Size-Distribution

ModelingToolkit implementation of a multi-modal lognormal atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"). The model represents the aerosol number, surface-area and volume distributions as a sum of three lognormal modes (Eq. 8.54), and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl AerosolDistribution. Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at the default and documented n_modes = 3; default mode parameters are the Urban distribution of Table 8.3.

ModelingToolkit implementation of the Desert atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Desert distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [726, 114, 0.178] cm^-3, D_g = [0.002, 0.038, 21.60] um, log10 sigma = [0.247, 0.770, 0.438]) — two fine modes plus a coarse mineral-dust mode at 21.6 um. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl DesertAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Desert Table 8.3 mode parameters as defaults.

ModelingToolkit implementation of the Free troposphere atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Free troposphere distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [129, 59.7, 63.5] cm^-3, D_g = [0.007, 0.250, 0.520] um, log10 sigma = [0.645, 0.253, 0.425]) — a nucleation/ultrafine mode at 7 nm plus two sub-micron accumulation modes. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl FreeTroposphereAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Free troposphere Table 8.3 mode parameters as defaults.

ModelingToolkit implementation of the Marine atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Marine distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [133, 66.6, 3.1] cm^-3, D_g = [0.008, 0.266, 0.580] um, log10 sigma = [0.657, 0.210, 0.396]) — a dilute marine boundary-layer background with a nucleation mode, an accumulation mode, and a coarse mode at 0.58 um. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl MarineAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Marine Table 8.3 mode parameters as defaults.

ModelingToolkit implementation of the Polar atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Polar distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [21.7, 0.186, 3.0e-4] cm^-3, D_g = [0.138, 0.75, 8.6] um, log10 sigma = [0.245, 0.300, 0.291]) — a dilute accumulation mode plus two coarse modes characteristic of the very clean polar atmosphere. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl PolarAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Polar Table 8.3 mode parameters as defaults.

ModelingToolkit implementation of the Remote-continental atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Remote-continental distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [3200, 2900, 0.3] cm^-3, D_g = [0.020, 0.116, 1.800] um, log10 sigma = [0.161, 0.217, 0.380]) — a number-rich continental background of two fine modes plus a sparse coarse mode at 1.8 um. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl RemoteContinentalAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Remote-continental Table 8.3 mode parameters as defaults.

ModelingToolkit implementation of the Rural atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Rural distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [6650, 147, 1990] cm^-3, D_g = [0.015, 0.054, 0.084] um, log10 sigma = [0.225, 0.557, 0.266]) — three sub-micron continental-background modes, with no coarse mode. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl RuralAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Rural Table 8.3 mode parameters as defaults.

Two-moment stochastic collection equation (SCE) for cloud-droplet coalescence (Tzivion, Feingold & Levin 1989), scalarized to I=5 mass-doubling categories. Two models, one per collection kernel: StochasticCollectionConstant (K=K0) and StochasticCollectionGolovin (K=C(x+y)). Each tracks number concentration N_k and mass concentration M_k in every category and closes the higher moments with the non-dimensional parameter xi_p. Migrated from the array-variable @component in Aerosol.jl src/stochastic_collection.jl @ c8c640bb636b22f2425460e9ed5cba50793bfee1 (esm-ar1e); the upstream @arrayop/@makearray array operations were scalarized to flat scalar states and equations.

Two-moment stochastic collection equation (SCE) for cloud-droplet coalescence (Tzivion, Feingold & Levin 1989), scalarized to I=5 mass-doubling categories. Two models, one per collection kernel: StochasticCollectionConstant (K=K0) and StochasticCollectionGolovin (K=C(x+y)). Each tracks number concentration N_k and mass concentration M_k in every category and closes the higher moments with the non-dimensional parameter xi_p. Migrated from the array-variable @component in Aerosol.jl src/stochastic_collection.jl @ c8c640bb636b22f2425460e9ed5cba50793bfee1 (esm-ar1e); the upstream @arrayop/@makearray array operations were scalarized to flat scalar states and equations.

