On the limits of Köhler activation theory: how do collision and coalescence affect the activation of aerosols?

Hoffmann, Franziska

doi:10.5194/acp-17-8343-2017

Cited by 15 publications

(16 citation statements)

References 33 publications

(59 reference statements)

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“…The mechanism of CDSD broadening in this study requires the model to consider both solute and curvature effects all the time (i.e., before and after activation, deactivation and reactivation). Our results suggest the importance of solute and curvature effects to the deactivation and reactivation processes, which are consistent with previous studies (e.g., Andrejczuk et al, 2008;Hoffmann et al, 2015;Hoffmann, 2017;Chen et al, 2018). However the results are counter to some other studies where details of activation and deactivation are argued to be unimportant in the cloud simulation (e.g., Srivastava, 1991;Chuang et al, 1997;Grabowski et al, 2018).…”

Section: Conclusion and Atmospheric Implicationssupporting

confidence: 90%

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

et al. 2018

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Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

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Section: Conclusion and Atmospheric Implicationssupporting

confidence: 90%

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

et al. 2018

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“…PALM's Lagrangian cloud model (LCM) is based on its LPM, using Lagrangian particles as so-called superdroplets (e.g., Shima et al, 2009), each representing an ensemble of identical droplets that change their properties (e.g., water mass, aerosol mass, number of represented real droplets -the so-called weighting factor) by undergoing cloud microphysical processes. PALM's approach has been applied in various studies to further process-level understanding of warm-phase cloud microphysics, covering deliquescent aerosols, their entrainment and mixing with the cloud, as well as droplet activation, growth by diffusion, and collision and coalescence (Riechelmann et al, 2012;Hoffmann et al, 2015Hoffmann et al, , 2017Hoffmann, 2017;Noh et al, 2018).…”

Section: Lagrangian Cloud Model Improvementsmentioning

confidence: 99%

Overview of the PALM model system 6.0

Maronga

Banzhaf²,

Burmeister³

et al. 2020

Geosci. Model Dev.

Self Cite

227

141

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Abstract. In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

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“…The reaction rates of oxidation by ozone and hydrogen peroxide can be described as a Hoffmann and Calvert (1985):…”

Section: Oxidationmentioning

confidence: 99%

libcloudph++ 2.0: aqueous-phase chemistry extension of the particle-based cloud microphysics scheme

Jaruga

Pawłowska

2018

Geosci. Model Dev.

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Abstract. This paper introduces a new scheme available in the library of algorithms for representing cloud microphysics in numerical models named libcloudph++. The scheme extends the particle-based microphysics scheme with a Monte Carlo coalescence available in libcloudph++ to the aqueous-phase chemical processes occurring within cloud droplets. The representation of chemical processes focuses on the aqueous-phase oxidation of the dissolved SO2 by O3 and H2O2. The particle-based microphysics and chemistry scheme allows for tracking of the changes in the cloud condensation nuclei (CCN) distribution caused by both collisions between cloud droplets and aqueous-phase oxidation. The scheme is implemented in C++ and equipped with bindings to Python. The scheme can be used on either a CPU or a GPU, and is distributed under the GPLv3 license. Here, the particle-based microphysics and chemistry scheme is tested in a simple 0-dimensional adiabatic parcel model and then used in a 2-dimensional prescribed flow framework. The results are discussed with a focus on changes to the CCN sizes and comparison with other model simulations discussed in the literature.

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On the limits of Köhler activation theory: how do collision and coalescence affect the activation of aerosols?

Cited by 15 publications

References 33 publications

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

Overview of the PALM model system 6.0

libcloudph++ 2.0: aqueous-phase chemistry extension of the particle-based cloud microphysics scheme

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