Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data

Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

doi:https://doi.org/10.5194/npg-27-133-2020

Articles | Volume 27, issue 1

https://doi.org/10.5194/npg-27-133-2020

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

https://doi.org/10.5194/npg-27-133-2020

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

Articles | Volume 27, issue 1

Research article

|

19 Mar 2020

Research article |

| 19 Mar 2020

Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data

Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer

Data sets

Data for ``Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data'' by Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer, NPG 2020 A. Gires, I. Tchiguirinskaia, and D. Schertzer https://doi.org/10.5281/zenodo.3707904

Short summary

This paper aims to analyse and simulate correlations between two fields in a scale-invariant framework. It starts by theoretically assessing and numerically confirming the behaviour of renormalized multiplicative power law combinations of two fields with known scale-invariant properties. Then a new indicator of correlation is suggested and tested on rainfall data to study the correlation between the common rain rate and drop size distribution features.