Author
Listed:
- Cheraghalizadeh, Jafar
- Luković, Mirko
- Najafi, Morteza N.
Abstract
Recently it was shown that self-organized criticality is an important component of the dynamics of cumulus clouds (Najafi et al., 2021). Here we introduce a new algorithm to simulate cumulus clouds in two-dimensional square lattices, based on two important facts: the cohesive energy of wet air parcels and a sand-pile-type diffusion of cloud segments. The latter is realized by considering the evaporation/condensation of air parcels in various regions of the cloud, which enables them to diffuse to the neighboring regions. The results stemming from this model are in excellent agreement with observations reported in the above-cited paper, in which the exponents were determined for two-dimensional earth-to-sky RGB cloud images. The exponents obtained at the lowest condensation level in our model are consistent with the exponents observed in nature. We find that the cloud fields obtained from our model are fractal, with the outer perimeter having a fractal dimension of Df=1.25±0.01. Furthermore, the distributions of the radius of gyration and the loop length follow a power-law function with exponents τr=2.3±0.1 and τl=2.1±0.1, respectively. The loop Green function is found to be logarithmic with the radius of gyration of the loops following the observational results. The winding angle statistic of the external perimeter of the cloud field is also analyzed, showing an exponent in agreement with the fractal dimension, which may serve as the conformal invariance of the system.
Suggested Citation
Cheraghalizadeh, Jafar & Luković, Mirko & Najafi, Morteza N., 2024.
"Simulating cumulus clouds based on self-organized criticality,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
Handle:
RePEc:eee:phsmap:v:636:y:2024:i:c:s037843712400061x
DOI: 10.1016/j.physa.2024.129553
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:636:y:2024:i:c:s037843712400061x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.