Merge pull request #646 from CliMA/aj/rename

The Great Rename

Author: trontrytel

Project.toml

@@ -1,7 +1,7 @@
 name = "CloudMicrophysics"
 uuid = "6a9e3e04-43cd-43ba-94b9-e8782df3c71b"
 authors = ["Climate Modeling Alliance"]
-version = "0.27.4"
+version = "0.28.0"
 
 [deps]
 ClimaParams = "5c42b081-d73a-476f-9059-fd94b934656c"

box/Alpert_Knopf_2016_forward.jl

@@ -23,7 +23,7 @@ include(joinpath(pkgdir(CM), "box", "box.jl"))
 A_aero = FT(1e-5) * 1e-4 # INP surface area, m^2
 σg = 10
 N₀ = 1000
-N_ice = 0
+N_icl = 0
 T_initial = FT(256)         # initial temperature, K
 cooling_rate = FT(0.5 / 60) # prescribed cooling rate K s^-1
 aerosol = CMP.Illite(FT)    # aerosol free parameters
@@ -43,7 +43,7 @@ Aj_sorted = zeros(N₀)
 Aj_sorted = sort(Aj_unsorted, rev = true)
 
 # initial condition for the ODE problem
-IC = [T_initial, A_sum, FT(N₀), FT(N_ice)]
+IC = [T_initial, A_sum, FT(N₀), FT(N_icl)]
 # additional model parameters
 p_def = (; tps, A_aero, aerosol, cooling_rate, N₀)
 

box/box.jl

@@ -17,26 +17,26 @@ function box_model(dY, Y, p, t)
 
     # Our state vector
     T = Y[1]          # temperature
-    N_liq = Y[3]      # number concentration of existing water droplets
-    N_ice = Y[4]      # number concentration of activated ice crystals
+    N_lcl = Y[3]      # number concentration of existing water droplets
+    N_icl = Y[4]      # number concentration of activated ice crystals
 
     Δa = FT(1) - CMO.a_w_ice(tps, T)
     J_immer = CMI_het.ABIFM_J(aerosol, Δa) # m^-2 s^-1
 
     # Update the tendecies
     dT_dt = -cooling_rate
-    dN_ice_dt = FT(0)
-    dN_liq_dt = FT(0)
-    if N_liq > 0
-        dN_ice_dt = J_immer * N_liq * A_aero
-        dN_liq_dt = -dN_ice_dt
+    dN_icl_dt = FT(0)
+    dN_lcl_dt = FT(0)
+    if N_lcl > 0
+        dN_icl_dt = J_immer * N_lcl * A_aero
+        dN_lcl_dt = -dN_icl_dt
     end
 
     # Set tendencies
     dY[1] = dT_dt          # temperature
     dY[2] = FT(0)          # not used here
-    dY[3] = dN_liq_dt      # number concentration of droplets
-    dY[4] = dN_ice_dt      # number concentration of ice crystals
+    dY[3] = dN_lcl_dt      # number concentration of droplets
+    dY[4] = dN_icl_dt      # number concentration of ice crystals
 end
 
 """
@@ -52,8 +52,8 @@ function box_model_with_probability(dY, Y, p, t)
     # Our state vector
     T = Y[1]                      # temperature
     A = Y[2]                      # available surface area for freezing
-    N_liq = max(FT(0), Y[3])      # number concentration of existing water droplets
-    N_ice = max(FT(0), Y[4])      # number concentration of activated ice crystals
+    N_lcl = max(FT(0), Y[3])      # number concentration of existing water droplets
+    N_icl = max(FT(0), Y[4])      # number concentration of activated ice crystals
 
