formatting changes

Author: wilsonduan10

examples/SurfaceFluxExample/kappa_calibration.jl

@@ -6,10 +6,10 @@ the equation: u(z) = u^* / κ log (z / z0),
 which represents the wind profile in Monin-Obukhov
 Similarity Theory (MOST) formulations. In order to recover the empirically determined κ = 0.4, 
 we use data from the John Hopkins Tubulence Channel Flow, which offers DNS simulations of a channel flow with 
-smooth wall boundary conditions, i.e. z0m ≈ 0 m. The dataset can be found here: https://turbulence.pha.jhu.edu/Channel_Flow.aspx
+smooth wall boundary conditions, i.e. z0m ≈ 0 m. The dataset can be found here: https://turbulence.pha.jhu.edu/Channel\_Flow.aspx.
 We use the dataset's u^* as an observable, and each ensemble member estimates u^* through the
-SurfaceFluxes.jl function surface_conditions, see https://github.com/CliMA/SurfaceFluxes.jl
-In order to calculate u^*, the function surface_conditions is provided a set of thermodynamic params,
+SurfaceFluxes.jl function surface\_conditions, see https://github.com/CliMA/SurfaceFluxes.jl
+In order to calculate u^*, the function surface\_conditions is provided a set of thermodynamic params,
 a functional form for stability functions (Businger, Gryanick, Grachev), and the constants corresponding
 to that functional form. In this example, we elect the Businger functions. 
 =#
@@ -52,10 +52,10 @@ include("setup_parameter_set.jl")
 Next, we download and read data from the John Hopkins Tubulence Channel Flow dataset,
 specifically those concerning mean velocity and its variance over various heights.
 The parameters defining the dataset are given by:
-- u_star = 4.14872e-02
+- u\_star = 4.14872e-02
 - δ = 1.000
 - ν = 8.00000e-06
-- Re_tau = 5185.897
+- Re\_tau = 5185.897
 =#
 mkpath(joinpath(@__DIR__, "data")) # create data folder if not exists
 web_datafile_path = "https://turbulence.oden.utexas.edu/channel2015/data/LM_Channel_5200_mean_prof.dat"
@@ -69,7 +69,7 @@ z = data_mean_velocity[:, 1]
 u = data_mean_velocity[:, 3] * u_star_obs
 
 # Next, we define our physical model, where we first define thermodynamic parameters
-# and MOST parameters to pass into the surface_conditions function from SurfaceFluxes.jl.
+# and MOST parameters to pass into the surface\_conditions function from SurfaceFluxes.jl.
 # We define the MOST stability functions to be of the Businger type.
 """
     physical_model(inputs, parameters)
@@ -116,7 +116,7 @@ function physical_model(parameters, inputs)
 
     κ_nt = (; von_karman_const = κ)
 
-    # Now, we initialize the variable surf_flux_params, which we will eventually pass into 
+    # Now, we initialize the variable surf\_flux\_params, which we will eventually pass into 
     # surface_conditions along with mean wind data
     UFP = typeof(ufp)
     TPtype = typeof(thermo_params)
@@ -262,4 +262,4 @@ png("final_and_initial_ensemble")
 # ![see plot: ](../assets/kappa_calibration_plot2.png)
 
 # Evidently, EKI was highly successful at recovering the von karman constant κ = 0.4. This process will be extended to recover
-# stability function parameters such as a_m, a_h, b_m, b_h, and Pr_0. 
+# stability function parameters such as a\_m, a\_h, b\_m, b\_h, and Pr\_0.