Evaluating Snow Depth on Arctic Sea Ice in CCSM
Sea ice cover in the Arctic Ocean is a continued focus of attention. This study investigates the impact of the snow overlying the sea ice in the Arctic Ocean. The impact of snow depth biases in the Community Climate System Model (CCSM) is shown to impact not only the sea ice, but also the overall Arctic climate. Following the identification of seasonal biases produced in CCSM simulations, the thermodynamic transfer through the snow–ice column is perturbed to determine model sensitivity to these biases. This study concludes that perturbations on the order of the observed biases result in modification of the annual mean conductive flux through the snow–ice column of 0.5 W m2 relative to an unmodified simulation. The results suggest that the ice has a complex response to snow characteristics, with ice of different thicknesses producing distinct reactions. Our results indicate the importance of an accurate simulation of snow on the Arctic sea ice. Consequently, future work investigating the impact of current precipitation biases and missing snow processes, such as blowing snow, densification, and seasonal changes, is warranted.
Ben Blazey worked with me as a summer student in 2010, beginning a project to evaluate the simulation of snow on sea ice. After working at LANL he returned to Boulder and worked with Marika Holland, looking at CCSM output. This became part of his Ph.D. thesis at CU Boulder, now published. The LANL work was accomplished using DOE Cloud-Cryo funds.