Water-ice partition in the Arctic mixed-phase clouds Based on Long-term ARCF Observations

Recent analyses on global distribution of mixed-phase clouds and IPCC inter-model differences in simulated cloud radiative forcing under the doubling CO2 condition indicate that mixed-phase cloud representations in climate models contribute significantly to current climate predication uncertainties. However, due to inadequate observations and studies, processes controlling ice particles generation and growth and the water-ice mass partition mixed-phase clouds are not still fully understood. A novel multi-sensor retrieval algorithm is applied to long-term ARCF (Atmospheric Radiation Management (ARM) Climate Research Facility) observations at the NSA (North Slope of Alaska) site and provides an important data set to better understand stratiform mixed-phase cloud properties and processes. Statistical results show that widely used temperature dependence of water-ice mass partition in models based on in situ observations from frontal clouds cannot accurately represent the water-ice partition of arctic mixed-phase clouds. Moreover, there is a significant difference in the temperature dependence of water-ice partition between the spring season and the other seasons, which can be attributed to high aerosol loading during the spring season over the Arctic region. Aerosol loading is closely linked to cloud microphysics: liquid water effective radius decrease with increasing of aerosol extinction coefficient while maximum radar Doppler velocity in the mixed-phase layer increases with increasing aerosol extinction coefficient. Statistical results show the negative correlation between aerosol extinction coefficient and liquid water fraction (LWP/(LWP+IWP)). These new insights provide important guidance on developing new mixed-phase cloud parameterization for large-scale models.