diff --git a/.github/workflows/CodeCov.yml b/.github/workflows/CodeCov.yml
index c3ed91c..db43231 100644
--- a/.github/workflows/CodeCov.yml
+++ b/.github/workflows/CodeCov.yml
@@ -19,7 +19,7 @@ jobs:
     - name: Set up Julia
       uses: julia-actions/setup-julia@latest
       with:
-        version: 1.10.3
+        version: 1.10.5
 
     - name: Test with coverage
       env:
diff --git a/.github/workflows/JuliaFormatter.yml b/.github/workflows/JuliaFormatter.yml
index 8200588..222278b 100644
--- a/.github/workflows/JuliaFormatter.yml
+++ b/.github/workflows/JuliaFormatter.yml
@@ -31,7 +31,7 @@ jobs:
     - uses: julia-actions/setup-julia@latest
       if: steps.filter.outputs.julia_file_change == 'true'
       with:
-        version: 1.10.3
+        version: 1.10.5
 
     - name: Apply JuliaFormatter
       if: steps.filter.outputs.julia_file_change == 'true'
diff --git a/.github/workflows/UpDeps.yml b/.github/workflows/UpDeps.yml
index aa1fef4..18421c4 100644
--- a/.github/workflows/UpDeps.yml
+++ b/.github/workflows/UpDeps.yml
@@ -23,7 +23,7 @@ jobs:
 
     - uses: julia-actions/setup-julia@latest
       with:
-        version: 1.10.3
+        version: 1.10.5
 
     - name: Apply UpDeps
       run: |
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 3ca7bbe..3419312 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -16,7 +16,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.10.3'
+          - '1.10.5'
         os:
           - ubuntu-latest
           - macOS-latest
diff --git a/Data/Atlas_LES_Profiles/download_atlas_les_profiles.jl b/Data/Atlas_LES_Profiles/download_atlas_les_profiles.jl
index eed7787..1da7d78 100644
--- a/Data/Atlas_LES_Profiles/download_atlas_les_profiles.jl
+++ b/Data/Atlas_LES_Profiles/download_atlas_les_profiles.jl
@@ -92,7 +92,7 @@ SOCRATES_flight_observations_Box_links = Dict( # The raw observational data from
     These all have the same fiilename so we have to manually append the flight number to the filename
 
 """
-function download_atlas_les_outputs(; cases = cases)
+function download_atlas_les_outputs(; cases::AbstractArray{Int} = cases, forcing_type::Symbol = :obs_data)
 
     # create joinpath(thisdir, "Output_Data") if doesn't exist
     if !isdir(joinpath(thisdir, "Output_Data"))
@@ -106,23 +106,27 @@ function download_atlas_les_outputs(; cases = cases)
         ERA5_filename = RF_num * "_output/era5/SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc" # e.g. https://atmos.uw.edu/~ratlas/RF12_output/era5/SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc
 
         # download obs model output
-        try
-            obs_savepath = joinpath(thisdir, "Output_Data", RF_num * "_Obs_" * split(obs_filename, "/")[end]) # just the filename, not any paths
-            download("https://atmos.uw.edu/~ratlas/" * obs_filename, obs_savepath)
-            @info "Found $("https://atmos.uw.edu/~ratlas/"*obs_filename)"
-        catch e
-            @warn "Did not find $("https://atmos.uw.edu/~ratlas/"*obs_filename)"
-            # @warn e
-        end
 
-        # download ERA5 forcing
-        try
-            ERA5_savepath = joinpath(thisdir, "Output_Data", RF_num * "_ERA5_" * split(ERA5_filename, "/")[end]) # just the filename, not any paths
-            download("https://atmos.uw.edu/~ratlas/" * ERA5_filename, ERA5_savepath)
-            @info "Found $("https://atmos.uw.edu/~ratlas/"*ERA5_filename)"
-        catch e
-            @warn "Did not find $("https://atmos.uw.edu/~ratlas/"*ERA5_filename)"
-            # @warn e
+        if forcing_type == :obs_data
+            try
+                obs_savepath = joinpath(thisdir, "Output_Data", RF_num * "_Obs_" * split(obs_filename, "/")[end]) # just the filename, not any paths
+                download("https://atmos.uw.edu/~ratlas/" * obs_filename, obs_savepath)
+                @info "Found $("https://atmos.uw.edu/~ratlas/"*obs_filename)"
+            catch e
+                @warn "Did not find $("https://atmos.uw.edu/~ratlas/"*obs_filename)"
+                # @warn e
+            end
+
+        elseif forcing_type == :ERA5_data
+            # download ERA5 forcing
+            try
+                ERA5_savepath = joinpath(thisdir, "Output_Data", RF_num * "_ERA5_" * split(ERA5_filename, "/")[end]) # just the filename, not any paths
+                download("https://atmos.uw.edu/~ratlas/" * ERA5_filename, ERA5_savepath)
+                @info "Found $("https://atmos.uw.edu/~ratlas/"*ERA5_filename)"
+            catch e
+                @warn "Did not find $("https://atmos.uw.edu/~ratlas/"*ERA5_filename)"
+                # @warn e
+            end
         end
     end
 end
diff --git a/Manifest.toml b/Manifest.toml
index 96689b5..2a3873d 100644
--- a/Manifest.toml
+++ b/Manifest.toml
@@ -1,14 +1,14 @@
 # This file is machine-generated - editing it directly is not advised
 
