Radiation is key process in numerical models of the atmosphere. The problem is well-understood and the parameterization of radiation has seen relatively few conceptual advances in the past 15 years. It is nonthelss often the single most expensive component of all physical parameterizations despite being computed less frequently than other terms. This combination of cost and maturity suggests value in a single radiation parameterization that could be shared across models; devoting effort to a single parameterization might allow for fine tuning for efficiency. The challenge lies in the coupling of this parameterization to many disparate representations of clouds and aerosols.

This talk will describe RRTMGP, a new radiation parameterization that seeks to balance efficiency and flexibility. This balance is struck by isolating computational tasks in "kernels" that expose as much fine-grained parallelism as possible. These have simple interfaces and are interoperable across programming languages so that they might be repalced by alternative implementations in domain-specific langauges. Coupling to the host model makes use of object-oriented features of Fortran 2003, minimizing branching within the kernels and the amount of data that must be transferred.

We will show accuracy and efficiency results for a globally-representative set of atmospheric profiles using a relatively high-resolution spectral discretization.