Revisiting Winter Arctic Ice Mass Balance Observations With a 1‐D Model: Sensitivity Studies, Snow Density Estimation, Flooding, and Snow Ice Formation

• Published in: Journal of Geophysical Research: Oceans
• Main Authors: Gani, Sarah, Sirven, Jérôme, Sennéchael, Nathalie, Provost, Christine
• Other Authors: Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), ANR-10-EQPX-0032,IAOOS,Système d'observation de la glace, de l'atmopshère et de l'océan en Arctique(2010)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2019
• Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; Arctic; Sea ice; Svalbard
• Online Access: https://hal.science/hal-03015301; https://hal.science/hal-03015301/document; https://hal.science/hal-03015301/file/Gani_et_al-2019-Journal_of_Geophysical_Research__Oceans-1.pdf; https://doi.org/10.1029/2019JC015431

International audience We used a state‐of‐the art one‐dimensional snow and ice model (the LIM1D model), to simulate data collected in winter 2015 north of Svalbard with ice mass balance instruments. The quality of the simulations was assessed by comparing simulated temperature profiles and sea ice thicknesses with the data: The root‐mean‐square difference between observed and modeled temperature was 1.06 °C in snow and 0.19 °C in ice, and the root‐mean‐square difference between simulated and observed ice thickness was 2.0 cm (snow depth was prescribed). The long‐wave heat flux from the ERA‐I reanalysis was adequate to perform winter numerical simulations; in contrast, the ERA‐I air temperature induced large errors in the snow and ice temperature. Snow density had a direct impact on heat transfers and, thus, on the simulation. The joint use of the data and the simulations permitted the adjustment of the snow density profiles with a light (240 kg/m3) snow deposited on top of a denser (370 kg/m3) snow. The ice flooding, which occurred after a storm‐induced breakup of floes loaded with snow, was simulated by prescribing the observed lower limit of the snow. The simulations provided insights on the evolution of sea ice bulk salinity, brine fraction, and the amount of snow ice formed during the flooding event.