The Simplified Arakawa-Schubert scheme parameterizes the effect of deep convection on the environment (represented by the model state variables) in the following way. First, a simple cloud model is used to determine the change in model state variables due to one entraining/detraining cloud type, per unit cloud-base mass flux. Next, the total change in state variables is retrieved by determining the actual cloud base mass flux using the quasi-equilibrium assumption, whereby convection is assumed to be steady-state. This implies that the generation of the cloud work function (interpreted as entrainment-moderated convective available potential energy (CAPE)) by the large scale dynamics is in balance with the consumption of the cloud work function by the convection. More...
Files | |
file | sascnvn.F |
Contains the entire SAS deep convection scheme. | |
Modules | |
module | sascnvn |
Functions/Subroutines | |
subroutine, public | sascnvn::sascnvn_init (imfdeepcnv, imfdeepcnv_sas, errmsg, errflg) |
subroutine, public | sascnvn::sascnvn_run ( |
This subroutine contains the entirety of the SAS deep convection scheme. | |
The SAS scheme uses the working concepts put forth in Arakawa and Schubert (1974) [6] but includes modifications and simplifications from Grell (1993) [75] such as saturated downdrafts and only one cloud type (the deepest possible), rather than a spectrum based on cloud top heights or assumed entrainment rates. The scheme was implemented for the GFS in 1995 by Pan and Wu [166], with further modifications discussed in Han and Pan (2011) [80] , including the calculation of cloud top, a greater CFL-criterion-based maximum cloud base mass flux, updated cloud model entrainment and detrainment, improved convective transport of horizontal momentum, a more general triggering function, and the inclusion of convective overshooting.
This space is reserved for a description of how this scheme uses information from other scheme types and/or how information calculated in this scheme is used in other scheme types.