Joshua Carter

The relationship of clouds and climate has recently been highlighted as an area of uncertainty. Many organisations including the IPCC have stated that the role of clouds is a key source of low confidence in climate projections. The field of cloud microphysics has consequently received increased attention. Microphysics discerns the interior processes of clouds, and how they affect cloud evolution. Capturing these processes in computational models has been challenging due to the many complicated overlaps of processes, their fine interconnectivity and effects on each other, as well as the number of hydrometeors, which themselves are extremely varied. Riming is a process that exhibits several of these problems. Riming collection efficiency is dependent on crystal habit, fall velocities and droplet size distributions. Riming has often been inadequately captured in meteorological models, causing unnatural mass jumps, and lacking an interconnectivity with the aforementioned qualities. This is significant, as the riming process determines cloud longevity, precipitation intensity and albedo. Changes to riming rates lead to enhanced precipitation, including the potential for high precipitation intensity. Enhanced time aloft can supply ice crystals with sufficient ingredients to produce such precipitation, and increase horizontal advection. Increased accuracy during the riming process will increase confidence in climate projections, as well as allowing for more advanced and accurate heavy precipitation foresight. Capturing the subtle effects upon riming rates will require a careful consideration of habit populations, habit characteristics and variations. To overcome the current problems associated with modelling the riming process, a Lagrangian framework will be used to more accurately demonstrate the fine scale effects of habit, and to introduce a multidimensional riming representation.