     # immersion freezing rate
     Δa = FT(1) - CMO.a_w_ice(tps, T)
@@ -62,9 +62,9 @@ function box_model_with_probability(dY, Y, p, t)
     # Update the tendecies
     dT_dt = -cooling_rate
     dAj_dt = FT(0)
-    dN_ice_dt = FT(0)
-    dN_liq_dt = FT(0)
-    if N_liq > 0
+    dN_icl_dt = FT(0)
+    dN_lcl_dt = FT(0)
+    if N_lcl > 0
         n_frz = 0
         for j in range(start = 1, stop = N₀, step = 1)
             # Sample from the surface area distribution
@@ -81,15 +81,15 @@ function box_model_with_probability(dY, Y, p, t)
         end
         Aj_sum = sum(Aj_sorted)
         dAj_dt = (Aj_sum - A) / const_dt
-        dN_ice_dt = max(FT(0), n_frz / const_dt)
-        dN_liq_dt = -dN_ice_dt
+        dN_icl_dt = max(FT(0), n_frz / const_dt)
+        dN_lcl_dt = -dN_icl_dt
     end
 
     # Set tendencies
     dY[1] = dT_dt          # temperature
     dY[2] = dAj_dt         # total Aj
-    dY[3] = dN_liq_dt      # mumber concentration of droplets
-    dY[4] = dN_ice_dt      # number concentration of ice activated particles
+    dY[3] = dN_lcl_dt      # mumber concentration of droplets
+    dY[4] = dN_icl_dt      # number concentration of ice activated particles
 
 end
 
@@ -100,16 +100,16 @@ Returns the solution of an ODE probelm defined by the box model.
 
 Inputs:
  - IC - A vector with the initial conditions for
-   [T, A_sum, N_liq, N_ice]
+   [T, A_sum, N_lcl, N_icl]
  - t_0 - simulation start time
  - t_end - simulation end time
  - p - a named tuple with simulation parameters.
 
 Initial condition contains (all in base SI units):
  - T - temperature
  - A_sum - available surface area for freezing
- - N_liq - cloud droplet number concnentration
- - N_ice - ice crystal number concentration
+ - N_lcl - cloud droplet number concnentration
+ - N_icl - ice crystal number concentration
 
 The named tuple p should contain:
  - tps - a struct with free parameters for Thermodynamics package,

docs/make.jl

@@ -63,6 +63,7 @@ Guides = [
 pages = Any[
     "Home" => "index.md",
     "Parameterizations" => Parameterizations,
+    "Thermodynamics interface" => "Thermodynamics.md",
     "How to guides" => Guides,
     "Models" => Models,
     "API" => "API.md",

docs/src/API.md

@@ -8,8 +8,8 @@ CurrentModule = CloudMicrophysics
 ```@docs
 MicrophysicsNonEq
 MicrophysicsNonEq.τ_relax
-MicrophysicsNonEq.conv_q_vap_to_q_liq_ice
-MicrophysicsNonEq.conv_q_vap_to_q_liq_ice_MM2015
+MicrophysicsNonEq.conv_q_vap_to_q_lcl_icl
+MicrophysicsNonEq.conv_q_vap_to_q_lcl_icl_MM2015
 MicrophysicsNonEq.terminal_velocity
 ```
 
@@ -28,9 +28,9 @@ Microphysics1M.get_v0
 Microphysics1M.get_n0
 Microphysics1M.lambda_inverse
 Microphysics1M.terminal_velocity
-Microphysics1M.conv_q_liq_to_q_rai
-Microphysics1M.conv_q_ice_to_q_sno_no_supersat
-Microphysics1M.conv_q_ice_to_q_sno
+Microphysics1M.conv_q_lcl_to_q_rai
+Microphysics1M.conv_q_icl_to_q_sno_no_supersat
+Microphysics1M.conv_q_icl_to_q_sno
 Microphysics1M.accretion
 Microphysics1M.accretion_rain_sink
 Microphysics1M.accretion_snow_rain
@@ -63,17 +63,17 @@ Microphysics2M.get_size_distribution_bounds
 