-julia_version = "1.10.3"
+julia_version = "1.10.5"
 manifest_format = "2.0"
 project_hash = "09cee719b9d2d781c7d51cda0b1b8d979bb782d1"
 
 [[deps.Adapt]]
 deps = ["LinearAlgebra", "Requires"]
-git-tree-sha1 = "6a55b747d1812e699320963ffde36f1ebdda4099"
+git-tree-sha1 = "50c3c56a52972d78e8be9fd135bfb91c9574c140"
 uuid = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
-version = "4.0.4"
+version = "4.1.1"
 weakdeps = ["StaticArrays"]
 
     [deps.Adapt.extensions]
@@ -23,29 +23,34 @@ uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
 
 [[deps.Atomix]]
 deps = ["UnsafeAtomics"]
-git-tree-sha1 = "c06a868224ecba914baa6942988e2f2aade419be"
+git-tree-sha1 = "c3b238aa28c1bebd4b5ea4988bebf27e9a01b72b"
 uuid = "a9b6321e-bd34-4604-b9c9-b65b8de01458"
-version = "0.1.0"
+version = "1.0.1"
+
+    [deps.Atomix.extensions]
+    AtomixCUDAExt = "CUDA"
+    AtomixMetalExt = "Metal"
+    AtomixoneAPIExt = "oneAPI"
+
+    [deps.Atomix.weakdeps]
+    CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+    Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
+    oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b"
 
 [[deps.Base64]]
 uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
 
 [[deps.Bzip2_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "9e2a6b69137e6969bab0152632dcb3bc108c8bdd"
+git-tree-sha1 = "8873e196c2eb87962a2048b3b8e08946535864a1"
 uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0"
-version = "1.0.8+1"
-
-[[deps.CEnum]]
-git-tree-sha1 = "389ad5c84de1ae7cf0e28e381131c98ea87d54fc"
-uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
-version = "0.5.0"
+version = "1.0.8+4"
 
 [[deps.CFTime]]
 deps = ["Dates", "Printf"]
-git-tree-sha1 = "5afb5c5ba2688ca43a9ad2e5a91cbb93921ccfa1"
+git-tree-sha1 = "937628bf8b377208ac359f57314fd85d3e0165d9"
 uuid = "179af706-886a-5703-950a-314cd64e0468"
-version = "0.1.3"
+version = "0.1.4"
 
 [[deps.CommonDataModel]]
 deps = ["CFTime", "DataStructures", "Dates", "Preferences", "Printf"]
@@ -54,16 +59,16 @@ uuid = "1fbeeb36-5f17-413c-809b-666fb144f157"
 version = "0.2.5"
 
 [[deps.CommonSubexpressions]]
-deps = ["MacroTools", "Test"]
-git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7"
+deps = ["MacroTools"]
+git-tree-sha1 = "cda2cfaebb4be89c9084adaca7dd7333369715c5"
 uuid = "bbf7d656-a473-5ed7-a52c-81e309532950"
-version = "0.3.0"
+version = "0.3.1"
 
 [[deps.Compat]]
 deps = ["TOML", "UUIDs"]
-git-tree-sha1 = "b1c55339b7c6c350ee89f2c1604299660525b248"
+git-tree-sha1 = "8ae8d32e09f0dcf42a36b90d4e17f5dd2e4c4215"
 uuid = "34da2185-b29b-5c13-b0c7-acf172513d20"
-version = "4.15.0"
+version = "4.16.0"
 weakdeps = ["Dates", "LinearAlgebra"]
 
     [deps.Compat.extensions]
@@ -92,15 +97,15 @@ version = "1.9.1"
 
 [[deps.Dierckx]]
 deps = ["Dierckx_jll"]
-git-tree-sha1 = "d1ea9f433781bb6ff504f7d3cb70c4782c504a3a"
+git-tree-sha1 = "7da4b14cc4c3443a1afc64abee17f4fcb45ad837"
 uuid = "39dd38d3-220a-591b-8e3c-4c3a8c710a94"
-version = "0.5.3"
+version = "0.5.4"
 
 [[deps.Dierckx_jll]]
-deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "6596b96fe1caff3db36415eeb6e9d3b50bfe40ee"
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "3251f44b3cac6fec4cec8db45d3ab0bfed51c4d8"
 uuid = "cd4c43a9-7502-52ba-aa6d-59fb2a88580b"
-version = "0.1.0+0"
+version = "0.2.0+0"
 
 [[deps.DiffResults]]
 deps = ["StaticArraysCore"]
@@ -130,9 +135,9 @@ uuid = "7b1f6079-737a-58dc-b8bc-7a2ca5c1b5ee"
 
 [[deps.ForwardDiff]]
 deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "LinearAlgebra", "LogExpFunctions", "NaNMath", "Preferences", "Printf", "Random", "SpecialFunctions"]
-git-tree-sha1 = "cf0fe81336da9fb90944683b8c41984b08793dad"
+git-tree-sha1 = "a2df1b776752e3f344e5116c06d75a10436ab853"
 uuid = "f6369f11-7733-5829-9624-2563aa707210"
-version = "0.10.36"
+version = "0.10.38"
 weakdeps = ["StaticArrays"]
 
     [deps.ForwardDiff.extensions]
@@ -146,9 +151,9 @@ version = "1.14.2+1"
 
