Non-Monotonic Dependencies of Cloud Microphysics and Precipitation on Aerosol Loading in Deep Convective Clouds: A Case Study Using the WRF Model with Bin Microphysics

Abstract

Aerosol-cloud-precipitation interactions in deep convective clouds are investigated through numerical simulations of a heavy precipitation event over South Korea on 15–16 July 2017. The Weather Research and Forecasting model with a bin microphysics scheme is used, and various aerosol number concentrations in the range N0 = 50–12,800 cm−3 are considered. Precipitation amount changes non-monotonically with increasing aerosol loading, with a maximum near a moderate aerosol loading (N0 = 800 cm−3). Up to this optimal value, an increase in aerosol number concentration results in a greater quantity of small droplets formed by nucleation, increasing the number of ice crystals. Ice crystals grow into snow particles through deposition and riming, leading to enhanced melting and precipitation. Beyond the optimal value, a greater aerosol loading enhances generation of ice crystals while the overall growth of ice hydrometeors through deposition stagnates. Subsequently, the riming rate decreases because of the smaller size of snow particles and supercooled drops, leading to a decrease in ice melting and a slight suppression of precipitation. As aerosol loading increases, cold pool and low-level convergence strengthen monotonically, but cloud development is more strongly affected by latent heating and convection within the system that is non-monotonically reinforced.

Non-Monotonic Aerosol Effect on Precipitation in Convective Clouds over Tropical Oceans

“…This value marks the turning point from invigoration to suppression in the trend. Such nonmonotonic dependence suggests competition between at least two dominant processes 34,35 . However, before investigating aerosol-related processes, we explored the possible influence of meteorology on both aerosols and clouds that can produce apparent correlations with no real causality 36 .…”

Hourly extreme precipitation changes under the influences of regional and urbanization effects in Beijing

“…Recent numerical modelling studies show that the relationship between precipitation amount and aerosol loading is not monotonic (Jeon et al ., 2018; Lkhamjav et al ., 2018). The amount of precipitation from deep convective clouds slightly decreases as aerosol loading increases in a certain range of concentration, while notably increases in a higher concentration range.…”

Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems

“…Changes in hydrometer concentration and size distribution were shown to affect clouds' microphysical process rates (such as condensation, evaporation, freezing and collision-coalescence), which in turn could affect the dynamics of the clouds (Khain et al, 2005;Koren et al, 2005;Heikenfeld et al, 2019;Chen et al, 2017;Seifert and Beheng, 2006a), the rain production (Levin and Cotton, 2009;Albrecht, 1989;Tao et al, 2012) and the clouds' radiative effect (Koren et al, 2010;Storelvmo et al, 2011;Twomey, 1977;Albrecht, 1989). The aerosol effect, and in particular its effects on the radiation budget and the atmospheric energy budget, is dependent on cloud regime Lee et al, 2009;Mülmenstädt and Feingold, 2018;van den Heever et al, 2011;Rosenfeld et al, 2013;Glassmeier and Lohmann, 2016;Gryspeerdt and Stier, 2012;Christensen et al, 2016), time (Dagan et al, 2017(Dagan et al, , 2018cGryspeerdt et al, 2015;Seifert et al, 2015;Lee et al, 2012), aerosol type and size distribution (Jiang et al, 2018;Lohmann and Hoose, 2009), and (even for a given cloud regime) meteorological conditions (Dagan et al, 2015a;Fan et al, 2009Fan et al, , 2007Kalina et al, 2014;Khain et al, 2008) and was shown to be non-monotonic (Dagan et al, 2015b;Jeon et al, 2018;Gryspeerdt et al, 2019;Liu et al,...…”

“…However, unlike in the deep-cloud case, the mean effect on precipitation, under typical modern-day conditions, is thought to be negative (Albrecht, 1989;Rosenfeld, 2000;Jiang et al, 2006;Xue and Feingold, 2006;Dagan and Chemke, 2016). The aerosol effect on shallow cloud cover and mean water mass (measured by liquid water path -LWP) might also depend on the meteorological conditions and aerosol range (Dagan et al, 2015b(Dagan et al, , 2017Dey et al, 2011;Savane et al, 2015) and is the outcome of competition between different opposing responses of rain suppression (that could lead to an increase in cloud lifetime and coverage; Albrecht, 1989), warm cloud invigoration (that could also lead to an increase in cloud coverage and LWP; Koren et al, 2014;Kaufman et al, 2005; al., 2011b), and an increase in entrainment and evaporation (that could lead to a decrease in cloud coverage; Small et al, 2009;Jiang et al, 2006;Costantino and Bréon, 2013;Seigel, 2014). Another addition to this complex response is the fact that the aerosol effect on warm convective clouds was shown to be time-dependent and affected by the clouds' feedbacks on the thermodynamic conditions (Seifert et al, 2015;Dagan et al, , 2017Dagan et al, , 2018bLee et al, 2012;Stevens and Feingold, 2009).…”