fettweis Xavier , Hofer Stefan , Krebs-Kanzow Uta , Amory Charles , Aoki Teruo , Berends Constantijn J. , Born Andreas , Box Jason E. , Delhasse Alison , Fujita Koji , Gierz Paul , Goelzer Heiko , Hanna Edward , Hashimoto Akihiro , Huybrechts Philippe , Kapsch Marie-Luise , King Michalea D. , Kittel Christoph , Lang Charlotte , Langen Peter L. , Lenaerts Jan T. M. , Liston Glen E. , Lohmann Gerrit , Mernild Sebastian H. , Mikolajewicz Uwe , Modali Kameswarrao , Mottram Ruth H. , Niwano Masashi , Noël Brice , Ryan Jonathan C. , Smith Amy , Streffing Jan , Tedesco Marco , van de Berg Willem Jan , van den Broeke Michiel , van de Wal Roderik S. W. , van Kampenhout Leo , Wilton David , Wouters Bert , Ziemen Florian , Zolles Tobias 
Published: November 2020

Abstract. Observations and models agree that the Greenland Ice Sheet (GrIS)
surface mass balance (SMB) has decreased since the end of the 1990s due to
an increase in meltwater runoff and that this trend will accelerate in the
future. However, large uncertainties remain, partly due to different
approaches for modelling the GrIS SMB, which have to weigh physical
complexity or low computing time, different spatial and temporal
resolutions, different forcing fields, and different ice sheet
topographies and extents, which collectively make an inter-comparison
difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to
refine these uncertainties by intercomparing 13 models of four types which
were forced with the same ERA-Interim reanalysis forcing fields, except for
two global models. We interpolate all modelled SMB fields onto a common ice
sheet mask at 1 km horizontal resolution for the period 1980–2012 and score
the outputs against (1) SMB estimates from a combination of gravimetric
remote sensing data from GRACE and measured ice discharge; (2) ice cores,
snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent
from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the
largest spread among models can be found around the margins of the ice
sheet, highlighting model deficiencies in an accurate representation of the
GrIS ablation zone extent and processes related to surface melt and runoff.
Overall, polar regional climate models (RCMs) perform the best compared to
observations, in particular for simulating precipitation patterns. However,
other simpler and faster models have biases of the same order as RCMs
compared with observations and therefore remain useful tools for long-term
simulations or coupling with ice sheet models. Finally, it is interesting to
note that the ensemble mean of the 13 models produces the best estimate of
the present-day SMB relative to observations, suggesting that biases are not
systematic among models and that this ensemble estimate can be used as a
reference for current climate when carrying out future model developments.
However, a higher density of in situ SMB observations is required,
especially in the south-east accumulation zone, where the model spread can
reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.