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Hugh Morrison - Cloud Microphysical ParameterizationsHugh Morrison

The representation of clouds is a major uncertainty in model simulations of weather and climate, including estimates of global climate change. Processes that impact cloud and precipitation particles, such as evaporation and particle collisions, occur on sub-centimeter scales that cannot be resolved by current models. Therefore, these microphysical processes must be parameterized. My research focuses on the development and testing of cloud microphysical parameterizations. In large-scale models such as general circulation models (GCMs), cloud-scale and mesoscale dynamical processes are also unresolved. These models therefore require assumptions about the macrophysical distribution of clouds and sub-grid scale cloud-dynamical interactions. Convectively-driven clouds are treated by the cumulus convection scheme with generally a simple representation of the microphysics. Stratiform clouds are treated by the large-scale condensate scheme with typically a more detailed treatment of the microphysics. My research involves the development of a new microphysics scheme for stratiform clouds in the NCAR Community Atmosphere Model (CAM) GCM. This scheme predicts both the mixing ratio and number concentration of the cloud water. Predicting both mixing ratio and number increases the degrees of freedom and allows for the treatment of aerosol indirect effects, i.e., the impact of aerosol on the cloud radiative properties. A major challenge is parameterizing the sub-grid scale distribution of cloud water and cloud-dynamical interactions which are critical in treating the microphysics. One approach is to use a higher-resolution cloud model for the sub-grid scheme coupled to the large-scale model – the so called multi-scale modeling framework. Of course, this approach comes at a computational cost.

Higher-resolution cloud and large-eddy models resolve cloud-scale circulations and can therefore address some of the issues described above. However, important cloud-dynamic processes are still unresolved, in particular the entrainment and mixing between cloudy and cloud-free air. In collaboration with Wojciech Grabowski (MMM), I am also developing a warm (ice-free) microphysics scheme for application in high-resolution models that again predicts both the mixing ratios and number concentrations of cloud water and precipitation particles. The focus of this work is to develop a flexible scheme that can treat microphysical transformations during entrainment and mixing and droplet activation (i.e., the activation of cloud condensation nuclei into growing cloud droplets) both at the cloud base and in the cloud interior. An example of the scheme applied in an idealized two-dimensional (2D) framework mimicking a warm convective bubble is shown in Figure 1. These results show the development of the cloud in terms of mixing ratio and droplet concentration in its early stages (t = 4 min), and the later (t = 8 min) development of entraining regions that mix clear air into the cloud interior. The microphysical transformations during this entrainment and mixing have a large impact on the mean cloud properties. We are also working to extend the warm scheme to the ice phase using a new approach that improves the representation of transformations that occur as ice particles rime by collecting water drops.


Figure 1. Droplet mixing ratio (contour interval 0.5 g/kg) and number concentration (contour interval 10 cm -3 ) in the X-Z plane for an idealized 2D warm bubble simulation using the new microphysics scheme at time t = 4 min (bottom) and t = 8 min (top).


ASP Spotlight April 2007
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