What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates

• Published in: The Cryosphere
• Main Authors: Mottram, Ruth, Hansen, Nicolaj, Kittel, Christoph, van Wessem, J. Melchior, Melchior, Agosta, Cécile, Amory, Charles, Boberg, Fredrik, van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, Nicole, P M, van Meijgaard, Erik, Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, Sebastian, B, Souverijns, Niels
• Other Authors: Danish Meteorological Institute (DMI), Université de Liège, Universiteit Utrecht / Utrecht University Utrecht, Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Catholic University of Leuven = Katholieke Universiteit Leuven (KU Leuven), Royal Netherlands Meteorological Institute (KNMI), British Antarctic Survey (BAS), Natural Environment Research Council (NERC), Met Office Hadley Centre (MOHC), United Kingdom Met Office Exeter, Danmarks Tekniske Universitet = Technical University of Denmark (DTU), This publication was supported by PROTECT. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 869304 and PROTECT contribution number 19.Acquisition of meteorological data in Adélie Land has been made with the financial and logistical support of the French Polar Institute IPEV (programme CALVA-1013). The authors appreciate the support of the University of Wisconsin-Madison Automatic Weather Station programme for the dataset, data display, and information (NSF grant no. 1924730).The COSMO-CLM2 integrations were supported by the Belgian Science Policy Office (BELSPO; grant no. 747 BR/143/A2/AEROCLOUD) and the Research Foundation Flanders (FWO; grant nos. 748 G0C2215N and GOF5318N; EOS ID: 30454083). Computational resources and services were provided by the Flemish Supercomputer Center, funded by the FWO and the Flemish Government, EWI department. Matthias Demuzere, Jan Lenaerts, Irina Gorodetskaya, and Sam Vanden Broucke are gratefully acknowledged for supporting the COSMO-CLM2 integrations. COSMO-CLM2 is the community model of the German regional climate research jointly further developed by the CLM community. Computational resources for MAR simulations have been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S. – FNRS) under grant no. 2.5020.11 and the Tier-1 supercomputer (Zenobe) of the Fédération Wallonie Bruxelles infrastructure funded by the Walloon Region under grant agreement no. 1117545. Christoph Kittel's work was supported by the Fonds de la Recherche Scientifique – FNRS under grant no. T.0002.16.Melchior van Wessen, Willem Jan van de Berg, and Erik van Meijgaard acknowledge the ECMWF for the use of their computing and archive facilities for the RACMO2 simulations.Ruth Mottram, Nicolaj Hansen, and Sebastian B. Simonsen acknowledge the ESA Climate Change Initiative for the Greenland ice sheet funded via ESA-ESRIN contract no. 4000104815/11/I-NB and the Sea Level Budget Closure CCI project funded via ESA-ESRIN contract no. 4000119910/17/I-NB. HIRHAM5 regional climate model simulations were carried out by Ruth Mottram and Fredrik Boberg as part of the ice2ice project, a European Research Council project under the European Community’s Seventh Framework Programme (FP7/ 2007–2013)/ ERC grant agreement 610055. Data analysis was supported by the Danish state through the National Centre for Climate Research (NCKF).
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2021
• Subjects: [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology; [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; Antarctic; Antarctic Peninsula; The Antarctic; Transantarctic Mountains; West Antarctica; Antarc*; Antarctica; Ice Sheet; Ice Shelves; The Cryosphere
• Online Access: https://hal.science/hal-03330157; https://hal.science/hal-03330157/document; https://hal.science/hal-03330157/file/tc-15-3751-2021.pdf; https://doi.org/10.5194/tc-15-3751-2021

International audience Abstract. We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica.