Aerosol effects on deep convection: the propagation of aerosol perturbations through  convective cloud microphysics

Abstract. The impact of aerosols on ice- and mixed-phase processes in deep convective clouds remains highly uncertain, and the wide range of interacting microphysical processes is still poorly understood. To understand these processes, we analyse diagnostic output of all individual microphysical process rates for two bulk microphysics schemes in the Weather and Research Forecasting model (WRF). We investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations through the microphysics all the way to the macrophysical development of the convective clouds. We perform simulations for two different cases of idealised supercells using two double-moment bulk microphysics schemes and a bin microphysics scheme. The simulations cover a comprehensive range of values for cloud droplet number concentration (CDNC) and cloud condensation nuclei (CCN) concentration as a proxy for aerosol effects on convective clouds. We have developed a new cloud tracking algorithm to analyse the morphology and time evolution of individually tracked convective cells in the simulations and their response to the aerosol perturbations. This analysis confirms an expected decrease in warm rain formation processes due to autoconversion and accretion for more polluted conditions. There is no evidence of a significant increase in the total amount of latent heat, as changes to the individual components of the integrated latent heating in the cloud compensate each other. The latent heating from freezing and riming processes is shifted to a higher altitude in the cloud, but there is no significant change to the integrated latent heat from freezing. Different choices in the treatment of deposition and sublimation processes between the microphysics schemes lead to strong differences including feedbacks onto condensation and evaporation. These changes in the microphysical processes explain some of the response in cloud mass and the altitude of the cloud centre of gravity. However, there remain some contrasts in the development of the bulk cloud parameters between the microphysics schemes and the two simulated cases.

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The propagation of aerosol perturbations in convective cloud microphysics

10.5194/acp-2018-609 ◽

2018 ◽

Author(s):

Max Heikenfeld ◽

Bethan White ◽

Laurent Labbouz ◽

Philip Stier

Keyword(s):

Cloud Condensation Nuclei ◽

Cloud Droplet ◽

Convective Cloud ◽

Cloud Microphysics ◽

Number Concentration ◽

Microphysics Scheme ◽

Microphysical Process ◽

Convective Clouds ◽

Wide Range ◽

The Impact

Abstract. The impact of aerosols on ice- and mixed-phase processes in deep convective clouds remains highly uncertain and the wide range of interacting microphysical processes are still poorly understood. To understand these processes, we analyse diagnostic output of all individual microphysical process rates for two cloud microphysics schemes in the Weather and Research Forecasting model (WRF). We investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations through the microphysics all the way to the macrophysical development of the convective clouds. We perform simulations for two different cases of idealised supercells using two double-moment bulk microphysics schemes and a bin microphysics scheme. We use simulations with a comprehensive range of values for cloud droplet number concentration (CDNC) and cloud condensation nuclei (CCN) concentration as a proxy for aerosol effects on convective clouds. We have developed a new cloud tracking algorithm to analyse the morphology and time evolution of individually tracked convective cells in the simulations and their response to the aerosol perturbations. This analysis confirms an expected decrease in warm rain formation processes due to autoconversion and accretion for polluted conditions. The height at which the freezing occurs increases with increasing CDNC. However, there is no evidence of a significant increase in the total amount of latent heat release from freezing and riming. The cloud mass and the altitude of the cloud centre of gravity show contrasting responses to changes in proxies for aerosol number concentration between the different microphysics schemes.

