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Merge pull request #380 from CliMA/al/aida_calib
Generalize ice nucleation calibration funcs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,128 @@ | ||
| import ClimaParams as CP | ||
| import CloudMicrophysics as CM | ||
| import CloudMicrophysics.Parameters as CMP | ||
| import Thermodynamics as TD | ||
|
|
||
| #! format: off | ||
| function perf_model_params(FT, IN_mode) | ||
| if IN_mode == "ABDINM" | ||
| const_dt = FT(1) | ||
| w = FT(0.4) | ||
| dep_nucleation = "ABDINM" | ||
| heterogeneous = "None" | ||
| homogeneous = "None" | ||
| condensation_growth = "None" | ||
| deposition_growth = "Deposition" | ||
| size_distribution = "Monodisperse" | ||
| elseif IN_mode == "ABIFM" | ||
| const_dt = FT(1) | ||
| w = FT(0.4) | ||
| dep_nucleation = "None" | ||
| heterogeneous = "ABIFM" | ||
| homogeneous = "None" | ||
| condensation_growth = "Condensation" | ||
| deposition_growth = "Deposition" | ||
| size_distribution = "Monodisperse" | ||
| elseif IN_mode == "ABHOM" | ||
| const_dt = FT(1) | ||
| w = FT(1) | ||
| dep_nucleation = "None" | ||
| heterogeneous = "None" | ||
| homogeneous = "ABHOM" | ||
| condensation_growth = "None" | ||
| deposition_growth = "Deposition" | ||
| size_distribution = "Monodisperse" | ||
| end | ||
| params = (; const_dt, w, | ||
| condensation_growth, deposition_growth, # growth | ||
| size_distribution, # size distribution | ||
| dep_nucleation, heterogeneous, homogeneous, # nucleation | ||
| ) | ||
| return params | ||
| end | ||
|
|
||
| function perf_model_IC(FT, IN_mode) | ||
| tps = TD.Parameters.ThermodynamicsParameters(FT) | ||
| wps = CMP.WaterProperties(FT) | ||
|
|
||
| ρₗ = wps.ρw | ||
| R_d = TD.Parameters.R_d(tps) | ||
| R_v = TD.Parameters.R_v(tps) | ||
| ϵₘ = R_d / R_v | ||
|
|
||
| if IN_mode == "ABDINM" | ||
| Nₐ = FT(8e6) # according to fig 2 panel b deposition nucleation experiment | ||
| Nₗ = FT(0) | ||
| Nᵢ = FT(0) | ||
| r₀ = FT(0.5e-6) | ||
| p₀ = FT(987.018 * 1e2) | ||
| T₀ = FT(212.978) | ||
| C_v = FT(10.8509 * 1e-6) | ||
| qᵥ = ϵₘ / (ϵₘ - 1 + 1 / C_v) | ||
| qₗ = FT(0) | ||
| qᵢ = FT(0) | ||
| q = TD.PhasePartition.(qᵥ + qₗ + qᵢ, qₗ, qᵢ) | ||
| Rₐ = TD.gas_constant_air(tps, q) | ||
| eₛ = TD.saturation_vapor_pressure(tps, T₀, TD.Liquid()) | ||
| e = eᵥ(qᵥ, p₀, Rₐ, R_v) | ||
| Sₗ = FT(e / eₛ) | ||
| elseif IN_mode == "ABIFM" | ||
| Nₐ = FT(0) | ||
| Nₗ = FT(8e6) | ||
| Nᵢ = FT(0) | ||
| r₀ = FT(0.5e-6) | ||
| p₀ = FT(987.018 * 1e2) | ||
| T₀ = FT(212.978) | ||
| qₗ = FT(Nₗ * 4 / 3 * FT(π) * r₀^3 * ρₗ / FT(1.2)) # 1.2 should be ρₐ | ||
| C_l = FT(qₗ / ((1 - qₗ) * ϵₘ + qₗ)) # concentration/mol fraction of liquid | ||
| C_v = FT(10.8509 * 1e-6 - C_l) # concentration/mol fraction of vapor | ||
| qᵥ = ϵₘ / (ϵₘ - 1 + 1 / C_v) | ||
| qᵢ = FT(0) | ||
| q = TD.PhasePartition.(qᵥ + qₗ + qᵢ, qₗ, qᵢ) | ||
| Rₐ = TD.gas_constant_air(tps, q) | ||
| eₛ = TD.saturation_vapor_pressure(tps, T₀, TD.Liquid()) | ||
| e = eᵥ(qᵥ, p₀, Rₐ, R_v) | ||
| Sₗ = FT(e / eₛ) | ||
| elseif IN_mode == "ABHOM" | ||
| Nₐ = FT(0) | ||
| Nₗ = FT(300 * 1e6) | ||
| Nᵢ = FT(0) | ||
| r₀ = FT(25 * 1e-9) | ||
| p₀ = FT(9712.183) | ||
| T₀ = FT(190) | ||
| qₗ = FT(Nₗ * 4 / 3 * FT(π) * r₀^3 * ρₗ / FT(1.2)) # 1.2 should be ρₐ | ||
| C_l = FT(qₗ / ((1 - qₗ) * ϵₘ + qₗ)) # concentration/mol fraction of liquid | ||
| C_v = FT(5 * 1e-6) | ||
| qᵥ = ϵₘ / (ϵₘ - 1 + 1 / C_v) | ||
| qᵢ = FT(0) | ||
| q = TD.PhasePartition.(qᵥ + qₗ + qᵢ, qₗ, qᵢ) | ||
| Rₐ = TD.gas_constant_air(tps, q) | ||
| eₛ = TD.saturation_vapor_pressure(tps, T₀, TD.Liquid()) | ||
| e = eᵥ(qᵥ, p₀, Rₐ, R_v) | ||
| Sₗ = FT(e / eₛ) | ||
| end | ||
| return [Sₗ, p₀, T₀, qᵥ, qₗ, qᵢ, Nₐ, Nₗ, Nᵢ, FT(0)] | ||
| end | ||
|
|
||
| function perf_model_pseudo_data(FT, IN_mode, params, IC) | ||
| n_samples = 10 | ||
|
|
||
| if IN_mode == "ABDINM" | ||
| coeff_true = [FT(27.551), FT(-2.2209)] | ||
| elseif IN_mode == "ABIFM" | ||
| coeff_true = [FT(54.58834), FT(-10.54758)] | ||
| elseif IN_mode == "ABHOM" | ||
| coeff_true = [FT(255.927125), FT(-68.553283)] | ||
| end | ||
|
|
||
| G_truth = run_model(params, coeff_true, IN_mode, FT, IC) | ||
| dim_output = length(G_truth) | ||
|
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||
| Γ = 0.005 * LinearAlgebra.I * (maximum(G_truth) - minimum(G_truth)) | ||
| noise_dist = Distributions.MvNormal(zeros(dim_output), Γ) | ||
|
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||
| y_truth = zeros(length(G_truth), n_samples) # where noisy ICNC will be stored | ||
| y_truth = G_truth .+ rand(noise_dist) | ||
| return [y_truth, Γ, coeff_true] | ||
| end | ||
| #! format: on |
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