TwO-Moment Aerosol Sectional (TOMAS) Brownian-coagulation model with five mass-doubling size bins. Each bin k carries two moments - particle number concentration N_k and mass concentration M_k - and the bins are coupled by Brownian coagulation: intra- and inter-bin collisions remove particles and transfer mass toward larger bins at rates set by a precomputed 5x5 coagulation-coefficient matrix. f_k and psi_k are the within-bin linear number-distribution reconstruction coefficients of the two-moment scheme, evaluated algebraically from N_k. Migrated from the module-level script Aerosol.jl src/TOMAS.jl @ c8c640bb636b22f2425460e9ed5cba50793bfee1; the upstream array-variable ODESystem was scalarized to 20 scalar unknowns and mtk2esm-scaffolded. All coagulation coefficients, bin masses and the bin-spacing factor xi are baked in as numeric literals, so the model has no free parameters.

ModelingToolkit implementation of the Urban atmospheric aerosol size distribution, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 8 ("Properties of the Atmospheric Aerosol"), Table 8.3. The Urban distribution is a preset of the multi-modal lognormal AerosolDistribution model: three lognormal modes (N = [99300, 1110, 36400] cm^-3, D_g = [0.013, 0.014, 0.050] um, log10 sigma = [0.245, 0.666, 0.337]) — a nucleation mode and an Aitken mode at sub-20 nm plus an accumulation mode at 50 nm, characteristic of polluted urban air. The model represents the aerosol number, surface-area and volume distributions as a sum of the three modes (Eq. 8.54) and reports the total number/surface/volume concentrations, the mode-1 Hatch-Choate diameters, and the vertical aerosol mass profile (Eq. 8.55). Migrated from Aerosol.jl UrbanAerosol, a preset wrapper around AerosolDistribution(3). Purely algebraic: ten observed outputs, no differential states, an empty equations array. The upstream length-n_modes array parameters are scalarized at n_modes = 3 with the Urban Table 8.3 mode parameters as defaults.

Size-distribution and fall-speed diagnostics of the WRF single-moment 6-class microphysics scheme (WSM6; Hong and Lim 2006), transcribed from slope_wsm6 and the cold-rain preamble of mp_wsm6_run in phys/physics_mmm/mp_wsm6.F90 (WRF 4.8, NCAR/MMM-physics): the temperature-dependent snow intercept factor n0s(T)/n0s (HDC 2004 eq. 6), the inverse slopes lambda^-1 of the exponential rain, snow and graupel distributions and their powers lambda^-b, lambda^-2, lambda^-3 (held at 1/lambda_max below the threshold qcrmin), the diagnosed ice crystal number concentration N_i (HDC eq. 5c), mean ice crystal diameter D_i (HDC eq. 5b) and fall speed V_i (HDC eq. 5a), the mass-weighted fall speeds of rain, snow and graupel V = a Gamma(4+b)/6 lambda^-b (rho0/rho)^(1/2), the ventilation coefficients precs1/2 and precg1/2 of the snow and graupel distributions (mp_wsm6_init products shared by deposition, evaporation and melting), and the combined snow/graupel fall speed WSM6 uses since V3.0. Everything is a pointwise function of the layer state on the layer index `lev` (WRF k, layer 1 at the surface). It also holds the transport properties of air at T and p (kinematic viscosity, vapor diffusivity, thermal conductivity; lib/wrf_air_properties.esm), the ventilation factor (WSM6 work2) and the ventilation moments coeres of rain, snow and graupel. The process-rate components (warm_rain.esm, cold_accretion.esm, ice_deposition.esm) mount this component as subsystem `sd` and take all of these from it, mirroring how the kernel computes them once per sub-step (slope_wsm6) and reuses them in every process; melting_freezing.esm evaluates the same templates at its own, earlier state. Scheme constants come from wsm6_parameters.esm (subsystem `par`) and physical constants from lib/wrf_constants.esm (subsystem `wrf`). Consumer-supplied inputs are the rewrite-target ops `input_<name>` lowered in the inline tests through a per-test template library extracted from kernel dumps of the instrumented WRF fork ctessum-claude/WRF, commit e42a269 (v4.8.0-2-ge42a269e). EqWeFiC, cited here for FORTRAN_BUGS.md and couplings/, is https://github.com/EarthSciML/EqWeFiC, where these components were developed and are coupled into a WRF column.