Prescribe cloud N in r_eff, update to the newest CloudMicrophysics

Author: trontrytel

Project.toml

@@ -48,7 +48,7 @@ ClimaDiagnostics = "0.2.12"
 ClimaParams = "0.10.19"
 ClimaTimeSteppers = "0.8.2"
 ClimaUtilities = "0.1.22"
-CloudMicrophysics = "0.22.8"
+CloudMicrophysics = "0.22.9"
 Dates = "1"
 DiffEqBase = "6.145"
 FastGaussQuadrature = "0.5, 1"

reproducibility_tests/ref_counter.jl

@@ -1,4 +1,4 @@
-220
+221
 
 # **README**
 #
@@ -20,6 +20,9 @@
 
 
 #=
+221
+- Change the way cloud liquid effective radius is computed for radiation
+
 220
 - Split out cached variables that should be treated implicitly, so that all
   other cached variables are no longer updated by the implicit solver

src/callbacks/callbacks.jl

@@ -208,8 +208,14 @@ NVTX.@annotate function rrtmgp_model_callback!(integrator)
             # RRTMGP needs effective radius in microns
             @. ᶜreliq = ifelse(
                 cloud_liquid_water_content > FT(0),
-                CM.CloudDiagnostics.effective_radius_const(cmc.liquid) *
-                m_to_um_factor,
+                CM.CloudDiagnostics.effective_radius_Liu_Hallet_97(
+                    cmc.liquid,
+                    Y.c.ρ,
+                    cloud_liquid_water_content / max(eps(FT), cloud_fraction),
+                    cmc.N_cloud_liquid_droplets,
+                    FT(0),
+                    FT(0),
+                ) * m_to_um_factor,
                 FT(0),
             )
             @. ᶜreice = ifelse(

src/parameters/create_parameters.jl

@@ -107,10 +107,18 @@ atmos_name_map = (;
     :optics_lookup_temperature_max => :optics_lookup_temperature_max,
 )
 
-cloud_parameters(FT_or_toml) = (;
-    liquid = CM.Parameters.CloudLiquid(FT_or_toml),
-    ice = CM.Parameters.CloudIce(FT_or_toml),
-    Ch2022 = CM.Parameters.Chen2022VelType(FT_or_toml),
+cloud_parameters(::Type{FT}) where {FT <: AbstractFloat} =
+    cloud_parameters(CP.create_toml_dict(FT))
+
+cloud_parameters(toml_dict::CP.AbstractTOMLDict) = (;
+    liquid = CM.Parameters.CloudLiquid(toml_dict),
+    ice = CM.Parameters.CloudIce(toml_dict),
+    Ch2022 = CM.Parameters.Chen2022VelType(toml_dict),
+    N_cloud_liquid_droplets = CP.get_parameter_values(
+        toml_dict,
+        "prescribed_cloud_droplet_number_concentration",
+        "ClimaAtmos",
+    ).prescribed_cloud_droplet_number_concentration,
 )
 
 microphys_1m_parameters(::Type{FT}) where {FT <: AbstractFloat} =