CNRM-ARPEGE v6.2.4 contribution to Antarctic Cordex

• Main Authors: Beaumet, Julien, Krinner, Gerhard, Déqué, Michel, Alias, Antoinette
• Format: Dataset
• Language: English
• Published: Zenodo 2020
• Subjects: Antarctic; Cordex; ARPEGE; Climate projection; Surface mass balance; Bias correction; The Antarctic; Antarc*; Antarctica; Ice Sheet; Sea ice
• Online Access: https://dx.doi.org/10.5281/zenodo.4059192; https://zenodo.org/record/4059192

This data set is a contribution to Antarctic Polar Cordex using the stretched grid capacity of CNRM-ARPEGE atmospheric GCM. Model outputs have been interpolated from the native ARPEGE grid, with horizontal resolution varying between 35kms (near the stretching pole) to 45 kms on the Antarctic continent, to the ANTi-44 domain (actual lon/lat). The data and metadata format respect almost all of Cordex/CMIP conventions (variables names, units, file names...). The data set consists in six simulations of 30 years time slots : 1981-2010 for "historical" simulations and 2071-2100 for future projections using radiative forcing from RCP8.5 scenario : - ARP-AMIP : amip-style control run driven by observed SST and sea-ice (1981-2100) - ARP-NOR-OC : Future projection driven by NorESM1-M RCP8.5 climate change signal on SST and sea-ice (2071-2100) - ARP-MIR-OC : Future projection driven by MIROC-ESM RCP8.5 climate change signal on SST and sea-ice (2071-2100) More details on these three simulations are given in Beaumet et al., 2019 ( 10.5194/tc-13-3023-2019) - ARP-AMIP-AC : Driven by observed SST and sea-ice + run-time flux bias correction* - ARP-NOR-AOC : Driven by same SST and sea-ice as NOR-OC + run-time flux bias correction* - ARP-MIR-AOC : Driven by same SST and sea-ice as MIR-OC + run-time flux bias correction* Empirical run-time bias correction uses correction terms derived from the climatological mean of tendency errors of a simulation nudged towards climate reanalysis (here ERA-Interim). The method is presented first in Guldberg et al., 2005 (10.1111/j.1600-0870.2005.00120.x) and Krinner et al., 2019 (10.1029/2018MS001438). The method applied with ARPEGE over Antarctica and the evalution of the simulation are presented in this paper : https://doi.org/10.5194/tc-2020-307 (In review) Outputs are available at daily time scale for near-surface atmospherique mean (tas), min (tasmin) and max (tasmax) temperature, total precipitation (pr), snowfall (prsn), snowmelt(snm), surface snow sublimation (sbl_i) and surface runoff (mrros). If you consider using these data, please email me ([e-mail]) to see how I can help and/or be involved. : Modelled surface mass balance of the Antarctic ice-sheet can be estimated using precipitation minus surface sublimation and runoff : SMB = pr - sbl_i - mrros