 [[deps.Hwloc_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "ca0f6bf568b4bfc807e7537f081c81e35ceca114"
+git-tree-sha1 = "50aedf345a709ab75872f80a2779568dc0bb461b"
 uuid = "e33a78d0-f292-5ffc-b300-72abe9b543c8"
-version = "2.10.0+0"
+version = "2.11.2+3"
 
 [[deps.InteractiveUtils]]
 deps = ["Markdown"]
@@ -161,45 +166,31 @@ version = "0.2.2"
 
 [[deps.JLLWrappers]]
 deps = ["Artifacts", "Preferences"]
-git-tree-sha1 = "7e5d6779a1e09a36db2a7b6cff50942a0a7d0fca"
+git-tree-sha1 = "a007feb38b422fbdab534406aeca1b86823cb4d6"
 uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
-version = "1.5.0"
+version = "1.7.0"
 
 [[deps.KernelAbstractions]]
-deps = ["Adapt", "Atomix", "InteractiveUtils", "LinearAlgebra", "MacroTools", "PrecompileTools", "Requires", "SparseArrays", "StaticArrays", "UUIDs", "UnsafeAtomics", "UnsafeAtomicsLLVM"]
-git-tree-sha1 = "db02395e4c374030c53dc28f3c1d33dec35f7272"
+deps = ["Adapt", "Atomix", "InteractiveUtils", "MacroTools", "PrecompileTools", "Requires", "StaticArrays", "UUIDs"]
+git-tree-sha1 = "b9a838cd3028785ac23822cded5126b3da394d1a"
 uuid = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
-version = "0.9.19"
+version = "0.9.31"
 
     [deps.KernelAbstractions.extensions]
     EnzymeExt = "EnzymeCore"
+    LinearAlgebraExt = "LinearAlgebra"
+    SparseArraysExt = "SparseArrays"
 
     [deps.KernelAbstractions.weakdeps]
     EnzymeCore = "f151be2c-9106-41f4-ab19-57ee4f262869"
-
-[[deps.LLVM]]
-deps = ["CEnum", "LLVMExtra_jll", "Libdl", "Preferences", "Printf", "Requires", "Unicode"]
-git-tree-sha1 = "065c36f95709dd4a676dc6839a35d6fa6f192f24"
-uuid = "929cbde3-209d-540e-8aea-75f648917ca0"
-version = "7.1.0"
-
-    [deps.LLVM.extensions]
-    BFloat16sExt = "BFloat16s"
-
-    [deps.LLVM.weakdeps]
-    BFloat16s = "ab4f0b2a-ad5b-11e8-123f-65d77653426b"
-
-[[deps.LLVMExtra_jll]]
-deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"]
-git-tree-sha1 = "88b916503aac4fb7f701bb625cd84ca5dd1677bc"
-uuid = "dad2f222-ce93-54a1-a47d-0025e8a3acab"
-version = "0.0.29+0"
+    LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+    SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [[deps.LLVMOpenMP_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "d986ce2d884d49126836ea94ed5bfb0f12679713"
+git-tree-sha1 = "78211fb6cbc872f77cad3fc0b6cf647d923f4929"
 uuid = "1d63c593-3942-5779-bab2-d838dc0a180e"
-version = "15.0.7+0"
+version = "18.1.7+0"
 
 [[deps.LazyArtifacts]]
 deps = ["Artifacts", "Pkg"]
@@ -234,9 +225,9 @@ uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
 
 [[deps.Libiconv_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "f9557a255370125b405568f9767d6d195822a175"
+git-tree-sha1 = "be484f5c92fad0bd8acfef35fe017900b0b73809"
 uuid = "94ce4f54-9a6c-5748-9c1c-f9c7231a4531"
-version = "1.17.0+0"
+version = "1.18.0+0"
 
 [[deps.LinearAlgebra]]
 deps = ["Libdl", "OpenBLAS_jll", "libblastrampoline_jll"]
@@ -244,9 +235,9 @@ uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 
 [[deps.LogExpFunctions]]
 deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"]
-git-tree-sha1 = "18144f3e9cbe9b15b070288eef858f71b291ce37"
+git-tree-sha1 = "13ca9e2586b89836fd20cccf56e57e2b9ae7f38f"
 uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
-version = "0.3.27"
+version = "0.3.29"
 
     [deps.LogExpFunctions.extensions]
     LogExpFunctionsChainRulesCoreExt = "ChainRulesCore"
@@ -263,9 +254,9 @@ uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
 
 [[deps.MPICH_jll]]
 deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"]
-git-tree-sha1 = "4099bb6809ac109bfc17d521dad33763bcf026b7"
+git-tree-sha1 = "7715e65c47ba3941c502bffb7f266a41a7f54423"
 uuid = "7cb0a576-ebde-5e09-9194-50597f1243b4"
-version = "4.2.1+1"
+version = "4.2.3+0"
 
 [[deps.MPIPreferences]]
 deps = ["Libdl", "Preferences"]
@@ -275,15 +266,14 @@ version = "0.1.11"
 
 [[deps.MPItrampoline_jll]]
 deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"]
-git-tree-sha1 = "8c35d5420193841b2f367e658540e8d9e0601ed0"
+git-tree-sha1 = "70e830dab5d0775183c99fc75e4c24c614ed7142"
 uuid = "f1f71cc9-e9ae-5b93-9b94-4fe0e1ad3748"
-version = "5.4.0+0"
+version = "5.5.1+2"
 
