Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence -- simulation data

This data set contains the simulation outputs used in the study summarized below:

 

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of

uncertainty in climate projections. A variation on superparameterization (SP) called ‘‘ultraparameterization’’

(UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough

(250x20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate

model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model

using 2-degree resolution (14,000 embedded CRMs) with one-moment microphysics. By using a small domain

and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.

Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere

radiation and cloud vertical structure. The most encouraging improvemen...