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Numerical Simulation of the Effect of Cloud Condensation Nuclei Concentration on the Microphysical Processes in Typhoon Usagi

Advances in Meteorology ◽

10.1155/2019/8293062 ◽

2019 ◽

Vol 2019 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Xiying Ye ◽

Qimin Cao ◽

Baolin Jiang ◽

Wenshi Lin

Keyword(s):

Latent Heat ◽

Cloud Condensation Nuclei ◽

Cloud Water ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Condensation Nuclei ◽

Microphysics Scheme ◽

Sensitivity Tests ◽

Microphysical Processes ◽

Heat Released

The Weather Research and Forecasting model version 3.2.1 with the Lin microphysics scheme was used herein to simulate super typhoon Usagi, which occurred in 2013. To investigate the effect of the concentration of cloud condensation nuclei (CCN) on the development of typhoon Usagi, a control simulation was performed with a CCN concentration of 100 cm−3, together with two sensitivity tests: C10 and C1000, having CCN concentrations of 10 cm−3 and 1000 cm−3, respectively. The path, intensity, precipitation, microphysical processes, and the release of latent heat resulting from the typhoon in all three simulations were analyzed to show that an increase in CCN concentration leads to decreases in intensity and precipitation, an increase of the cloudless area in the eye of the typhoon, a more disordered cloud system, and less latent heat released through microphysical processes, especially the automatic conversion of cloud water into rainwater. Overall, an increase in CCN concentration reduces the total latent heat released during the typhoon suggesting that typhoon modification by aerosol injection may be optimized using numerical simulations to ensure the strongest release of latent heat within the typhoon.

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The response of precipitation to aerosol through riming and melting in deep convective clouds

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-29007-2010 ◽

2010 ◽

Vol 10 (11) ◽

pp. 29007-29050

Author(s):

Z. Cui ◽

S. Davies ◽

K. S. Carslaw ◽

A. M. Blyth

Keyword(s):

Cloud Model ◽

Cloud Microphysics ◽

Mixed Phase ◽

Cloud Base ◽

Spatial And Temporal Variability ◽

Convective Clouds ◽

Ice Particles ◽

Wide Range ◽

Deep Convective Clouds ◽

The Impact

Abstract. We have used a 2-D axisymmetric, non-hydrostatic, bin-resolved cloud model to examine the impact of aerosol changes on the development of mixed-phase convective clouds. We have simulated convective clouds from four different sites (three continental and one tropical marine) with a wide range of realistic aerosol loadings and initial thermodynamic conditions (a total of 93 different clouds). It is found that the accumulated precipitation responds very differently to changing aerosol in the marine and continental environments. For the continental clouds, the scaled total precipitation reaches a maximum for aerosol that produce drop numbers at cloud base between 180–430 cm−3 when other conditions are the same. In contrast, all the tropical marine clouds show an increase in accumulated precipitation and deeper convection with increasing aerosol loading. For continental clouds, drops are rapidly depleted by ice particles shortly after the onset of precipitation. The precipitation is dominantly produced by melting ice particles. The riming rate increases with aerosol when the loading is very low, and decreases when the loading is high. Peak precipitation intensities tend to increase with aerosol up to drop concentrations (at cloud base) of ~500 cm−3 then decrease with further aerosol increases. This behaviour is caused by the initial transition from warm to mixed-phase rain followed by reduced efficiency of mixed-phase rain at very high drop concentrations. The response of tropical marine clouds to increasing aerosol is different to, and larger than, that of continental clouds. In the more humid tropical marine environment with low cloud bases we find that accumulated precipitation increases with increasing aerosol. The increase is driven by the transition from warm to mixed-phase rain. Our study suggests that the response of deep convective clouds to aerosol will be an important contribution to the spatial and temporal variability in cloud microphysics and precipitation.

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Reply to “Comments on ‘Do Ultrafine Cloud Condensation Nuclei Invigorate Deep Convection?’”

