Exploring the effects of microphysical complexity in numerical simulations of liquid and mixed-phase clouds

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Abstract

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.

Layman's Abstract

The problem of the Earth’s average surface temperature increasing due to the releaseof greenhouse gases from fossil fuel burning has been well established over the past fewdecades. However it is perhaps less well known generally that human activities alsolead to an increase in microscopic liquid and solid particles within the atmosphere, thatindividually are too small to be seen with the naked eye. Such particles, known within theatmospheric science community as atmospheric aerosols, are very important for severalreasons including their effects on air quality (and thus human health), visibility, and alsotheir ability to absorb and reflect radiation of different wavelengths. This latter effect canoccur through the direct presence of aerosols in the atmosphere, causing a warming orcooling effect, but also indirectly through the ability of aerosols to act as tiny surfacesupon which water vapour can condense to form clouds. Clouds are important in weatherand climate not just as a source of precipitation but also, for example, their role in reducingthe amount of sunlight that reaches the Earth’s surface, and for trapping heat releasedfrom the ground. Changes in the number of aerosols released into the atmosphere dueto human activities (e.g. from fossil fuel burning and the burning of vegetation duringland clearance) can impact on cloud properties and precipitation in ways that are not yetfully understood. Current estimates from computer simulations of the Earth’s climatesuggest that to date, the increase in aerosol numbers due to human activity is likely tohave enhanced the ability of clouds to reflect incoming sunlight back out to space. It isbelieved that this cooling effect has helped to mask the effects of global warming to somedegree, although the exact extent remains very poorly quantified. This PhD thesis seeks to increase our understanding of the influence of atmosphericaerosols on clouds by utilising the very latest computer models. We show that even themost detailed simulations representing the effects of aerosols on clouds do not necessarilyproduce consistent results when compared against each other. For clouds containing bothliquid droplets and ice crystals together, the results of our computer simulations showthat the ability to represent the number of aerosols above a certain size is important fordetermining how many ice crystals are formed and the overall structure of the cloud asa whole. Also the ability of the computer model to account for changes in the shapeand size of ice crystals as they grow was found to be important too. These results showthat in some cases, it is beneficial to be able to represent the effects of aerosols on clouds,although future work is needed to understand why even the most sophisticated simulationscan disagree with each other.

Keyword(s)

clouds, microphysics, aerosol, modelling

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