Open AccessImplementation of a 1‐D Thermodynamic Model for Simulating the Winter‐Time Evolvement of Physical Properties of Snow and Ice Over the Arctic Ocean
Author(s) -
Kang EuiJong,
Sohn ByungJu,
Tonboe Rasmus Tage,
Dybkjær Gorm,
Holmlund Kenneth,
Kim JongMin,
Liu Chao
Publication year - 2021
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2020ms002448
Subject(s) - freeboard , snow , sea ice , climatology , geology , sea ice thickness , satellite , arctic , cryosphere , arctic ice pack , environmental science , sea ice growth processes , meteorology , atmospheric sciences , geomorphology , geography , oceanography , fluidized bed , aerospace engineering , engineering , waste management
Abstract This paper presents a sea ice prognostic model involving a one‐dimensional thermodynamic diffusion model, nudging satellite‐derived snow/ice temperatures, and two‐dimensional Lagrangian ice tracking. The aim of the model is to produce the evolvement of the physical properties of the snow and ice over the Arctic Ocean during the winter season. While the one‐dimensional column process solves the solution at a specific time and location, the evolvement of physical properties of the same ice target can be continuously simulated along the trajectory of ice movement determined by the Lagrangian tracking method. The main inputs were reanalysis‐based atmospheric forcings, thermal conditions constrained through nudging of snow skin temperature and snow‐ice interface temperature, and satellite‐derived ice motion vectors. The simulation results showed that the model can successfully reproduce well‐known regional features and geographical distributions of snow depth and ice thickness. The model‐simulated variables (i.e., snow depth, total freeboard, ice freeboard, ice thickness, and temperature) showed high correlations with the in situ or satellite measurements. In particular, the simulated temperatures were in excellent agreement with drifting buoy measurements. Since the nudging of the satellite‐derived temperature data into the model improved the thermal structure considerably, these data appear to be a key element for the successful simulation of other variables as well.