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-20-0315.1 ◽

2021 ◽

Vol 78 (1) ◽

pp. 341-350

Author(s):

Wojciech W. Grabowski ◽

Hugh Morrison

Keyword(s):

Negative Impact ◽

Cloud Condensation Nuclei ◽

Deep Convection ◽

Diagnostic Technique ◽

Cloud Water ◽

Latent Heating ◽

Condensation Nuclei ◽

Modeling Framework ◽

Microphysics Scheme ◽

The Impact

AbstractThis is a rebuttal of Fan and Khain’s comments (hereafter FK21) on a 2020 paper by Grabowski and Morrison (hereafter GM20) that questions the impact of ultrafine cloud condensation nuclei (CCN) on deep convection. GM20 argues that “cold invigoration,” an increase of the updraft speed from lofting and freezing of additional cloud water in polluted environments, is unlikely because the latent heating from freezing of this cloud water approximately recovers the negative impact on the buoyancy from the weight of this water. FK21 suggest a variety of processes that could invalidate our claim. We maintain that our argument is valid and invite the authors to compare their microphysics scheme with ours in the same simplified modeling framework. However, pollution does affect the partitioning of latent heating within the column and likely leads to convection changes beyond a single diurnal cycle through larger-scale circulation changes. This argument explains impacts seen in our idealized mesoscale simulations and in convective–radiative equilibrium simulations by others. We agree with FK21 on the existence of a “warm invigoration” mechanism but question its interpretation. Consistent with the simulations in GM20, we argue that changes in the buoyancy can be explained by the response of the supersaturation to droplet microphysical changes induced by pollution. The buoyancy change is determined by supersaturation differences between pristine and polluted conditions, while condensation rate responds to these supersaturation changes. Finally, we agree with FK21 that the piggybacking modeling technique cannot prove or disprove invigoration; rather, it is a diagnostic technique that can be used to understand mechanisms driving simulation differences.

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Sensitivity study of the aerosol effects on a supercell storm throughout its lifetime

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-24087-2014 ◽

2014 ◽

Vol 14 (17) ◽

pp. 24087-24118 ◽

Cited By ~ 1

Author(s):

A. Takeishi ◽

T. Storelvmo

Keyword(s):

Droplet Size ◽

Cloud Condensation Nuclei ◽

Wrf Model ◽

Convective Cloud ◽

Sensitivity Study ◽

Cloud Microphysics ◽

Microphysics Scheme ◽

Convective Clouds ◽

Aerosol Loading ◽

Deep Convective Clouds

Abstract. An increase in atmospheric aerosol loading could alter the microphysics, dynamics, and radiative characteristics of deep convective clouds. Earlier modeling studies have shown that the effects of increased aerosols on the amount of precipitation from deep convective clouds are model-dependent. This study aims to understand the effects of increased aerosol loading on a deep convective cloud throughout its lifetime with the use of the Weather Research and Forecasting (WRF) model as a cloud-resolving model (CRM). It simulates an idealized supercell thunderstorm with 8 different aerosol loadings, for three different cloud microphysics schemes. Variation in aerosol concentration is mimicked by varying either cloud droplet number concentration or the number of activated cloud condensation nuclei. We show that the sensitivity to aerosol loading is dependent on the choice of microphysics scheme. For the schemes that are sensitive to aerosols loading, the production of graupel via riming of snow is the key factor determining the precipitation response. The formulation of snow riming depends on the microphysics scheme and is usually a function of two competing effects, the size effect and the number effect. In many simulations, a decrease in riming is seen with increased aerosol loading, due to the decreased droplet size that lowers the riming efficiency drastically. This decrease in droplet size also results in a delay in the onset of precipitation, as well as so-called warm rain suppression. Although these characteristics of convective invigoration (Rosenfeld et al., 2008) are seen in the first few hours of the simulations, variation in the accumulated precipitation mainly stems from graupel production rather than convective invigoration. These results emphasize the importance of accurate representations of graupel formation in microphysics schemes.

