The effects of cloud-aerosol-interaction complexity on simulations of presummer rainfall over southern China

Abstract

Convection-permitting simulations are used to understand the effects of cloud-aerosol interactions on a case of heavy rainfall over south China. The simulations are evaluated using radar observations from the South China Monsoon Rainfall Experiment and remotely sensed estimates of precipitation, clouds and radiation. We focus on the effects of complexity in cloud-aerosol interactions, especially processing and transport of dissolved material inside clouds. In particular, simulations with aerosol concentrations held constant are compared with a fully coupled cloud-aerosol-interacting system to isolate the 5 effects of processing on a line of organised-deep convection. It is shown that in-cloud processing of aerosols can change the vertical structure of squall lines thereby inducing changes in the statistics of surface rainfall. These effects are shown to be consistent with a modulation by aerosol of the timescale of the converting cloud-droplets to rain.Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 4.0 License. This licence does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribu-10 tion 4.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other. ©Crown copyright 2019 IntroductionPhysical models of clouds and aerosol microphysics are complex components of atmospheric simulators and, because they are fundamental to the Earth's energy and hydrological cycles, they are a large source of uncertainty in predictions across a wide 15 range of time-scales: from weather forecasts and seasonal predictions, out to climate projections.Complexity in microphysics schemes arises from the number of processes being modelled and how many prognostic variables are used. Simple single-moment schemes use hydrometeor mass as the prognostic variable for each of cloud droplets, rain and ice. More complex schemes differentiate between sub-species of hydrometeor (graupel, hail, cloud ice and snow) or employ more than one prognostic for each species. Greater complexity improves physical realism but raises the computa-20 tional expense and it is not obvious where the balance between cost and benefit lies. Moreover, the relative importance of the different mechanisms by which aerosols affect clouds and precipitation are themselves uncertain (Tao , 2012). Although the 1 https://doi.basic hypotheses that cloud-droplet number concentrations can alter the brightness, longevities and amounts of clouds are wellestablished (Twomey , 1977;Albrecht , 1989;Rosenfeld et al , 2008), how these processes combine to determine the responses of systems of clouds has been found to depend on both the system under consideration (Kaufman et al , 2005;Rosenfeld et al , 2008) and the model being used (Hill et al , 2015;Johnson , 2015). For deep-convective clouds in particular, uncertainty abounds because increased droplet numbers are associated with both increased and decreased rainfall in ...

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A strong statistical link between aerosol indirect effects and the self-similarity of rainfall distributions

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