 [[deps.MacroTools]]
-deps = ["Markdown", "Random"]
-git-tree-sha1 = "2fa9ee3e63fd3a4f7a9a4f4744a52f4856de82df"
+git-tree-sha1 = "72aebe0b5051e5143a079a4685a46da330a40472"
 uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
-version = "0.5.13"
+version = "0.5.15"
 
 [[deps.Markdown]]
 deps = ["Base64"]
@@ -296,9 +286,9 @@ version = "2.28.2+1"
 
 [[deps.MicrosoftMPI_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "f12a29c4400ba812841c6ace3f4efbb6dbb3ba01"
+git-tree-sha1 = "bc95bf4149bf535c09602e3acdf950d9b4376227"
 uuid = "9237b28f-5490-5468-be7b-bb81f5f5e6cf"
-version = "10.1.4+2"
+version = "10.1.4+3"
 
 [[deps.Mmap]]
 uuid = "a63ad114-7e13-5084-954f-fe012c677804"
@@ -315,9 +305,9 @@ version = "0.12.17"
 
 [[deps.NaNMath]]
 deps = ["OpenLibm_jll"]
-git-tree-sha1 = "0877504529a3e5c3343c6f8b4c0381e57e4387e4"
+git-tree-sha1 = "030ea22804ef91648f29b7ad3fc15fa49d0e6e71"
 uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
-version = "1.0.2"
+version = "1.0.3"
 
 [[deps.NetCDF_jll]]
 deps = ["Artifacts", "Bzip2_jll", "HDF5_jll", "JLLWrappers", "LibCURL_jll", "Libdl", "XML2_jll", "Zlib_jll", "Zstd_jll"]
@@ -341,31 +331,31 @@ version = "0.8.1+2"
 
 [[deps.OpenMPI_jll]]
 deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML", "Zlib_jll"]
-git-tree-sha1 = "a9de2f1fc98b92f8856c640bf4aec1ac9b2a0d86"
+git-tree-sha1 = "2dace87e14256edb1dd0724ab7ba831c779b96bd"
 uuid = "fe0851c0-eecd-5654-98d4-656369965a5c"
-version = "5.0.3+0"
+version = "5.0.6+0"
 
 [[deps.OpenSSL_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "3da7367955dcc5c54c1ba4d402ccdc09a1a3e046"
+git-tree-sha1 = "7493f61f55a6cce7325f197443aa80d32554ba10"
 uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95"
-version = "3.0.13+1"
+version = "3.0.15+3"
 
 [[deps.OpenSpecFun_jll]]
-deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1"
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "1346c9208249809840c91b26703912dff463d335"
 uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
-version = "0.5.5+0"
+version = "0.5.6+0"
 
 [[deps.OrderedCollections]]
-git-tree-sha1 = "dfdf5519f235516220579f949664f1bf44e741c5"
+git-tree-sha1 = "12f1439c4f986bb868acda6ea33ebc78e19b95ad"
 uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-version = "1.6.3"
+version = "1.7.0"
 
 [[deps.PCHIPInterpolation]]
-git-tree-sha1 = "0a19c7df8f154657088ac84b58347863e45c465d"
+git-tree-sha1 = "fa9c9839789b203e99580cd09c212df78f883562"
 uuid = "afe20452-48d1-4729-9a8b-50fb251f06cd"
-version = "0.2.0"
+version = "0.2.1"
 
     [deps.PCHIPInterpolation.extensions]
     PCHIPInterpolationRecipesBaseExt = "RecipesBase"
@@ -431,9 +421,9 @@ version = "1.10.0"
 
 [[deps.SpecialFunctions]]
 deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
-git-tree-sha1 = "2f5d4697f21388cbe1ff299430dd169ef97d7e14"
+git-tree-sha1 = "64cca0c26b4f31ba18f13f6c12af7c85f478cfde"
 uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
-version = "2.4.0"
+version = "2.5.0"
 
     [deps.SpecialFunctions.extensions]
     SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"
@@ -443,9 +433,9 @@ version = "2.4.0"
 
 [[deps.StaticArrays]]
 deps = ["LinearAlgebra", "PrecompileTools", "Random", "StaticArraysCore"]
-git-tree-sha1 = "9ae599cd7529cfce7fea36cf00a62cfc56f0f37c"
+git-tree-sha1 = "47091a0340a675c738b1304b58161f3b0839d454"
 uuid = "90137ffa-7385-5640-81b9-e52037218182"
-version = "1.9.4"
+version = "1.9.10"
 
     [deps.StaticArrays.extensions]
     StaticArraysChainRulesCoreExt = "ChainRulesCore"
@@ -456,9 +446,9 @@ version = "1.9.4"
     Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [[deps.StaticArraysCore]]
-git-tree-sha1 = "36b3d696ce6366023a0ea192b4cd442268995a0d"
+git-tree-sha1 = "192954ef1208c7019899fbf8049e717f92959682"
 uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
-version = "1.4.2"
+version = "1.4.3"
 
 [[deps.Statistics]]
 deps = ["LinearAlgebra", "SparseArrays"]
@@ -480,10 +470,6 @@ deps = ["ArgTools", "SHA"]
 uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"
 version = "1.10.0"
 