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Assessing Desert Dust Indirect Effects on Cloud Microphysics through a Cloud Nucleation Scheme: A Case Study over the Western Mediterranean

Remote Sensing ◽

10.3390/rs12213473 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3473

Author(s):

Konstantinos Tsarpalis ◽

Petros Katsafados ◽

Anastasios Papadopoulos ◽

Nikolaos Mihalopoulos

Keyword(s):

Cloud Condensation Nuclei ◽

Dust Emission ◽

Cloud Microphysics ◽

Western Mediterranean ◽

Dust Particles ◽

Microphysics Scheme ◽

Double Moment ◽

Aerosol Activation ◽

The Impact

In this study, the performance and characteristics of the advanced cloud nucleation scheme of Fountoukis and Nenes, embedded in the fully coupled Weather Research and Forecasting/Chemistry (WRF/Chem) model, are investigated. Furthermore, the impact of dust particles on the distribution of the cloud condensation nuclei (CCN) and the way they modify the pattern of the precipitation are also examined. For the simulation of dust particle concentration, the Georgia Tech Goddard Global Ozone Chemistry Aerosol Radiation and Transport of Air Force Weather Agency (GOCART-AFWA) is used as it includes components for the representation of dust emission and transport. The aerosol activation parameterization scheme of Fountoukis and Nenes has been implemented in the six-class WRF double-moment (WDM6) microphysics scheme, which treats the CCN distribution as a prognostic variable, but does not take into account the concentration of dust aerosols. Additionally, the presence of dust particles that may facilitate the activation of CCN into cloud or rain droplets has also been incorporated in the cumulus scheme of Grell and Freitas. The embedded scheme is assessed through a case study of significant dust advection over the Western Mediterranean, characterized by severe rainfall. Inclusion of CCN based on prognostic dust particles leads to the suppression of precipitation over hazy areas. On the contrary, precipitation is enhanced over areas away from the dust event. The new prognostic CCN distribution improves in general the forecasting skill of the model as bias scores, the root mean square error (RMSE), false alarm ratio (FAR) and frequencies of missed forecasts (FOM) are limited when modelled data are compared against satellite, LIDAR and aircraft observations.

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The response of precipitation to aerosol through riming and melting in deep convective clouds

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-3495-2011 ◽

2011 ◽

Vol 11 (7) ◽

pp. 3495-3510 ◽

Cited By ~ 21

Author(s):

Z. Cui ◽

S. Davies ◽

K. S. Carslaw ◽

A. M. Blyth

Keyword(s):

Cloud Model ◽

Cloud Microphysics ◽

Mixed Phase ◽

Cloud Base ◽

Spatial And Temporal Variability ◽

Convective Clouds ◽

Ice Particles ◽

Wide Range ◽

Deep Convective Clouds ◽

The Impact

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Theoretical basis for convective invigoration due to increased aerosol concentration

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-2773-2011 ◽

2011 ◽

Vol 11 (1) ◽

pp. 2773-2842 ◽

Cited By ~ 1

Author(s):

Z. J. Lebo ◽

J. H. Seinfeld

Keyword(s):

