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

Abstract

Abstract. Convection-permitting simulations are used to understand the effects of cloud–aerosol interactions in a case of heavy rainfall over southern China. The simulations are evaluated using radar observations from the Southern China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of precipitation, clouds and radiation. We focus on the effects of complexity in cloud–aerosol interactions, especially the depletion and transport of aerosol material by clouds. In particular, simulations with aerosol concentrations held constant are compared with a fully cloud–aerosol-interacting system to investigate the effects of two-way coupling between aerosols and clouds on a line of organised deep convection. It is shown that the cloud processing of aerosols can change the vertical structure of the storm by using up aerosols within the core of line, thereby maintaining a relatively clean environment which propagates with the heaviest rainfall. This induces changes in the statistics of surface rainfall, with a cleaner environment being associated with less-intense but more-frequent rainfall. These effects are shown to be related to a shortening of the timescale for converting cloud droplets to rain as the aerosol number concentration is decreased. The simulations are compared to satellite-derived estimates of surface rainfall, a condensed-water path and the outgoing flux of short-wave radiation. Simulations for fewer aerosol particles outperform the more polluted simulations for surface rainfall but give poorer representations of top-of-atmosphere (TOA) radiation.

Investigating the Effect of Aerosol Uncertainty on Convective Precipitation Forecasting in South China's Coastal Area

“…In our convective system case, the effect of varying IF aerosol concentrations on precipitation intensity is amplified at reduced WF aerosol concentrations. More and stronger precipitation is generated in a clean environment, which agrees with the previous observation and modeling studies (Furtado et al., 2020; Lebo et al., 2012). However, stronger convection is also generated in the supplementary simulation with extremely more aerosols (WmorImor).…”

“…Chen et al, 2019;Furtado et al, 2018;Guo et al, 2022;Miyamoto, 2021). Furtado et al (2020) investigated the surface rainfall change with spanned range of extremely clean to extremely polluted conditions to demonstrate the aerosol effect. Researchers had to design their experiments in such an idealized way because of the lack of long-term concurrent observation of aerosol properties that can address the covariability of aerosols, dynamics, and thermodynamics (Fan et al, 2016).…”

The Synoptic Impacts on the Convection Initiation of a Warm‐Sector Heavy Rainfall Event Over Coastal South China Prior to the Monsoon Onset: A Numerical Modeling Study

“…In recent years, numerous studies have documented the climatological characteristics and physical mechanisms of the pre‐summer rainfall over SC (e.g., G. Chen et al., 2009a, 2009b, 2018; X. Chen et al., 2016, 2017; Jiang et al., 2017; Gu et al., 2018; Yuan et al., 2019; Zhang & Meng, 2019). Efforts have also been made to develop numerical weather prediction (NWP) technique including data assimilation (Bao et al., 2017; Zhang et al., 2016), model physic parameterization (Furtado et al., 2018, 2020; Qian et al., 2018), and perturbation‐generation methods for ensemble forecast (Zhang 2018, 2019). Despite all these research progresses (summarized by Luo et al., 2020), it remains challenging to make timely and accurate forecast for the pre‐summer warm‐sector heavy rainfall over coastal SC under relatively weaker large‐scale dynamic lifting.…”

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

“…The simulations analysed where performed with a convection-permitting (0.03 • horizontal-resolution) configuration of the Met Office Unified Model. A description of the model set-up can be found in Furtado et al (2018), together with a detailed description of the non-aerosol components of the microphysics scheme (see also Grosvenor et al (2017) (Furtado et al , 2018(Furtado et al , , 2020 The method for coupling clouds and aerosols is described in Miltenberger et al (2018): interstitial aerosol particles are removed by activation of cloud-droplets; following activation, a prognostic variable for dissolved aerosol mass is co-advected with the hydrometeors so that it is transported conservatively through clouds. During evaporation of hydrometeors, the soluble mass is re-deposited into the air with a number concentration equal to the number of evaporated particles.…”