 ## Rates
 ```@docs
-Microphysics2M.LiqRaiRates
+Microphysics2M.LclRaiRates
 Microphysics2M.autoconversion
 Microphysics2M.accretion
-Microphysics2M.liquid_self_collection
-Microphysics2M.autoconversion_and_liquid_self_collection
+Microphysics2M.cloud_liquid_self_collection
+Microphysics2M.autoconversion_and_cloud_liquid_self_collection
 Microphysics2M.rain_self_collection
 Microphysics2M.rain_breakup
 Microphysics2M.rain_self_collection_and_breakup
 Microphysics2M.rain_terminal_velocity
 Microphysics2M.rain_evaporation
-Microphysics2M.conv_q_liq_to_q_rai
+Microphysics2M.conv_q_lcl_to_q_rai
 Microphysics2M.number_increase_for_mass_limit
 Microphysics2M.number_decrease_for_mass_limit
 ```

docs/src/CloudDiagnostics.md

@@ -8,13 +8,13 @@ Available diagnostics are:
  - Radar reflectivity
  - Effective radius
 
-Calculating these diagnostics make use of the physical moment equation for the 
+Calculating these diagnostics make use of the physical moment equation for the
 generalized gamma distribution, as a function of particle mass. We denote the moment
-as ``M_x^n`` to emphasize that it is the moment with respect to the particle size 
+as ``M_x^n`` to emphasize that it is the moment with respect to the particle size
 distribution written as a function of particle mass ``x``.
 ```math
 \begin{equation}
-M_x^n(;N, ν, μ, B) 
+M_x^n(;N, ν, μ, B)
   = ∫_0^∞ x^n ⋅ f(x) dx
   = N ⋅ B^{-\frac{n}{μ}} ⋅ \frac{Γ\left(\frac{ν+1+n}{μ}\right)}{Γ\left(\frac{ν+1}{μ}\right)}
 \end{equation}
@@ -106,8 +106,8 @@ We compute the total third and second moment as a sum of cloud condensate and
 precipitation moments:
 ```math
 \begin{equation}
-r_{eff} 
-  = \frac{M^3_{r,c} + M^3_{r,r}}{M^2_{r,c} + M^2_{r,r}} 
+r_{eff}
+  = \frac{M^3_{r,c} + M^3_{r,r}}{M^2_{r,c} + M^2_{r,r}}
   = \frac{∫_0^∞ r^3 \, (n_c(r) + n_r(r)) \, dr}{∫_0^∞ r^2 \, (n_c(r) + n_r(r)) \, dr}.
 \label{eq:reff}
 \end{equation}
@@ -145,12 +145,12 @@ where:
 Where the volume-averaged radius is computed using
 ```math
 \begin{equation}
-  r_{vol} = \left(\frac{3}{4 \pi \rho_w}\right)^{\frac{1}{3}} \, \left(\frac{L}{N}\right)^{\frac{1}{3}} = \left(\frac{3  \rho (q_{liq} + q_{rai})}{4 \pi \rho_w (N_{liq} + N_{rai})}\right)^{\frac{1}{3}},
+  r_{vol} = \left(\frac{3}{4 \pi \rho_w}\right)^{\frac{1}{3}} \, \left(\frac{L}{N}\right)^{\frac{1}{3}} = \left(\frac{3  \rho (q_{lcl} + q_{rai})}{4 \pi \rho_w (N_{lcl} + N_{rai})}\right)^{\frac{1}{3}},
 \end{equation}
 ```
 where:
-  - ``L = \rho q``, is the liquid water content,
-  - ``N = N_{liq} + N_{rai}``.
+  - ``L = \rho q``, is the liquid water content (cloud water and rain),
+  - ``N = N_{lcl} + N_{rai}``.
 
 By default for the 1-moment scheme we don't consider precipitation and assume
 a constant cloud droplet number concentration of 100 $cm^{-3}$.

