Separating Physical Impacts from Natural Variability Using Piggybacking (Master–Slave) Technique

In a chaotic system, like moist convection, it is difficult to separate the impact of a physical process from effects of natural variability. This is because modifying even a small element of the system physics typically leads to a different system evolution and it is difficult to tell whether the difference comes from the physical impact or it merely represents a different flow realization. This paper discusses a relatively simple and computationally efficient modelling methodology that allows separation of the two. The methodology is referred to as the piggybacking or the master-slave approach. The idea is to use two sets of thermodynamic variables (the temperature, water vapor, and all aerosol, cloud, and precipitation variables) in a single cloud simulation. The two sets can differ in a specific element of the physics, such as aerosol properties, microphysics parameterization, large-scale forcing, environmental profiles, etc. One thermodynamic set is coupled to the dynamics and drives the simulated flow, and the other set piggybacks the flow, that is, thermodynamic variables are carried by the flow but they do not affect it. By switching the sets (i.e. the set driving the simulation becomes the piggybacking one, and vice versa), the impact on the cloud dynamics can be evaluated. This paper provides details of the method and reviews results of its application to such problems as the postulated deep convection invigoration in polluted environments, the impact of changes in environmental profiles (e.g., due to climate change) on convective dynamics, and the role of cloud-layer heterogeneities on shallow convective cloud field evolution. Prospects for applying piggybacking technique to other areas of atmospheric simulation (e.g., weather prediction or geoengineering) are also mentioned.