Interactive Meso‐scale Simulation of Skyscapes

Abstract

Although an important component of natural scenes, the representation of skyscapes is often relatively simplistic. This can be largely attributed to the complexity of the thermodynamics underpinning cloud evolution and wind dynamics, which make interactive simulation challenging. We address this problem by introducing a novel layered model that encompasses both terrain and atmosphere, and supports efficient meteorological simulations. The vertical and horizontal layer resolutions can be tuned independently, while maintaining crucial inter-layer thermodynamics, such as convective circulation and land-air transfers of heat and moisture. In addition, we introduce a cloud-form taxonomy for clustering, classifying and upsampling simulation cells to enable visually plausible, finely-sampled volumetric rendering. As our results demonstrate, this pipeline allows interactive simulation followed by up-sampled rendering of extensive skyscapes with dynamic clouds driven by consistent wind patterns. We validate our method by reproducing characteristic phenomena such as diurnal shore breezes, convective cells that contribute to cumulus cloud formation, and orographic effects from moist air driven upslope.

Stormscapes

“…On the other hand, recent work in cloud modeling captures the formation of other cloud types, beyond the scope of this work, by adopting a higher scale of abstraction [Vimont et al 2020]. The results we show indicate that our method can simulate various plausible cloud morphologies while expressing accurately seminal physical hypotheses of cloud formation.…”

“…Due to the complexity of cloud simulations, also considering the often very large spatial extend, numerous methods introduce refined representations for simulating clouds. This ranges from geometric-and particle-based representations [Bouthors and Neyret 2004;Gardner 1985;Neyret 1997], coupled map lattices for extended cellular automata [Miyazaki et al 2001], position-based dynamics [Ferreira Barbosa et al 2015] to layer-based approaches [Vimont et al 2020]. Due to these representations a wide range of cloud phenomena can be simulated realistically and efficiently.…”

“…In computer graphics, existing methods for clouds either focus on simulating specific cloud types [Goswami and Neyret 2017;Harris et al 2003], their interactive generation [Dobashi et al 2008], representations to enable cloud formations [Vimont et al 2020], or the realistic rendering [Bitterli et al 2018;. Moreover, it has even been recognized that clouds and other weather phenomena can be used as a means for modeling urban landscapes [Garcia-Dorado et al 2017].…”

Interactive simulation of plume and pyroclastic volcanic ejections

“…Closer to the high-speed, turbulent, and dense gas ejected by volcanoes, weather phenomena such as cloud formation share the challenge of combining large spatial extents with small-scale details. Similar to cloud simulation methods [8,11,31], we model thermal transfer and buoyancy. However, existing solutions cannot be reused in our case.…”

Ecoclimates

“…Physics-based approaches for cloud modeling employ Eulerian solvers to advect fluids for simulating different forms of clouds [Harris et al 2003;Herrera et al 2021;Miyazaki et al 2001;Overby et al 2002]. Due to the importance of clouds in various application domains, there exists a number of representations for clouds that range from particles [Bouthors et al 2008;Goswami and Neyret 2017;Neyret 1997], position-based dynamics [Ferreira Barbosa et al 2015] to layers [Vimont et al 2020], interpolation-based methods [Webanck et al 2018], and cellular automata [Miyazaki et al 2001]. However, despite these advances, simulating cloud dynamics remains a challenging research problem.…”