docs/src/IceNucleation.md

@@ -27,14 +27,14 @@ The parameterization for deposition on dust particles is an implementation of
 ## Activated fraction for deposition freezing on dust
 There are 2 parameterizations from [Mohler2006](@cite) available: one
   which calculates the activated fraction and one which calculates nucleation
-  rate. 
+  rate.
 The activated fraction parameterization follows eq. (3) in the paper.
 ```math
 \begin{equation}
 f_i(S_i) = exp[a(S_i - S_0)] - 1
 \end{equation}
 ```
-where 
+where
   - ``f_i`` is the activated fraction
      (the ratio of aerosol particles acting as ice nuclei to the total number of aerosol particles),
   - ``a`` is a scaling parameter dependent on aerosol properties and temperature,
@@ -45,7 +45,7 @@ The other parameterization models the nucleation rate of ice
   see eq. (5) in [Mohler2006](@cite).
 ```math
 \begin{equation}
-\frac{dn_{ice}}{dt} = N_{aer} a \frac{dS_i}{dt}
+\frac{dn_{icl}}{dt} = N_{aer} a \frac{dS_i}{dt}
 \end{equation}
 ```
 where:
@@ -140,11 +140,11 @@ Once ``J_{ABIFM}`` is calculated, it can be used to determine the ice production
 per second via immersion freezing.
 ```math
 \begin{equation}
-  P_{ice} = J_{ABIFM}A(N_{aer} - N_{ice})
+  P_{ice} = J_{ABIFM}A(N_{aer} - N_{icl})
 \end{equation}
 ```
 where ``A`` is surface area of an individual ice nuclei, ``N_{aer}`` is total number
-  of ice nuclei, and ``N_{ice}`` is number of ice crystals already in the system.
+  of ice nuclei, and ``N_{icl}`` is number of ice crystals already in the system.
 
 ### ABIFM Example Figures
 The following plot shows ``J`` as a function of ``\Delta a_w`` as compared to
@@ -186,12 +186,12 @@ It is also important to note that this plot is reflective of cirrus clouds
 
 ### Bigg (1953) Volume and Time Dependent Heterogeneous Freezing
 Heterogeneous freezing in the P3 scheme as described in [MorrisonMilbrandt2015](@cite)
-  follows the parameterization from [Bigg1953](@cite) with parameters from 
+  follows the parameterization from [Bigg1953](@cite) with parameters from
   [BarklieGokhale1959](@cite). The number of ice nucleated in a timestep via
   heterogeneous freezing is determined by
 ```math
 \begin{equation}
-  N_{ice} = N_{liq} \left[ 1 - exp(-B V_{l} \Delta t exp(aT_s)) \right]
+  N_{icl} = N_{lcl} \left[ 1 - exp(-B V_{l} \Delta t exp(aT_s)) \right]
 \end{equation}
 ```
 where `a` and `B` are parameters taken from [BarklieGokhale1959](@cite) for
@@ -276,7 +276,7 @@ For the activity based immersion freezing model (ABIFM):
  - Magenta corresponds to kaolinite.
 The P3 heterogeneous parameterization also shows much more ICNC than any of the ABIFM runs. It
   should be noted that the P3 parameterization does not distinguish between immersion freezing,
-  contact freezing, etc. 
+  contact freezing, etc.
 
 The P3 scheme allows homogeneous freezing to freeze all droplets at temperatures equal to or less than 233.15K. No homogeneous freezing occurs at warmer temperatures.
 
@@ -302,7 +302,7 @@ where ``T`` is the temperature in degrees Celsius, ``INPC`` is the INP concentra
 
     Our implementation uses base SI units and takes ``T`` in Kelvin.
 