-[[deps.Test]]
-deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
-uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-
 [[deps.Thermodynamics]]
 deps = ["DocStringExtensions", "KernelAbstractions", "Random", "RootSolvers"]
 git-tree-sha1 = "090a50e507242bd6c85267645186260fe89a1cfe"
@@ -504,21 +490,21 @@ uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 
 [[deps.UnsafeAtomics]]
-git-tree-sha1 = "6331ac3440856ea1988316b46045303bef658278"
+git-tree-sha1 = "b13c4edda90890e5b04ba24e20a310fbe6f249ff"
 uuid = "013be700-e6cd-48c3-b4a1-df204f14c38f"
-version = "0.2.1"
+version = "0.3.0"
 
-[[deps.UnsafeAtomicsLLVM]]
-deps = ["LLVM", "UnsafeAtomics"]
-git-tree-sha1 = "d9f5962fecd5ccece07db1ff006fb0b5271bdfdd"
-uuid = "d80eeb9a-aca5-4d75-85e5-170c8b632249"
-version = "0.1.4"
+    [deps.UnsafeAtomics.extensions]
+    UnsafeAtomicsLLVM = ["LLVM"]
+
+    [deps.UnsafeAtomics.weakdeps]
+    LLVM = "929cbde3-209d-540e-8aea-75f648917ca0"
 
 [[deps.XML2_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Zlib_jll"]
-git-tree-sha1 = "52ff2af32e591541550bd753c0da8b9bc92bb9d9"
+git-tree-sha1 = "a2fccc6559132927d4c5dc183e3e01048c6dcbd6"
 uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a"
-version = "2.12.7+0"
+version = "2.13.5+0"
 
 [[deps.Zlib_jll]]
 deps = ["Libdl"]
@@ -527,20 +513,20 @@ version = "1.2.13+1"
 
 [[deps.Zstd_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "e678132f07ddb5bfa46857f0d7620fb9be675d3b"
+git-tree-sha1 = "622cf78670d067c738667aaa96c553430b65e269"
 uuid = "3161d3a3-bdf6-5164-811a-617609db77b4"
-version = "1.5.6+0"
+version = "1.5.7+0"
 
 [[deps.libaec_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "46bf7be2917b59b761247be3f317ddf75e50e997"
+git-tree-sha1 = "f5733a5a9047722470b95a81e1b172383971105c"
 uuid = "477f73a3-ac25-53e9-8cc3-50b2fa2566f0"
-version = "1.1.2+0"
+version = "1.1.3+0"
 
 [[deps.libblastrampoline_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
-version = "5.8.0+1"
+version = "5.11.0+0"
 
 [[deps.nghttp2_jll]]
 deps = ["Artifacts", "Libdl"]
diff --git a/Project.toml b/Project.toml
index 4e6942b..8f537b6 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "SOCRATESSingleColumnForcings"
 uuid = "efca6b66-9b98-11ed-1a32-7b7cdccd517a"
 authors = ["Jordan Benjamin"]
-version = "0.10.2"
+version = "0.10.3"
 
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
diff --git a/README.md b/README.md
index 81a34af..288405b 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 # SOCRATESSingleColumnForcings
 
-This repository includes scripts to take in SOCRATES flight data and create both 2D [lev,time] datasets and 1D [lev] columns of time-interpoloation functions to force the CliMa EDMF Turbulence-Convection single-column model.
+This repository includes scripts to take in SOCRATES flight data and create both 2D [lev,time] datasets and 1D [lev] columns of time-interpoloation functions to force the CliMA EDMF Turbulence-Convection single-column model.
 
 The profiles are created off the data used to force LES simulations by Atlas, 2020 (https://doi.org/10.1029/2020MS002205), some of her scripts are included in /Rachel_Atlas_Scripts.
 
@@ -27,4 +27,4 @@ The remainder of the properties are always taken from the ERA5 based Atlas input
 
 
 
-Once this is finalized, perhaps the relevant parts can be ported to `CliMa/AtmosphericProfilesLibrary.jl` (`CliMa/TurbulenceConvection.jl` as is doesn't access this repo)
+Once this is finalized, perhaps the relevant parts can be ported to `CliMA/AtmosphericProfilesLibrary.jl` (`CliMA/TurbulenceConvection.jl` as is doesn't access this repo)
diff --git a/src/SOCRATESSingleColumnForcings.jl b/src/SOCRATESSingleColumnForcings.jl
index de7f130..4067e4d 100644
--- a/src/SOCRATESSingleColumnForcings.jl
+++ b/src/SOCRATESSingleColumnForcings.jl
@@ -12,6 +12,8 @@ using Dates
 const FT = Float64
 const flight_numbers = [1, 9, 10, 11, 12, 13]
 const forcing_types = [:obs_data, :ERA5_data] # maybe change these to [:obs,:ERA5] later? would need to mirror in Cases.jl in TC.jl
+const TDPS = TD.Parameters.ThermodynamicsParameters
+const TDTS = TD.ThermodynamicState
 
 # Two cases with shallow cloud-topped boundary layers, RF12 and RF13, are run on a 192-level vertical grid.
 # The other four cases have clouds extending through deeper boundary layers; they are run on a 320-level vertical grid.
diff --git a/src/get_LES_reference_profiles.jl b/src/get_LES_reference_profiles.jl
index 24bf900..69c0b8d 100644
--- a/src/get_LES_reference_profiles.jl
+++ b/src/get_LES_reference_profiles.jl
@@ -10,14 +10,16 @@ SAM seems to hold ρ constant with time, so we can probably just rely on that
 """
 function get_LES_reference_profiles(
     flight_number::Int;
-    obs_or_ERA5 = "Obs"::Union{String, Symbol},
+    forcing_type::Symbol = :obs_data,
     new_zc::Union{Nothing, AbstractArray} = nothing,
     new_zf::Union{Nothing, AbstractArray} = nothing,
     # thermo_params,
 )
 
