Clouds strongly modulate the Earth’s radiative budget, are key elements in the hydrological cycle, and are major drivers of the uncertainty of the prediction of future climate. Clouds can consist of liquid water droplets, ice particles, or both at the same time. At temperatures below 0°C, liquid droplets remain in a metastable thermodynamic state until freezing is initiated heterogeneously, either by an ice particle with which it comes into contact or by an ice nucleating aerosol particle, or homogeneously at about -37°C. Whether and how many ice particles are present in an otherwise liquid cloud (i.e. the phase distribution) influences the dynamical development through latent heat release, the interaction with radiation, and the formation of precipitation. Despite its importance, the cloud phase distribution is poorly represented in many weather and climate models. In the ERC Starting Grant C2Phase (“Closure of the Cloud Phase”), we set out to improve the representation of the phase distribution in models by making use of recent progress in understanding of microphysical ice formation processes and in observational capabilities with space-based passive sensors.
More specifically, our objective is to test the following hypothesis: The relevant primary and secondary ice formation processes can be included in state-of-the art cloud models such that these agree in a statistical sense with space-based observations of the cloud thermodynamic phase for a wide range of conditions. The closure will be better (higher correlation between predicted and observed phase), the more physical details are included.