Make ᶜspecific lazy and remove matching_subfields

Author: charleskawczynski

src/cache/precomputed_quantities.jl

@@ -42,7 +42,7 @@ function implicit_precomputed_quantities(Y, atmos)
     TST = thermo_state_type(moisture_model, FT)
     n = n_mass_flux_subdomains(turbconv_model)
     gs_quantities = (;
-        ᶜspecific = specific_gs.(Y.c),
+        ᶜspecific = Base.materialize(ᶜspecific_gs_tracers(Y)),
         ᶜu = similar(Y.c, C123{FT}),
         ᶠu³ = similar(Y.f, CT3{FT}),
         ᶠu = similar(Y.f, CT123{FT}),
@@ -461,7 +461,7 @@ NVTX.@annotate function set_implicit_precomputed_quantities!(Y, p, t)
     thermo_params = CAP.thermodynamics_params(p.params)
     thermo_args = (thermo_params, moisture_model, precip_model)
 
-    @. ᶜspecific = specific_gs(Y.c)
+    ᶜspecific .= ᶜspecific_gs_tracers(Y)
     @. ᶠuₕ³ = $compute_ᶠuₕ³(Y.c.uₕ, Y.c.ρ)
 
     # TODO: We might want to move this to dss! (and rename dss! to something

src/prognostic_equations/hyperdiffusion.jl

@@ -6,6 +6,22 @@ import ClimaCore.Geometry as Geometry
 import ClimaCore.Fields as Fields
 import ClimaCore.Spaces as Spaces
 
+"""
+    ν₄(hyperdiff, Y)
+
+A `NamedTuple` of the hyperdiffusivity `ν₄_scalar` and the hyperviscosity
+`ν₄_vorticity`. These quantities are assumed to scale with `h^3`, where `h` is
+the mean nodal distance, following the empirical results of Lauritzen et al.
+(2018, https://doi.org/10.1029/2017MS001257). When `h == 1`, these quantities
+are equal to `hyperdiff.ν₄_scalar_coeff` and `hyperdiff.ν₄_vorticity_coeff`.
+"""
+function ν₄(hyperdiff, Y)
+    h = Spaces.node_horizontal_length_scale(Spaces.horizontal_space(axes(Y.c)))
+    ν₄_scalar = hyperdiff.ν₄_scalar_coeff * h^3
+    ν₄_vorticity = hyperdiff.ν₄_vorticity_coeff * h^3
+    return (; ν₄_scalar, ν₄_vorticity)
+end
+
 hyperdiffusion_cache(Y, atmos) = hyperdiffusion_cache(
     Y,
     atmos.hyperdiff,
@@ -34,7 +50,7 @@ function hyperdiffusion_cache(
     gs_quantities = (;
         ᶜ∇²u = similar(Y.c, C123{FT}),
         ᶜ∇²specific_energy = similar(Y.c, FT),
-        ᶜ∇²specific_tracers = remove_energy_var.(specific_gs.(Y.c)),
+        ᶜ∇²specific_tracers = Base.materialize(ᶜspecific_gs_tracers(Y)),
     )
 
     # Sub-grid scale quantities
@@ -85,7 +101,7 @@ NVTX.@annotate function prep_hyperdiffusion_tendency!(Yₜ, Y, p, t)
 
     n = n_mass_flux_subdomains(turbconv_model)
     diffuse_tke = use_prognostic_tke(turbconv_model)
-    (; ᶜp, ᶜspecific) = p.precomputed
+    (; ᶜp) = p.precomputed
     (; ᶜh_ref) = p.core
     (; ᶜ∇²u, ᶜ∇²specific_energy) = p.hyperdiff
     if turbconv_model isa PrognosticEDMFX
@@ -125,20 +141,14 @@ NVTX.@annotate function apply_hyperdiffusion_tendency!(Yₜ, Y, p, t)
     (; hyperdiff, turbconv_model) = p.atmos
     isnothing(hyperdiff) && return nothing
 
-    (; ν₄_vorticity_coeff, ν₄_scalar_coeff, divergence_damping_factor) =
-        hyperdiff
-
-    h_space = Spaces.horizontal_space(axes(Y.c))
-    h_length_scale = Spaces.node_horizontal_length_scale(h_space) # mean nodal distance
-
-    ν₄_scalar = ν₄_scalar_coeff * h_length_scale^3
-    ν₄_vorticity = ν₄_vorticity_coeff * h_length_scale^3
+    (; divergence_damping_factor) = hyperdiff
+    (; ν₄_scalar, ν₄_vorticity) = ν₄(hyperdiff, Y)
 
     n = n_mass_flux_subdomains(turbconv_model)
     diffuse_tke = use_prognostic_tke(turbconv_model)
     ᶜJ = Fields.local_geometry_field(Y.c).J
     point_type = eltype(Fields.coordinate_field(Y.c))
-    (; ᶜp, ᶜspecific) = p.precomputed
+    (; ᶜp) = p.precomputed
     (; ᶜ∇²u, ᶜ∇²specific_energy) = p.hyperdiff
     if turbconv_model isa PrognosticEDMFX
         (; ᶜρa⁰) = p.precomputed
@@ -241,11 +251,12 @@ NVTX.@annotate function prep_tracer_hyperdiffusion_tendency!(Yₜ, Y, p, t)
     (; hyperdiff, turbconv_model) = p.atmos
     isnothing(hyperdiff) && return nothing
 