+    (forcing_type ∈ (:obs_data, :ERA5_data)) || error("forcing_type must be :obs_data or :ERA5_data")
+
     # initial conditions
-    data = open_atlas_les_input(flight_number)
+    data = open_atlas_les_input(flight_number, forcing_type; open_files = true)
 
     return_values = (:p_c, :p_f, :ρ_c, :ρ_f)
 
@@ -42,24 +44,15 @@ function get_LES_reference_profiles(
         error("You must provide either new_zc or new_zf, or both, but only providing new_zc is not allowed")
     end
 
-    # resolve forcing keyword
-    if obs_or_ERA5 ∈ ["Obs", :obs_data]
-        forcing = :obs_data
-        # data = data[(:obs_data, :ERA5_data)]
-        data = data[(:obs_data,)] # drop ERA if we're doing obs cause we don't need it (11 has no obs either i think)        
-    elseif obs_or_ERA5 ∈ ["ERA5", :ERA5_data]
-        forcing = :ERA5_data
-        data = data[(:ERA5_data,)] # drop obs if we're doing era5 cause we don't need it (11 has no obs either i think)        
-    else
-        if obs_or_ERA5 ∉ [:obs_data, :ERA5_data, "Obs", "ERA5"]
-            error("obs_or_ERA5 must be either \"Obs\"/[:obs_data] or \"ERA5\"/[:ERA5_data]")
-        else
-            forcing = obs_or_ERA5
-        end
-    end
+    data = data[(forcing_type,)]
 
 
-    LES_data = open_atlas_les_output(flight_number)[forcing]
+    LES_data = open_atlas_les_output(flight_number, forcing_type)[forcing_type]
+
+    if isnothing(LES_data)
+        error("No LES data found for flight $flight_number")
+    end
+
     z = LES_data["z"][:]
 
     p = LES_data["p"][:] .* 100.0 # Pressure variations in SAM are under a milibar, so we can use the 1D p variable rather than the 2D PRES variable
diff --git a/src/helper_functions.jl b/src/helper_functions.jl
index 4104af2..5ec4bd3 100644
--- a/src/helper_functions.jl
+++ b/src/helper_functions.jl
@@ -69,14 +69,14 @@ end
 
 Does this cause we don't have surface q values as of rn
 """
-function data_to_tsg(data; thermo_params)
+function data_to_tsg(data; thermo_params::TDPS)
 
     Tg = data["Tg"]
     pg = data["Ps"]
 
     # not sure what to do at surface, so assuming saturation at surface
     pvg = TD.saturation_vapor_pressure.(thermo_params, Tg, TD.Liquid())
-    molmass_ratio = TD.molmass_ratio(thermo_params)
+    molmass_ratio = TDP.molmass_ratio(thermo_params)
 
     qg = (1 / molmass_ratio) .* pvg ./ (pg .- pvg) #Total water mixing ratio at surface , assuming saturation
 
@@ -87,7 +87,7 @@ end
 """
     data_to_ts
 """
-function data_to_ts(data; do_combine_air_and_ground_data = false, thermo_params) # add type data is ncdataset
+function data_to_ts(data; do_combine_air_and_ground_data::Bool = false, thermo_params::TDPS) # add type data is ncdataset
 
     T = data["T"]
     q = data["q"]
@@ -107,18 +107,11 @@ function data_to_ts(data; do_combine_air_and_ground_data = false, thermo_params)
     return ts
 end
 
-
-function insert_sorted(vect, val; by = monotonic_checker, monotonic_rev = monotonic_rev)
-    # @show(vect,val)
-    index = searchsortedfirst(vect, val; by = monotonic_checker, rev = monotonic_rev) #find index at which to insert x
+function insert_sorted(vect, val; by = identity, rev = false)
+    index = searchsortedfirst(vect, val; by = by, rev = rev) #find index at which to insert x
     return insert!(vect, index, val) #insert x at index
 end
 
-# function insert_sorted(vect, val;by=monotonic_checker,monotonic_rev=monotonic_rev)
-#     index = searchsortedfirst(vect, val;  by=monotonic_checker, rev=monotonic_rev) #find index at which to insert x
-#     return insert!(vect, index, val) #insert x at index
-# end
-
 
 
 
@@ -127,15 +120,15 @@ end
 
 # function lev_to_z_from_LES_output_column(tsz, lesz, lesp; thermo_params, data, flight_number, forcing_type, interp_method = :Spline1D, interp_kwargs = Dict(:f_enhancement_factor=>1, :f_p_enhancement_factor=>1))
 function lev_to_z_from_LES_output_column(
-    tsz,
+    tsz::AbstractArray{TS},
     lesz,
     lesp;
-    thermo_params,
+    thermo_params::TDPS,
     data,
-    flight_number,
-    forcing_type,
-    interp_method = :Spline1D,
-)
+    flight_number::Int,
+    forcing_type::Symbol,
+    interp_method::Symbol = :Spline1D,
+) where {TS <: TDTS}
     # Load pressure from the thermodynamic state
     p_in = TD.air_pressure.(thermo_params, tsz)
     # Interpolate z from the LES output to the pressure levels of the thermodynamic state
@@ -152,11 +145,11 @@ We only have the forcing data at that scale so...
 function lev_to_z_from_LES_output(
     ts,
     tsg;
-    thermo_params,
+    thermo_params::TDPS,
     data,
-    assume_monotonic = false,
-    flight_number,
-    forcing_type,
+    assume_monotonic::Bool = false,
+    flight_number::Int,
+    forcing_type::Symbol,
     ground_indices = nothing,
 )
 
