Large ensemble of downscaled historical daily snowfall from an earth system model to 5.5 km resolution over Dronning Maud Land, Antarctica

• Published in: Earth System Science Data
• Main Authors: Ghilain, Nicolas, Vannitsem, Stéphane, Dalaiden, Quentin, Goosse, Hugues, De Cruz, Lesley, Wei, Wenguang
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Physics and Astronomy; General Earth and Planetary Sciences; SURFACE MASS-BALANCE; ICE CORE; FIRN CORES; CLIMATE; ACCUMULATION; VARIABILITY; PRECIPITATION; TEMPERATURE; IMPACT; SHELF; East Antarctica; Dronning Maud Land; Antarc*; Antarctica; ice core
• Online Access: https://biblio.ugent.be/publication/01GT72GZNKE8G7KYHSCNXFMH90; http://hdl.handle.net/1854/LU-01GT72GZNKE8G7KYHSCNXFMH90; https://doi.org/10.5194/essd-14-1901-2022; https://biblio.ugent.be/publication/01GT72GZNKE8G7KYHSCNXFMH90/file/01H16RNEX3TC1DAYN269VE9Z67

We explore a methodology to statistically downscale snowfall - the primary driver of surface mass balance in Antarctica - from an ensemble of historical (1850-present day) simulations performed with an earth system model over the coastal region of Dronning Maud Land (East Antarctica). This approach consists of associating daily snowfall simulations from a polar-oriented regional atmospheric climate model at 5.5 km spatial resolution with specific weather patterns observed over 1979-2010 CE with the atmospheric reanalyses ERAInterim and ERA5. This association is then used to generate the spatial distribution of snowfall for the period from 1850 to present day for an ensemble of 10 members from the Community Earth System Model (CESM2). The new dataset of daily and yearly snowfall accumulation based on this methodology is presented in this paper (MASS2ANT dataset; https://doi.org/10.5281/zenodo.4287517; Ghilain et al., 2021). Based on a comparison with available ice cores and spatial reconstructions, our results show that the spatio-temporal distribution of snowfall is improved in the downscaled dataset compared with the CESM2 simulations. This dataset thus provides information that may be useful in identifying the large-scale patterns associated with the local precipitation conditions and their changes over the past century.