Spatial Variability in the Atmospheric Surface Layer and in the Surface Heat Exchange over Arctic Sea Ice

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The experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA) provided an invaluable supply of data from the main ice camp and from several remote sites. Recent analyses of some of these data present a paradox, however: in winter, when the sea ice is uniformly white and snow-covered, turbulent surface fluxes seem to be more spatially variable than in summer, when the surface is scarred with melt ponds and leads and, therefore, appears quite heterogeneous. Because these turbulent fluxes are key components of the surface heat and momentum budgets, this project proposes further analyses of the SHEBA data to study the nature and causes of spatial variability in surface fluxes and related surface-level meteorological variables over sea ice. The objectives of this project include the following analyses and products: investigate the spatial variability of mean atmospheric surface-level variables; investigate the spatial variability of sea ice surface properties, such as surface temperature, the surface fluxes of momentum and sensible heat, and the four radiative flux components; investigate the spatial variability of the modeled surface temperature and the surface heat budget by running simulations with a newly developed polar version of the one-dimensional mass and energy budget model SNTHERM on each of the SHEBA sites; test existing or develop new, simple parameterizations for the four radiative flux components with the goal of evaluating whether expendable sea ice buoys can be upgraded to provide all the components of the surface heat budget. The SHEBA data come from the main camp and from, generally, four remote sites up to 30 km from the main camp. The horizontal scales represented in the data set thus fall in the microscale to mesoscale range - 200 m to 30 km. Moreover, the data set includes at least 1000 hours of station pairs in each 1 km interval for all separations between 0 and 15 km. As a result, the analyses will have implications for how to aggregate properties over the diverse surfaces that may constitute grid cells in the Arctic Ocean in regional and global climate models.