-The following plot shows the relative frequency distribution for INPCs, as a function of temperature (the same as figure 1 in [Frostenberg2023](@cite)). 
+The following plot shows the relative frequency distribution for INPCs, as a function of temperature (the same as figure 1 in [Frostenberg2023](@cite)).
 
 ```@example
 include("plots/Frostenberg_fig1.jl")
@@ -311,4 +311,4 @@ include("plots/Frostenberg_fig1.jl")
 
 The following plot shows the relative frequency distribution for INPCs at the temperature ``T=-16 C``.
 
-![](Frostenberg_fig1_T16.svg)
+![](Frostenberg_fig1_T16.svg)

docs/src/IceNucleationParcel0D.md

@@ -271,11 +271,11 @@ Following the water activity based immersion freezing model (ABIFM), the ABIFM d
   per second via immersion freezing can then be calculating using
 ```math
 \begin{equation}
-  P_{ice, immer} = \left[ \frac{dN_i}{dt} \right]_{immer} = J_{immer}\;A_{aero}(N_{liq})
+  P_{ice, immer} = \left[ \frac{dN_i}{dt} \right]_{immer} = J_{immer}\;A_{aero}(N_{lcl})
   \label{eq:ABIFM_P_ice}
 \end{equation}
 ```
-where ``N_{liq}`` is total number of ice nuclei containing droplets and
+where ``N_{lcl}`` is total number of ice nuclei containing droplets and
   ``A_{aero}`` is surface area of the ice nucleating particle.
 
 ### Homogeneous Freezing
@@ -285,11 +285,11 @@ Homogeneous freezing follows the water-activity based model described in the
 The ice production rate from homogeneous freezing can then be determined:
 ```math
 \begin{equation}
-  P_{ice, hom} = \left[ \frac{dN_i}{dt} \right]_{hom} = J_{hom}V(N_{liq})
+  P_{ice, hom} = \left[ \frac{dN_i}{dt} \right]_{hom} = J_{hom}V(N_{lcl})
   \label{eq:hom_P_ice}
 \end{equation}
 ```
-where ``N_{liq}`` is total number of ice nuclei containing droplets and
+where ``N_{lcl}`` is total number of ice nuclei containing droplets and
   ``V`` is the volume of those droplets.
 
 ### P3 Ice Nucleation Parameterizations
@@ -459,8 +459,8 @@ and `stochastic` (solid lines) parameterization options. We show results for two
 Below, we show how the non-equilibrium formulation is able to represent the
 Wegener-Bergeron-Findeisen (WBF) regime in the parcel model.
 These plots show the liquid supersaturation, ice supersaturation,
-temperature, specific humidity `q_{vap}`, specific content of liquid `q_{liq}`,
-and specific content of ice `q_{ice}` over time.
+temperature, specific humidity `q_{vap}`, specific content of cloud liquid `q_{lcl}`,
+and specific content of cloud ice `q_{icl}` over time.
 When the supersaturation is negative evaporation/sublimation occurs,
 and when it is positive condensation/deposition occurs.
 In the example below, the water vapor pressure is smaller than the saturation water vapor pressure of liquid

docs/src/Microphysics0M.md

@@ -25,23 +25,23 @@ If based on maximum condensate specific content, the sink is defined as:
 ``` math
 \begin{equation}
   \left. \frac{d \, q_{tot}}{dt} \right|_{precip} =-
-    \frac{\max(0, q_{liq} + q_{ice} - q_{c0})}{\tau_{precip}}
+    \frac{\max(0, q_{lcl} + q_{icl} - q_{c0})}{\tau_{precip}}
 \end{equation}
 ```
 where:
-  - ``q_{liq}``, ``q_{ice}`` are cloud liquid water and cloud ice specific contents,
+  - ``q_{lcl}``, ``q_{icl}`` are cloud liquid water and cloud ice specific contents,
   - ``q_{c0}`` is the condensate specific content threshold above which water is removed,
   - ``\tau_{precip}`` is the relaxation timescale.
 
 If based on saturation excess, the sink is defined as:
 ```math
 \begin{equation}
   \left. \frac{d \, q_{tot}}{dt} \right|_{precip} =-
-    \frac{\max(0, q_{liq} + q_{ice} - S_{0} \, q_{vap}^{sat})}{\tau_{precip}}
+    \frac{\max(0, q_{lcl} + q_{icl} - S_{0} \, q_{vap}^{sat})}{\tau_{precip}}
 \end{equation}
 ```
 where:
-  - ``q_{liq}``, ``q_{ice}`` are cloud liquid water and cloud ice specific contents,
+  - ``q_{lcl}``, ``q_{icl}`` are cloud liquid water and cloud ice specific contents,
   - ``S_{0}`` is the supersaturation threshold above which water is removed,
   - ``q_{vap}^{sat}`` is the saturation specific humidity,
   - ``\tau_{precip}`` is the relaxation timescale.