-    (; ᶜspecific) = p.precomputed
     (; ᶜ∇²specific_tracers) = p.hyperdiff
 
-    for χ_name in propertynames(ᶜ∇²specific_tracers)
-        @. ᶜ∇²specific_tracers.:($$χ_name) = wdivₕ(gradₕ(ᶜspecific.:($$χ_name)))
+    # TODO: Fix RecursiveApply bug in gradₕ to fuse this operation.
+    # ᶜ∇²specific_tracers .= wdivₕ.(gradₕ.(ᶜspecific_gs_tracers(Y)))
+    foreach_gs_tracer(Y, ᶜ∇²specific_tracers) do ᶜρχ, ᶜ∇²χ, _
+        @. ᶜ∇²χ = wdivₕ(gradₕ(specific(ᶜρχ, Y.c.ρ)))
     end
 
     if turbconv_model isa PrognosticEDMFX
@@ -276,31 +287,24 @@ NVTX.@annotate function apply_tracer_hyperdiffusion_tendency!(Yₜ, Y, p, t)
     (; hyperdiff, turbconv_model) = p.atmos
     isnothing(hyperdiff) && return nothing
 
-    α_hyperdiff_tracer = CAP.α_hyperdiff_tracer(p.params)
-    (; ν₄_scalar_coeff) = hyperdiff
-    h_space = Spaces.horizontal_space(axes(Y.c))
-    h_length_scale = Spaces.node_horizontal_length_scale(h_space) # mean nodal distance
-    ν₄_scalar = ν₄_scalar_coeff * h_length_scale^3
-    n = n_mass_flux_subdomains(turbconv_model)
+    # Rescale the hyperdiffusivity for precipitating species.
+    (; ν₄_scalar) = ν₄(hyperdiff, Y)
+    ν₄_scalar_for_precip = CAP.α_hyperdiff_tracer(p.params) * ν₄_scalar
 
+    n = n_mass_flux_subdomains(turbconv_model)
     (; ᶜ∇²specific_tracers) = p.hyperdiff
 
     # TODO: Since we are not applying the limiter to density (or area-weighted
     # density), the mass redistributed by hyperdiffusion will not be conserved
     # by the limiter. Is this a significant problem?
-    # TODO: Figure out why caching the duplicated tendencies in ᶜtemp_scalar
-    # triggers allocations.
-    for (ᶜρχₜ, ᶜ∇²χ, χ_name) in matching_subfields(Yₜ.c, ᶜ∇²specific_tracers)
-        ν₄_scalar = ifelse(
-            χ_name in (:q_rai, :q_sno, :n_rai),
-            α_hyperdiff_tracer * ν₄_scalar,
-            ν₄_scalar,
-        )
-        @. ᶜρχₜ -= ν₄_scalar * wdivₕ(Y.c.ρ * gradₕ(ᶜ∇²χ))
-
-        # Exclude contributions from hyperdiffusion of condensate, 
-        # precipitating species from mass tendency. 
-        if χ_name == :q_tot
+    foreach_gs_tracer(Yₜ, ᶜ∇²specific_tracers) do ᶜρχₜ, ᶜ∇²χ, ρχ_name
+        ν₄_scalar_for_χ =
+            ρχ_name in (@name(ρq_rai), @name(ρq_sno), @name(ρn_rai)) ?
+            ν₄_scalar_for_precip : ν₄_scalar
+        @. ᶜρχₜ -= ν₄_scalar_for_χ * wdivₕ(Y.c.ρ * gradₕ(ᶜ∇²χ))
+
+        # Take into account the effect of total water diffusion on density.
+        if ρχ_name == @name(ρq_tot)
             @. Yₜ.c.ρ -= ν₄_scalar * wdivₕ(Y.c.ρ * gradₕ(ᶜ∇²χ))
         end
     end
@@ -323,13 +327,9 @@ NVTX.@annotate function apply_tracer_hyperdiffusion_tendency!(Yₜ, Y, p, t)
                 @. Yₜ.c.sgsʲs.:($$j).q_ice -=
                     ν₄_scalar * wdivₕ(gradₕ(ᶜ∇²q_iceʲs.:($$j)))
                 @. Yₜ.c.sgsʲs.:($$j).q_rai -=
-                    α_hyperdiff_tracer *
-                    ν₄_scalar *
-                    wdivₕ(gradₕ(ᶜ∇²q_raiʲs.:($$j)))
+                    ν₄_scalar_for_precip * wdivₕ(gradₕ(ᶜ∇²q_raiʲs.:($$j)))
                 @. Yₜ.c.sgsʲs.:($$j).q_sno -=
-                    α_hyperdiff_tracer *
-                    ν₄_scalar *
-                    wdivₕ(gradₕ(ᶜ∇²q_snoʲs.:($$j)))
+                    ν₄_scalar_for_precip * wdivₕ(gradₕ(ᶜ∇²q_snoʲs.:($$j)))
             end
         end
     end