Winter Arctic Sea Ice Volume Budget Decomposition from Satellite Observations and Model Simulations over the CryoSat-2 period (2010-2019)
Authors: Tsamados Michel , Racher Oliver , Holland Paul , Kimura Noriaki , Heorton Harry , Feltham Daniel , Schroeder David , Ridout Andy , Stroeve Julienne 
Published: March 2020

&lt;p&gt;In this study, satellite-derived observations of sea ice concentration, drift, and thickness are combined to provide a climatology and inter-annual monthly variability of the sea ice volume budget over the growth season for the CryoSat-2 period Octobre 2010 to April 2019. This allows the first wintertime observational decomposition of the dynamic (advection and divergence) and thermodynamic drivers of ice volume change.&lt;br&gt;&lt;br&gt;Dynamic and thermodynamic processes will be separated by applying similar methods to Holland and Kwok (2012), which decomposed the governing equation of ice concentration, C:&lt;br&gt;&lt;br&gt;[1] &amp;#8706;C/&amp;#8706;t + &amp;#8711;.(uC) = f_C - r&lt;br&gt;&lt;br&gt;where u is ice drift motion, f_C is thermodynamic freezing or melting, and r is the concentration change from mass-conserving mechanical ice redistribution processes which convert ice area to ice thickness, such as ridging and rafting. &amp;#8706;C/&amp;#8706;t represents ice intensification and &amp;#8711;.(uC) represents ice flux divergence, the dynamic contribution to ice concentration.&lt;br&gt;&lt;br&gt;Equation 1 can be rearranged and the dynamic contribution, &amp;#8711;.(uC), expanded to show the contributions from advection, (-u.&amp;#8711;C) and divergence, (-C&amp;#8711;.u), determining four terms:&lt;br&gt;&lt;br&gt;[2] &amp;#8706;C/&amp;#8706;t = -u.&amp;#8711;C - C&amp;#8711;.u + f - r&lt;br&gt;&lt;br&gt;The governing equation of the volume budget is of the same form but combines the thickness and concentration data:&lt;br&gt;&lt;br&gt;[3] &amp;#8706;Ch/&amp;#8706;t = -u.&amp;#8711;Ch - Ch&amp;#8711;.u + f_Ch&lt;br&gt;&lt;br&gt;where h is the thickness of the ice and the resulting product of the two datasets, Ch, is the effective thickness. If Ch were to be multiplied by the grid cell area this would give the volume, V. It is not necessary to take this step because the area remains constant and does not influence the relative values of the terms. However, when deriving an Arctic-wide climatology spatial integration across the grid cell areas is required. Ridging is taken into account by effective thickness change, therefore, it is not included in the calculations.&lt;br&gt;&lt;br&gt;The method is replicated using model simulations from the Centre for Climate Observation and Modelling (CPOM)-modified Los Alamos sea-ice model (CICE), providing a test of the model&amp;#8217;s ability to calculate the volume budgets but also identifying unrealistic growth regimes in the CryoSat-2 observational datasets. Sensitivity to several observational datasets is performed to provide an estimated uncertainty of the budget calculations.&lt;br&gt;&lt;br&gt;The observational results show ice gain in the central Arctic is dominated by ice freezing with contributions from convergence. Divergence at the coastlines of the Arctic form an ice sink where freezing generates new ice. Advection is shown to drive ice equatorward and induce melting at the ice edge where ice becomes thermodynamically unstable. The dynamic components are found to grow in influence throughout the growth season.&lt;br&gt;&lt;br&gt;The 2016/17 winter growth season budget shows reduced thermodynamic intensification and stronger dynamic tendencies which may be in response to thin initial ice and an exceptionally warm winter. Compared to the observed volume budget, the CICE model displays similar patterns of thermodynamic freezing, however, dynamic components in the central Arctic are significantly reduced whilst they are over-amplified at the ice edge.&lt;/p&gt;