Move entrainment fact to climaparams method call

CliMA · Aug 8, 2021 · 5cfd332 · 5cfd332
1 parent 81c9f0f
commit 5cfd332
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Showing 4 changed files with 16 additions and 16 deletions.
diff --git a/integration_tests/utils/parameter_set.jl b/integration_tests/utils/parameter_set.jl
@@ -9,13 +9,15 @@ end
 
 CLIMAParameters.Planet.MSLP(ps::EarthParameterSet) = ps.nt.MSLP
 CLIMAParameters.Atmos.Microphysics.τ_cond_evap(ps::EarthParameterSet) = ps.nt.τ_cond_evap
+CLIMAParameters.Atmos.EDMF.c_ε(ps::EarthParameterSet) = ps.nt.c_ε
 
 #! format: off
 function create_parameter_set(namelist)
     TC = TurbulenceConvection
     nt = (;
         MSLP = 100000.0, # or grab from, e.g., namelist[""][...]
         τ_cond_evap = TC.parse_namelist(namelist, "microphysics", "τ_cond_evap"; default = 10.0),
+        c_ε = TC.parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "entrainment_factor"),
     )
     return EarthParameterSet(nt)
 end

diff --git a/src/Turbulence_PrognosticTKE.jl b/src/Turbulence_PrognosticTKE.jl
@@ -934,6 +934,7 @@ function compute_updraft_closures(self::EDMF_PrognosticTKE, GMV::GridMeanVariabl
     sa = eos_struct()
     quadrature_order = 3
     grid = get_grid(self)
+    param_set = parameter_set(self)
 
     upd_cloud_diagnostics(self.UpdVar, reference_state(self))
 
@@ -942,7 +943,6 @@ function compute_updraft_closures(self::EDMF_PrognosticTKE, GMV::GridMeanVariabl
     input.dz = get_grid(self).dz
     input.zbl = compute_zbl_qt_grad(GMV)
     input.sort_pow = self.sorting_power
-    input.c_ent = self.entrainment_factor
     input.c_det = self.detrainment_factor
     input.c_div = self.entrainment_Mdiv_factor
     input.c_mu = self.entrainment_sigma
@@ -999,7 +999,7 @@ function compute_updraft_closures(self::EDMF_PrognosticTKE, GMV::GridMeanVariabl
                 input.dMdz = (input.M - Mm) * grid.dzi
                 input.tke = self.EnvVar.TKE.values[k]
 
-                ret = self.entr_detr_fp(input)
+                ret = self.entr_detr_fp(param_set, input)
                 self.entr_sc[i, k] = ret.entr_sc
                 self.detr_sc[i, k] = ret.detr_sc
                 self.sorting_function[i, k] = ret.sorting_function

diff --git a/src/turbulence_functions.jl b/src/turbulence_functions.jl
@@ -1,6 +1,6 @@
 # Entrainment Rates
 
-function entr_detr_env_moisture_deficit_b_ED_MF(entr_in::entr_struct)
+function entr_detr_env_moisture_deficit_b_ED_MF(param_set::APS, entr_in::entr_struct)
     _ret = entr_struct()
 
     moisture_deficit_d =
@@ -39,13 +39,14 @@ function entr_detr_env_moisture_deficit_b_ED_MF(entr_in::entr_struct)
         fabs(entr_in.buoy_ed_flux) /
         (fabs(entr_in.a_upd * entr_in.a_env * (entr_in.w_upd - entr_in.w_env) * (entr_in.b_upd - entr_in.b_env)) + 1e-8)
     logistic_e *= (1.0 / (1.0 + exp(entr_in.c_ed_mf * (ed_mf_ratio - 1.0))))
-    _ret.entr_sc = inv_timescale / dw * (entr_in.c_ent * logistic_e + c_det * moisture_deficit_e)
-    _ret.detr_sc = inv_timescale / dw * (entr_in.c_ent * logistic_d + c_det * moisture_deficit_d)
+    c_ε = CPEDMF.c_ε(param_set)
+    _ret.entr_sc = inv_timescale / dw * (c_ε * logistic_e + c_det * moisture_deficit_e)
+    _ret.detr_sc = inv_timescale / dw * (c_ε * logistic_d + c_det * moisture_deficit_d)
 
