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

Hossein Parishani, Michael Pritchard, Christopher Bretherton, Matthew Wyant & Marat Khairoutdinov
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...
1 citation reported since publication in 2019.
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