Periodic Reporting for period 2 - MC2 (Mixed-phase clouds and climate (MC2) – from process-level understanding to large-scale impacts)
Reporting period: 2019-09-01 to 2021-02-28
In the MC2 project we seek to address the above issues, through a multi-angle and multi-tool approach:
(i) By conducting extensive field measurements of cloud phase at mid- and high latitudes, we seek to identify the small-scale structure of mixed-phase clouds.
(ii) Large Eddy Simulations are employed to identify the underlying physics responsible for the observed structures, and the field measurements will provide case studies for regional cloud-resolving modelling in order to test and revise state-of-the-art cloud microphysics parameterizations.
(iv) GCMs, with revised microphysics parameterizations, are confronted with cloud phase constraints available from space.
(v) The validated GCMs will be used to re-evaluate the climate impact of mixed-phase clouds in terms of their contribution to climate forcings and feedbacks.
The overall objective can be summarised as follows: Through a synergistic combination of tools for the study of mixed-phase clouds at a range of scales, the MC2 project will move the field of climate science forward, from improved process-level understanding at small scales, to better climate change predictions on the global scale.
MC2 sub-objectives include:
1) To determine the small-scale structure of mixed-phase clouds, and the extent to which it matters. Specifically, determine to what extent cloud phase is spatially homogeneous, as opposed to non-uniform and ‘patchy’, and whether environmental factors like turbulent mixing play a role in cloud homogeneity.
2) To re-evaluate the aerosol effect on mixed-phase clouds. By first assessing the ability of GCMs with the most sophisticated cloud microphysics representations available to reproduce observed mixed-phase clouds, we will re-evaluate the aerosol effect on mixed-phase clouds.
3) To determine the large-scale variability of mixed-phase clouds, and specifically whether spatial and temporal variations in cloud phase for a given isotherm can be explained predominantly by variations in INP.
4) To provide new and improved estimates of the strength of the cloud-phase feedback and a re-evaluation of its importance for mid- and high-latitude climate change.