Rahul RanjanPhD student
Phone: +46 8 674 2432
My PhD is about process-level modelling of Aerosol-Cloud Interaction (ACI). ACI is credited as the greatest source of uncertainty in our future climate projections.
Process-level Modelling: Every cloud droplet in the atmosphere starts its journey from an aerosol particle. A set of parameters like updraft intensity, available water vapour and aerosol physicochemical properties (size distribution, hygroscopicity etc.) determine a cloud droplet’s birth and further growth. In process-level modelling, we vary these parameters to simulate the evolution of various cloud droplet properties.
It’s a well-established fact that the size distribution of aerosol particles is more important than composition in deciding the cloud droplet number concentration (CDNC). But under certain conditions, composition can also play a significant role, especially for smaller aerosol (< 40nm) particles, it can enhance CDNC by enabling smaller particles to activate. However, the role of composition is not very straightforward because of the complexity of aerosol composition and the role that dynamics play. Our understanding is further limited by the lack of concurrent long-term observation of aerosol properties and atmospheric dynamics.
To untangle the complexity, I am using long-term observations of aerosol properties and atmospheric dynamics to simulate the evolution of cloud droplet properties. It’s an attempt to better understand the relative importance of aerosol size and composition.