     return _ret
 end
 
-function entr_detr_env_moisture_deficit(entr_in::entr_in_struct)
+function entr_detr_env_moisture_deficit(param_set::APS, entr_in::entr_in_struct)
     _ret = entr_struct()
     l = zeros(2)
 
@@ -83,13 +84,14 @@ function entr_detr_env_moisture_deficit(entr_in::entr_in_struct)
     l[1] = entr_in.tke_coef * fabs(db / sqrt(entr_in.tke + 1e-8))
     l[2] = fabs(db / dw)
     inv_timescale = lamb_smooth_minimum(l, 0.1, 0.0005)
-    _ret.entr_sc = inv_timescale / dw * (entr_in.c_ent * logistic_e + c_det * moisture_deficit_e)
-    _ret.detr_sc = inv_timescale / dw * (entr_in.c_ent * logistic_d + c_det * moisture_deficit_d)
+    c_ε = CPEDMF.c_ε(param_set)
+    _ret.entr_sc = inv_timescale / dw * (c_ε * logistic_e + c_det * moisture_deficit_e)
+    _ret.detr_sc = inv_timescale / dw * (c_ε * logistic_d + c_det * moisture_deficit_d)
 
     return _ret
 end
 
-function entr_detr_env_moisture_deficit_div(entr_in::entr_struct)
+function entr_detr_env_moisture_deficit_div(param_set::APS, entr_in::entr_struct)
     _ret = entr_struct()
     l = zeros(2)
 
@@ -132,10 +134,9 @@ function entr_detr_env_moisture_deficit_div(entr_in::entr_struct)
     l[2] = fabs(db / dw)
     inv_timescale = lamb_smooth_minimum(l, 0.1, 0.0005)
 
-    _ret.entr_sc =
-        inv_timescale / dw * (entr_in.c_ent * logistic_e + c_det * moisture_deficit_e) + entr_MdMdz * entr_in.c_div
-    _ret.detr_sc =
-        inv_timescale / dw * (entr_in.c_ent * logistic_d + c_det * moisture_deficit_d) + detr_MdMdz * entr_in.c_div
+    c_ε = CPEDMF.c_ε(param_set)
+    _ret.entr_sc = inv_timescale / dw * (c_ε * logistic_e + c_det * moisture_deficit_e) + entr_MdMdz * entr_in.c_div
+    _ret.detr_sc = inv_timescale / dw * (c_ε * logistic_d + c_det * moisture_deficit_d) + detr_MdMdz * entr_in.c_div
 
 
     return _ret

diff --git a/src/types.jl b/src/types.jl
@@ -73,7 +73,6 @@ Base.@kwdef mutable struct entr_in_struct
     dz::Float64 = 0
     w_upd::Float64 = 0
     b_upd::Float64 = 0
-    c_ent::Float64 = 0
     dt::Float64 = 0
     b_env::Float64 = 0
     a_upd::Float64 = 0
@@ -761,7 +760,6 @@ mutable struct EDMF_PrognosticTKE{PS, A1, A2}
     extrapolate_buoyancy::Bool
     surface_area::Float64
     max_area::Float64
-    entrainment_factor::Float64
     entrainment_Mdiv_factor::Float64
     updraft_mixing_frac::Float64
     entrainment_sigma::Float64
@@ -1077,7 +1075,6 @@ mutable struct EDMF_PrognosticTKE{PS, A1, A2}
             extrapolate_buoyancy,
             surface_area,
             max_area,
-            entrainment_factor,
             entrainment_Mdiv_factor,
             updraft_mixing_frac,
             entrainment_sigma,