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Exploring the effects of microphysical complexity in numerical simulations of liquid and mixed-phase cloudsDearden, Christopher January 2011 (has links)
This thesis forms a NERC funded CASE studentship with the Met Office, whose aim is to investigate the treatment of cloud microphysical processes in numerical models, with a particular focus on exploring the impacts and possible benefits of microphysical complexity for the purpose of simulating clouds and precipitation. The issue of complexity is an important one in numerical modelling in order to maintain computational efficiency, particularly in the case of operational models. The latest numerical modelling tools are utilised to perform simulations of cloud types including idealised trade wind cumulus, orographic wave cloud and wintertime shallow convective cloud. Where appropriate, the modelling results are also validated against observations from recent field campaigns. The Factorial Method is employed as the main analysis tool to quantify the effect of microphysical variables in terms of their impact on a chosen metric. Ultimately it is expected that the techniques and results from this thesis will be used to help inform the future development of cloud microphysics schemes for use in both cloud resolving and operational models. This is timely given the current plans to upgrade the microphysics options available for use within the Met Office Unified Model. For an idealised warm cloud, it is shown that different bin microphysics schemes can produce different results, and therefore additional microphysical complexity does not necessarily ensure a more consistent simulation. An intercomparison of bin microphysics schemes 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 parameterization of ice growth by diffusion within the sampled temperature regime. The simulations were also found to be largely insensitive to values of the deposition coefficient within the range of 0.1 to 1.0. Results from a mesoscale modelling study of shallow wintertime convection demonstrate the importance of the representation of dynamical factors that control cloud macrostructure, and how this has the potential to overshadow any concerns of microphysical complexity. Collectively, the results of this thesis place emphasis on the need to encourage more synergy between the dynamics and microphysics research communities in order to improve the future performance of numerical models, and to help optimise the balance between model complexity and computational efficiency.
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