A method for computing the three-dimensional radial distribution function of cloud particles from holographic images

Larsen, Michael L.; Shaw, Raymond A.

doi:https://doi.org/10.5194/amt-11-4261-2018

Articles | Volume 11, issue 7

https://doi.org/10.5194/amt-11-4261-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-11-4261-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 7

Research article

|

19 Jul 2018

Research article |

| 19 Jul 2018

A method for computing the three-dimensional radial distribution function of cloud particles from holographic images

Michael L. Larsen and Raymond A. Shaw

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Final revised paper (published on 19 Jul 2018)
Preprint (discussion started on 18 Apr 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of “A method for computing the three dimensional radial distribution function of cloud particles from holographic images” by Larsen and Shaw', Anonymous Referee #2, 24 Apr 2018
- AC1: 'Author Response to Reviewers', Michael L. Larsen, 21 Jun 2018
RC2: 'Review of Larsen and Shaw, “A Method for Computing the Three-Dimensional Radial Distribution Function of Cloud Particles from Holographic Images,” amt-2018-60', Anonymous Referee #3, 09 May 2018
- AC2: 'Author Response to Reviewers', Michael L. Larsen, 21 Jun 2018

Peer-review completion

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

AR by Michael L. Larsen on behalf of the Authors (21 Jun 2018) Author's response Manuscript

ED: Publish as is (02 Jul 2018) by Szymon Malinowski

Short summary

A statistical tool frequently utilized to measure scale-dependent departures from perfect randomness is the radial distribution function. This tool has many strengths, but it is not easy to calculate for particle detections within a three-dimensional sample volume. In this manuscript, we introduce and test a new method to estimate the three-dimensional radial distribution function in realistic measurement volumes.