@@ -170,7 +163,7 @@ function lev_to_z_from_LES_output(
     Lt = size(ts, time_dim_num)
 
     if !assume_monotonic
-        LES_data = open_atlas_les_output(flight_number)[forcing_type]
+        LES_data = open_atlas_les_output(flight_number, forcing_type)[forcing_type]
         p_LES = LES_data["PRES"] # 2D,time varying
         z_LES = LES_data["z"] # 1D, constant
         # LES_min_z, LES_max_z = extrema(z_LES)
@@ -208,12 +201,9 @@ function lev_to_z_from_LES_output(
         # p_LES = pyinterp(t_in, t_les, p_LES) # i think you need to map this bc of the splines... but there's probably some way...
         p_LES = mapslices(x -> pyinterp(t_in, t_les, x, bc = "nearest", method = :Spline1D), p_LES; dims = 2) # apply to each row, use nearest interp but outside les time bounds is bogus
 
-        # for ts, tsz, interpolation is more annoying, maybe need to do in p,T,q separately and reconstitute?
-        # tsz = combine_air_and_ground_data(ts, tsg, ldn; data, reshape_ground = true, insert_location = :end) # here we just want to assume monotonic so we can pass those to this fcn (no need to merge bc our column fcn isn't handling...)
         tsz = ts
 
         # preallocate z
-        # z = zeros(Float64, size(tsz)...) # should be same size as ts
         s_tsz = collect(size(ts))
         s_tsz[ldn] += 1 # we just want to add a single slice of zeros for the ground -- these are all ocean cases so this should be fine for now...
         z = Array{Float64}(undef, s_tsz...) # should be same size as ts
@@ -278,7 +268,7 @@ function lev_to_z_from_LES_output(
 
 
             # Handle z's lower than LES Data (highest pressure to sfc) | use the thickness equation
-            new_z = lev_to_z_column(tsz_t[i_t_max_p:end]; thermo_params, data)
+            new_z = lev_to_z_column(tsz_t[i_t_max_p:end]; thermo_params)
             new_dz = new_z[2:end] .- new_z[1:(end - 1)] # get the dz from the thickness equation, but instead of going up from the ground, we're gonna flip it to go down from the last good z
             new_dz = cumsum(new_dz) # sum up our dz
             new_z = selectdim(z, tdn, i_t)[i_t_max_p] .+ new_dz
@@ -288,7 +278,7 @@ function lev_to_z_from_LES_output(
 
             # Handle z's higher than LES Data | use the thickness equation and add to the top of the LES data
             selectdim(z, tdn, i_t)[1:(i_t_min_p - 1)] =
-                lev_to_z_column(tsz_t[1:i_t_min_p]; thermo_params, data)[1:(end - 1)] .+ z[i_t_min_p] # go from start to top and add to existing top...
+                lev_to_z_column(tsz_t[1:i_t_min_p]; thermo_params)[1:(end - 1)] .+ z[i_t_min_p] # go from start to top and add to existing top...
 
 
             selectdim(z, tdn, i_t)[:] .-= selectdim(z, tdn, i_t)[index] # subtract out the ground value
@@ -312,15 +302,13 @@ tsz should be a one dimensional array consising of [ts..., tg]
 
 # to do -- add capability to use precomputed indices (insert_location)
 """
-function lev_to_z_column(tsz; thermo_params, data = data)
+function lev_to_z_column(tsz; thermo_params::TDPS)
 
     ts = tsz[1:(end - 1)] # need to make it a vector I guess... (not sure if this screws wit output shape)
     tsg = tsz[end]
     R_d = TDP.R_d(thermo_params)
     grav = TDP.grav(thermo_params)
 
-    # dimnames    = NC.dimnames(data["T"]) # use this as default cause calculating ts doesn't maintain dim labellings
-    # lev_dim_num = findfirst(x->x=="lev",dimnames)
     L = length(ts)
 
     index = searchsortedfirst(ts, tsg; by = x -> TD.air_pressure(thermo_params, x), rev = false) # find where the ground value would be inserted...
@@ -350,9 +338,9 @@ end
 
 TODO: document
 """
-function lev_to_z(p::FT, T::FT, q::FT, pg::FT, Tg::FT, qg::FT; thermo_params, data) where {FT <: Real}
+function lev_to_z(p::FT, T::FT, q::FT, pg::FT, Tg::FT, qg::FT; thermo_params::TDPS, data) where {FT <: Real}
     ts = TD.PhaseEquil_pTq.(thermo_params, p, T, q)
-    tsg = TD.PhaseEquil_pTq.(thermo_params, pg, Tg, qtg)
+    tsg = TD.PhaseEquil_pTq.(thermo_params, pg, Tg, qg)
     return lev_to_z(ts, tsg; data = data, thermo_params)
 end
 
