The Fractal Nature of Clouds in Global Storm-Resolving Models

TL;DR

This study investigates whether global storm-resolving models can accurately reproduce the fractal scaling laws of clouds observed in satellite data, revealing insights into model fidelity and the influence of boundary layer parametrisation.

Contribution

It demonstrates that storm-resolving models can replicate observed cloud fractal dimensions and highlights the impact of boundary layer schemes on these fractal properties.

Findings

Models reproduce observed fractal dimensions within 10%.

Fractal dimension is sensitive to boundary layer parametrisation.

Fractal dimension is independent of cloud area distributions.

Abstract

Clouds in observations are fractals: they show self-similarity across scales ranging from one to 1000 km. This includes individual storms and large-scale cloud structures typical of organised convection. It is not known whether global storm-resolving models reproduce the observed fractal scaling laws for clouds and organised convection. We compute the fractal dimension of clouds using Himawari satellite data and compare this to global storm-resolving model simulations completed as part of the DYAMOND intercomparison project. We find cloud fields in these simulations are indeed fractal, and reproduce the observed fractal dimension to within 10\%. We find the fractal dimension is sensitive to the choice of boundary layer parametrisation scheme used in each model simulation, and not to the convection parametrisation as might have been expected. The fractal dimension is independent of cloud area distributions, providing a complementary metric to assess the multi-scale structure of convection and convective organisation in model simulations.