Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model

Thomas, Lois; Grabowski, Wojciech W.; Kumar, Bipin

doi:https://doi.org/10.5194/acp-20-9087-2020

Articles | Volume 20, issue 14

https://doi.org/10.5194/acp-20-9087-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-20-9087-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 14

Research article

|

31 Jul 2020

Research article |

| 31 Jul 2020

Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model

Lois Thomas, Wojciech W. Grabowski, and Bipin Kumar

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Final revised paper (published on 31 Jul 2020)
Preprint (discussion started on 26 Feb 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Comments to the manuscript with ID number “acp-2020-159”', Anonymous Referee #1, 09 Apr 2020
- AC1: 'Responses to Reviewer 1 comments', Wojciech W. Grabowski, 17 Apr 2020
RC2: 'Comments on “Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model” by Thomas et al.', Anonymous Referee #2, 14 Apr 2020
- AC2: 'Responses to Reviewer 2 comments.', Wojciech W. Grabowski, 17 Apr 2020
  - RC3: 'Comments on “Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model” by Thomas et al.', Anonymous Referee #2, 17 Apr 2020
    - AC3: 'Response to the 2nd comment of Reviewer 2', Wojciech W. Grabowski, 18 Apr 2020
RC4: 'Reviewer 3 comments', Anonymous Referee #3, 23 Apr 2020
- AC4: 'responses ro Referee 3', Wojciech W. Grabowski, 27 Apr 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Wojciech W. Grabowski on behalf of the Authors (29 Apr 2020) Author's response Manuscript

ED: Reconsider after major revisions (05 May 2020) by Timothy Garrett

AR by Wojciech W. Grabowski on behalf of the Authors (06 May 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (19 May 2020) by Timothy Garrett

RR by Anonymous Referee #2 (31 May 2020)

RR by Anonymous Referee #1 (06 Jun 2020)

Suggestions for revision or reasons for rejection

Comments to the revision of manuscript with ID number “acp-2020-159”

I would recommend the publication of this manuscript after the authors carefully discuss the following comments again.

1. I disagree with the response to my comment about the “novel methodology”. Again, the method presented in this manuscript is DNS with large artificial kinetic viscosity, which is not a new method.

Since this is a DNS study, let us put the LES aside. Eq.4-9 in the manuscript show the standard
scaling argument of the scale separation of turbulence. DNS (finite difference numerical method or spectral method) of turbulence is limited by Re. To study how large scales of turbulence affect supersaturation fluctuations by means of DNS, the authors increased both the integral length scale and Kolmogorov length scale of turbulence simultaneously so that Re can be kept unchanged. This is very well described by Eq.4-9. What is the novelty regarding numerical methodology in DNS simulations with this configuration? In other words, how can I see the novelty from Eq.4-9?

The Reynolds number is defined as Re=u_rmsL/\nu. One can simply increase L and \nu at the
same time in a DNS simulation to check how large eddies affect supersaturation fluctuations.

I don’t understand the comment about the numerical dissipation for finite difference method
and the spectral method. Both methods deal with the physical dissipation, i.e., energy dissipation in the dissipation range of turbulence. How exactly increasing L and \nu simultaneously in a spectral DNS code makes the simulation novel?

To my knowledge, statistical convergence tests of the superdroplet method in such large simulation domain of DNS (large air viscosity though) has never been done. This is new and useful for the study of diffusional growth of cloud droplets.

2. The authors responded that “Yes, the eddy dissipation rate is a small-scale quantity, but this is how intensity of turbulence is expressed in models and in observations”.

Indeed, in the models and observations, \epsilon has been used to characterize the intensity of turbulence. However, I disagree that turbulence intensity is determined by \epsilon.

My understanding of the present study is that DNS combined with superdroplet approach is used to study the diffusional growth of cloud droplets. DNS means one solve the Navier-Stokes equation to the native scale of turbulence. Even though Re is small in DNS studies and scale contamination is inevitable, intermittency still exists, i.e., the inhomogeneous distribution of energy dissipation rate in turbulence. This intermittency is determined by the Reynolds number. That is, the energy dissipation rate is determined by the Reynolds number.
I encourage the authors to have a look at this seminal paper https://doi.org/10.1103/PhysRevLett.72.336 and numerous laboratory experimental evidence and observational evidence on this topic.

Referee Report: PDF

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RR by Anonymous Referee #3 (08 Jun 2020)

ED: Publish subject to minor revisions (review by editor) (17 Jun 2020) by Timothy Garrett

AR by Wojciech W. Grabowski on behalf of the Authors (18 Jun 2020) Author's response Manuscript

ED: Publish as is (29 Jun 2020) by Timothy Garrett

AR by Wojciech W. Grabowski on behalf of the Authors (30 Jun 2020)

Short summary

This work presents an extension of a classical small-scale modeling approach, direct numerical simulation (DNS), to large computational volumes, tens and hundreds of meters on the side. Diffusional growth of cloud droplets is more significantly affected by large scales of turbulent motions because vertical velocity perturbations associated with those scales result in larger and longer-lasting supersaturation perturbations that affect the spread of the droplet spectrum.