GFS saSAS Deep Convection Module

This subroutine contains the entirety of the SAMF deep convection scheme. More...

Functions/Subroutines
subroutine	samfdeepcnv::samfdeepcnv_run (im, km, first_time_step, restart, tmf, qmicro, itc, ntc, cliq, cp, cvap, eps, epsm1, fv, grav, hvap, rd, rv, t0c, delt, ntk, ntr, delp, prslp, psp, phil, qtr, prevsq, q, q1, t1, u1, v1, fscav, hwrf_samfdeep, progsigma, cldwrk, rn, kbot, ktop, kcnv, islimsk, garea, dot, ncloud, hpbl, ud_mf, dd_mf, dt_mf, cnvw, cnvc, QLCN, QICN, w_upi, cf_upi, CNV_MFD, CNV_DQLDT, CLCN, CNV_FICE, CNV_NDROP, CNV_NICE, mp_phys, mp_phys_mg, clam, c0s, c1, betal, betas, evef, pgcon, asolfac, do_ca, ca_closure, ca_entr, ca_trigger, nthresh, ca_deep, rainevap, sigmain, sigmaout, errmsg, errflg)

Detailed Description

For grid sizes larger than threshold value, as in Grell (1993) [77] , the SAMF deep convection scheme can be described in terms of three types of "controls": static, dynamic, and feedback. The static control component consists of the simple entraining/detraining updraft/downdraft cloud model and is used to determine the cloud properties, convective precipitation, as well as the convective cloud top height. The dynamic control is the determination of the potential energy available for convection to "consume", or how primed the large-scale environment is for convection to occur due to changes by the dyanmics of the host model. The feedback control is the determination of how the parameterized convection changes the large-scale environment (the host model state variables) given the changes to the state variables per unit cloud base mass flux calculated in the static control portion and the deduced cloud base mass flux determined from the dynamic control.

For grid sizes smaller than threshold value, the cloud base mass flux in the SAMF scheme is determined by the cumulus updraft velocity averaged ove the whole cloud depth (Han et al. (2017) [84] ), which in turn, determines changes of the large-scale environment due to the cumulus convection.

Argument Table

GFS samfdeepcnv General Algorithm

1. Compute preliminary quantities needed for static, dynamic, and feedback control portions of the algorithm.
2. Perform calculations related to the updraft of the entraining/detraining cloud model ("static control").
3. Perform calculations related to the downdraft of the entraining/detraining cloud model ("static control").
4. For grid sizes larger than the threshold value (currently 8 km):
   • 1) Using the updated temperature and moisture profiles that were modified by the convection on a short time-scale, recalculate the total cloud work function to determine the change in the cloud work function due to convection, or the stabilizing effect of the cumulus.
   • 2) For the "dynamic control", using a reference cloud work function, estimate the change in cloud work function due to the large-scale dynamics. Following the quasi-equilibrium assumption, calculate the cloud base mass flux required to keep the large-scale convective destabilization in balance with the stabilization effect of the convection.
5. For grid sizes smaller than the threshold value (currently 8 km):
   • 1) compute the cloud base mass flux using the cumulus updraft velocity averaged ove the whole cloud depth.
6. For scale awareness, the updraft fraction (sigma) is obtained as a function of cloud base entrainment. Then, the final cloud base mass flux is obtained by the original mass flux multiplied by the (1-sigma) 2.
7. For the "feedback control", calculate updated values of the state variables by multiplying the cloud base mass flux and the tendencies calculated per unit cloud base mass flux from the static control.

GFS samfdeepcnv Detailed Algorithm