Simulations_gap_layers_HIGHTSI_FIPS_2012_Antarctic_Zhongshan_Station

We applied a 1‐D high‐resolution Thermodynamic Sea Ice and snow model HIGHTSI (Launiainen & Cheng, 1998). To simulate the evolution of snow and ice temperature profiles and mass balance, HIGHTSI solves nonlinear partial differential heat conduction equations, as well as melting and freezing proc...

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Bibliographic Details
Main Author: Jiechen Zhao
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2021
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Online Access:https://doi.org/10.5281/zenodo.4556514
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Summary:We applied a 1‐D high‐resolution Thermodynamic Sea Ice and snow model HIGHTSI (Launiainen & Cheng, 1998). To simulate the evolution of snow and ice temperature profiles and mass balance, HIGHTSI solves nonlinear partial differential heat conduction equations, as well as melting and freezing processes. Solar radiation absorbed in the ice highly depends on the bulk extinction coefficient κ and the depth of ice surface scattering layer (SSL), i.e., a layer where a major part of the incoming solar radiation is either scattered or absorbed. The depth of SSL typically increases towards the end of the melt season, finally reaching some 0.1 m (Light et al., 2015). The solar radiation attenuates more rapidly in SSL than in the internal layer below. The parameterization of penetration of solar radiation within snow and ice allows HIGHTSI to quantitatively simulate sub-surface melting of snow and ice. HIGHTSI has been validated extensively and applied widely in both process studies and operational services (Cheng et al., 2008, 2013; Wang et al., 2015; Merkouriadi et al., 2017, 2019; Mäkynen et al., 2020; Zhao et al., 2020). Detailed model parameterizations are given in Supporting Information Table S2. We made a control model run on an MYI floe covering the entire melting season from late spring (1 November 2011) until autumn (31 March 2012). The initial snow depth and ice thickness were 0.17 m and 1.5 m, respectively, based on in situ observations. In early November, in-ice temperature revealed a linear profile (Lei et al., 2010) and therefore used as an initial condition for the control run. The meteorological parameters observed by an automatic weather station (AWS) at the Chinese Zhongshan Station were used as model forcing. The wind speed (Va), air temperature (Ta), and relative humidity (Rh) were observed at 10 m height with one-minute time interval. The total cloud fraction (CN) was observed visually four times daily. Total precipitation (Prec) was observed at the Russian Progress Station, 1 km southeast of ...