Large-Eddy Simulations of the Sensitivity of Polar Clouds to Climate Change and Sea Ice

Abstract:

Because of polar and in particular Arctic amplification of global warming, high latitudes are sensitive to climate change. How sensitive they are depends, among factors, on how sea ice, clouds, and boundary layer processes respond to climate change. For example, the uncertainties in the Arctic cloud fraction simulated by current GCMs contribute to the inter-model spread in sea ice states through their impact on the surface energy budget (Eisenman et al. 2007), and they potentially exert feedbacks on sea ice cover. It is questionable whether the widely used semi-empirical cloud parameterizations, developed primarily for low latitudes, can be applied to polar regions to capture their climate change response.

Here we use a newly-developed large-eddy simulations model (PyCLES) to study Arctic clouds and how they respond to a wide range of climate changes, including seasonal sea ice loss. PyCLES resolves motions that are relevant to cloud processes, but its domain size is limited. Therefore, we apply large-scale dynamics from an idealized GCM as forcings to PyCLES, and vary the climate by changing the longwave optical thickness. We study the statistically steady states that eventually ensue to elucide the processes governing Arctic clouds in different climates. We also include bulk mixed-phased microphysics and a simple (thermodynamic) sea ice model, which modifies the surface energy balance.

Our primary results show that without a low-level temperature inversion, low cloud fraction decreases as the climate warms. As sea ice melts, low cloud fraction also decreases as a result of increased surface temperature, assuming that the large-scale advection of water vapor remains unchanged.