This thesis forms a NERC funded CASE studentship with the Met Office, whose aimis to investigate the treatment of cloud microphysical processes in numerical models, witha particular focus on exploring the impacts and possible benefits of microphysical complexityfor the purpose of simulating clouds and precipitation. The issue of complexity isan important one in numerical modelling in order to maintain computational efficiency,particularly in the case of operational models. The latest numerical modelling tools areutilised to perform simulations of cloud types including idealised trade wind cumulus,orographic wave cloud and wintertime shallow convective cloud. Where appropriate, themodelling results are also validated against observations from recent field campaigns. TheFactorial Method is employed as the main analysis tool to quantify the effect of microphysicalvariables in terms of their impact on a chosen metric. Ultimately it is expectedthat the techniques and results from this thesis will be used to help inform the futuredevelopment of cloud microphysics schemes for use in both cloud resolving and operationalmodels. This is timely given the current plans to upgrade the microphysics optionsavailable for use within the Met Office Unified Model. For an idealised warm cloud, it is shown that different bin microphysics schemescan produce different results, and therefore additional microphysical complexity does notnecessarily ensure a more consistent simulation. An intercomparison of bin microphysicsschemes in a 1-D column framework is recommended to isolate the origin of the discrepancies. In relation to the mixed-phase wave cloud, model simulations based on an adaptive treatment of ice density and habit struggled to reproduce the observed ice crystal growth rates, highlighting the need for further laboratory work to improve the parameterizationof ice growth by diffusion within the sampled temperature regime. The simulations werealso found to be largely insensitive to values of the deposition coefficient within the rangeof 0.1 to 1.0. Results from a mesoscale modelling study of shallow wintertime convectiondemonstrate the importance of the representation of dynamical factors that controlcloud macrostructure, and how this has the potential to overshadow any concerns of microphysical complexity. Collectively, the results of this thesis place emphasis on the needto encourage more synergy between the dynamics and microphysics research communitiesin order to improve the future performance of numerical models, and to help optimisethe balance between model complexity and computational efficiency.
|Date of Award||31 Dec 2011|
- The University of Manchester
|Supervisor||Paul Connolly (Supervisor) & Thomas Choularton (Supervisor)|
- clouds, microphysics, aerosol, modelling