The Arctic Boundary Layer Cloud Annual Cycle and the Influence of Surface–Atmosphere Interactions: Implications for Arctic Climate Change

Arctic clouds significantly affect energy flows in the Arctic with a large influence on surface radiative fluxes. Contemporary climate models struggle to reproduce the observed Arctic cloud properties producing biases in the surface radiative fluxes, especially with respect to the low cloud annual cycle. In this research, we quantify the relationships between cloud properties and cloud influencing factors (e.g, vertical velocity and lower tropospheric stability) using CMIP5 model output to understand the cause of model discrepancies in the low cloud amount annual cycle. Differences in the total cloud amount annual cycle are primarily caused by differences in low, not high, clouds; the largest differences occur between the surface and 950 hPa. We also find that model groups disagree most under specific meteorological conditions: strong lower tropospheric stability, weak to moderate mid-tropospheric subsidence, and cold lower tropospheric air temperatures. Grouping models by characteristics of their cloud microphysical schemes reveals that models treating cloud ice and liquid condensate as separate prognostic variables simulate a larger ice condensate fraction than those that treat total cloud condensate as a prognostic variable and use a temperature-dependent phase partitioning. Thus, the cloud microphysical parameterization is the key driver of inter-model differences in the Arctic cloud annual cycle, providing further evidence of the important role of cloud ice microphysical processes in the evolution and modeling of the Arctic climate system. Lastly, we extend the cloud influencing factor analysis to assess contributions to projected changes in Arctic cloud properties. This presentation will discuss the implications of these results for constraining Arctic low cloud feedback.