Cloud Microphysics ◽

Number Concentration ◽

Latent Heating ◽

Microphysics Scheme ◽

Convective Clouds ◽

Aerosol Loading ◽

Significant Difference ◽

Deep Convective Clouds ◽

Bin Microphysics ◽

Cumulative Precipitation

Abstract. The potential effects of increased aerosol loading on the development of deep convective clouds and resulting precipitation amounts are studied by employing the Weather Research and Forecasting (WRF) model as a detailed high-resolution cloud resolving model (CRM) with both detailed bulk and bin microphysics schemes. The bulk microphysics scheme incorporates a physically based parameterization of cloud droplet activation as well as homogeneous and heterogeneous freezing in order to explicitly resolve the possible aerosol-induced effects on the cloud microphysics. These parameterizations allow one to segregate the effects of an increase in the aerosol number concentration into enhanced cloud condensation nuclei (CCN) and/or ice nuclei (IN) concentrations using bulk microphysics. The bin microphysics scheme, with its explicit calculations of cloud particle collisions, is shown to better predict cumulative precipitation. Increases in the CCN number concentration may not have a monotonic influence on the cumulative precipitation resulting from deep convective clouds. We demonstrate that the aerosol-induced effect is controlled by the balance between latent heating and the increase in condensed water aloft, each having opposing effects on buoyancy. It is also shown that under polluted conditions and in relatively dry environments, increases in the CCN number concentration reduce the cumulative precipitation due to the competition between the sedimentation and evaporation/sublimation timescales. The effect of an increase in the IN number concentration on the dynamics of deep convective clouds is small, but may act to suppress precipitation. A comparison of the predictions using the bin and bulk microphysics schemes demonstrate a significant difference between the predicted precipitation and the influence of aerosol perturbations on updraft velocity within the convective core. The bulk microphysics scheme is shown to be unable to capture the changes in latent heating that occur as a result of changes in the CCN number concentration, while the bin microphysics scheme demonstrates significant increases in the latent heating aloft with increasing CCN number concentration. This suggests that a detailed two-bulk microphysics scheme, which is more computationally efficient than bin microphysics schemes, may not be sufficient, even when coupled to a detailed activation scheme, to predict small changes that result from perturbations in aerosol loading.

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The Impact of Aerosol Vertical Distribution on a Deep Convective Cloud

Atmosphere ◽

10.3390/atmos12060675 ◽

2021 ◽

Vol 12 (6) ◽

pp. 675

Author(s):

Minzhong Zhang ◽

Xin Deng ◽

Ruihao Zhu ◽

Yangze Ren ◽

Huiwen Xue

Keyword(s):

Vertical Distribution ◽

Cloud Condensation Nuclei ◽

Wrf Model ◽

Convective Cloud ◽

Cloud Microphysics ◽

Aerosol Layer ◽

High Concentration ◽

Microphysical Processes ◽

The Impact ◽

Deep Convective Cloud

This study investigates the effects of aerosol vertical distribution on a deep convective cloud system. We intend to elucidate the mechanisms for aerosols entering the cloud from different heights, and how they affect cloud microphysics and precipitation. A thermal bubble is released at 1.5 km initially to run an idealized case using the Weather Research and Forecast (WRF) model. The aerosol layer with high concentration was initially put at different altitudes in the model to study the mechanisms and the number of aerosols entering the cloud. It was found that there are three mechanisms for aerosols from different heights to enter the cloud, depending on their relative height with the thermal bubble. Aerosols from lower altitudes (below 1 km) enter the cloud through pumping, while aerosols from higher altitudes (2–3 km, 3–5 km) enter the cloud through entrainment. Both mechanisms lead to low cloud condensation nuclei (CCN) concentration in the cloud. Only aerosols from intermediate altitudes (1–2 km), which is the same as the initial height of the thermal bubble, enter the cloud mainly by ascending with the bubble and lead to high CCN concentration in the cloud. The differences in activated CCN concentration affect the microphysical processes and precipitation remarkably. For the simulations with an initial aerosol layer at 1–2 km and 0–5 km, aerosols can enter the cloud more efficiently than the other four simulations. More activated CCNs in these two simulations lead to more graupels with smaller sizes at higher altitudes, which delays the precipitation but makes the precipitation last longer. However, the accumulated precipitation is similar in all six simulations, no matter what aerosol vertical distribution is like. The results in this study indicate that the altitude of aerosol layers determines the mechanisms for aerosols entering clouds, CCN concentration in the cloud, and to what extent the cloud microphysical processes and precipitation are affected.

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Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Entraining Parcel Simulations

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-18-0078.1 ◽

2018 ◽

Vol 75 (10) ◽

pp. 3365-3379 ◽

Cited By ~ 13

Author(s):

Gustavo C. Abade ◽

Wojciech W. Grabowski ◽

Hanna Pawlowska

Keyword(s):

Droplet Size ◽

Turbulent Mixing ◽

Cloud Condensation Nuclei ◽

Cloud Droplet ◽

Cloud Microphysics ◽

Droplet Growth ◽

Size Spectrum ◽

Entrainment Rate ◽

The Mean ◽

The Impact

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.

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