Shallow cumulus convection over land in cloud-resolving simulations with a coupled ray tracer

TL;DR

This paper introduces a GPU-accelerated Monte Carlo ray tracer coupled with a flow solver to simulate land-based shallow cumulus convection, producing realistic in-cloud heating and irradiance patterns that influence cloud evolution.

Contribution

It demonstrates the integration of a GPU-accelerated Monte Carlo ray tracer with cloud simulations, improving realism in radiative transfer modeling over conventional methods.

Findings

Ray tracer provides realistic in-cloud heating rates.

Simulated cloud evolution is insensitive to ray tracer sample size.

Coupled ray tracer produces irradiance patterns matching observations.

Abstract

We present simulations of cumulus convection over land with shortwave radiation computed by a Monte Carlo ray tracer coupled to the flow solver. Ray tracing delivers very realistic in-cloud heating rates and global horizontal irradiance fields. The necessary performance of the ray tracer has been enabled by the raw power of GPU computing and from techniques for accelerating data lookup and ray tracer convergence. We used a case study over a grassland in the Netherlands to compare simulations with a coupled ray tracer to those with a conventional two-stream solver, and to test ray tracer convergence. We demonstrate that the simulated cloud evolution is insensitive across a wide range of samples sizes in the ray tracer. Furthermore, simulations with a coupled ray tracer produce surface irradiance patterns that resemble observations and that strongly feed back to the evolution of clouds via locally enhanced surface heat fluxes.