@@ -365,7 +353,13 @@ tsg is thermodynamic state for ground
 
 if assume monotonic, everything should already be in the right order and we can use the vectorized version, otherwise we will use lev_to_z column applied column by column w/ mapslices
 """
-function lev_to_z(ts, tsg; thermo_params, data, assume_monotonic = false)
+function lev_to_z(
+    ts::AbstractArray{TS},
+    tsg::AbstractArray{TS};
+    thermo_params::TDPS,
+    data,
+    assume_monotonic::Bool = false,
+) where {TS <: TDTS}
 
     dimnames = NC.dimnames(data["T"]) # use this as default cause calculating ts doesn't maintain dim labellings
     lev_dim_num = findfirst(x -> x == "lev", dimnames)
@@ -374,7 +368,7 @@ function lev_to_z(ts, tsg; thermo_params, data, assume_monotonic = false)
 
     if !assume_monotonic
         tsz = combine_air_and_ground_data(ts, tsg, ldn; data, reshape_ground = true, insert_location = :end) # here we just want to assume monotonic so we can pass those to this fcn
-        z = mapslices(x -> lev_to_z_column(x; thermo_params, data), tsz; dims = ldn) # need to make a stack cause that's all mapslices can take...
+        z = mapslices(x -> lev_to_z_column(x; thermo_params), tsz; dims = ldn) # need to make a stack cause that's all mapslices can take...
     else
 
         R_d = TDP.R_d(thermo_params) # TD.Parameters.R_d(thermo_params)
@@ -408,7 +402,7 @@ function lev_to_z(ts, tsg; thermo_params, data, assume_monotonic = false)
     return z
 end
 
-function z_from_data(data; thermo_params)
+function z_from_data(data; thermo_params::TDPS)
     ts = data_to_ts(data; thermo_params, do_combine_air_and_ground_data = false)
     tsg = data_to_tsg(data; thermo_params)
     return lev_to_z(ts, tsg; thermo_params, data)
@@ -420,7 +414,13 @@ end
 
 Get the indices where the ground tsg would fit into the array ts...
 """
-function get_ground_insertion_indices(ts, tsg, concat_dim; thermo_params, data = data)
+function get_ground_insertion_indices(
+    ts::AbstractArray{TS},
+    tsg::AbstractArray{TS},
+    concat_dim::Union{Int, String};
+    thermo_params::TDPS,
+    data,
+) where {TS <: TDTS}
     function mapslice_func(vect; thermo_params = thermo_params, by = x -> TD.air_pressure(thermo_params, x))
         vardata = vect[1:(end - 1)]
         vardatag = vect[end]
@@ -455,12 +455,12 @@ assume_monotonic : assume that the ground value is actually below everything in
 function combine_air_and_ground_data(
     var,
     varg,
-    concat_dim;
+    concat_dim::Union{Int, String};
     data = nothing,
-    reshape_ground = true,
-    insert_location = :end,
+    reshape_ground::Bool = true,
+    insert_location::Union{Symbol, AbstractArray, Function} = :end,
 )
-    # if data is a string, read the data out from data (creates data `vardata` from `var` whether var is string or already is data)
+    # if var is a string, read the data out from data (creates data `vardata` from `var` whether var is string or already is data)
     vardata = isa(var, String) ? data[var] : var
     vardatag = isa(varg, String) ? data[varg] : varg
     concat_dim = isa(concat_dim, String) ? get_dim_num(concat_dim, vardata) : concat_dim # string to numbers
@@ -549,25 +549,37 @@ end
 
 get the dimension number of dim from nc_data
 """
-function get_dim_num(dim, nc_data = nothing)
-
-    # convert interp_dim to a number stored in interp_dim_num
-    if isa(dim, Number) # already a string, just returns...
-        dim_num = dim
-    elseif isa(dim, String)
-        if isa(nc_data, NC.CFVariable) # allow finding the number from an ncdataset and a string
-            dimnames = NC.dimnames(nc_data)
-            dim_num = findfirst(x -> x == dim, dimnames)
-        elseif isa(nc_data, NC.NCDataset)
-            @warn("dimension number for a dataset is not well defined, use a speciifc NC.CFVariable instead")
-        elseif isa(nc_data, AbstractArray)
-            error("cannot find dimension $(dim) in unlabeled data nc_data, pass in a labeled NCDataset instead...")
-        else
-            error("unsupported input type for nc_data $(typeof(nc_data))")
-        end
-    end
+get_dim_num(dim::Number, nc_data) = dim
+function get_dim_num(dim::String, nc_data::NC.CFVariable)
+    dimnames = NC.dimnames(nc_data)
+    dim_num = findfirst(x -> x == dim, dimnames)
     return dim_num
 end
+get_dim_num(dim::String, nc_data::NC.NCDataset) =
+    error("dimension number for a dataset is not well defined, use a speciifc NC.CFVariable instead")
+get_dim_num(dim::String, nc_data::AbstractArray) =
+    error("cannot find dimension $(dim) in unlabeled data nc_data, pass in a labeled NCDataset instead...")
+get_dim_num(dim::String, nc_data) = error("unsupported input type for nc_data $(typeof(nc_data))")
+
+# function get_dim_num(dim, nc_data = nothing)
+
+#     # convert interp_dim to a number stored in interp_dim_num
+#     if isa(dim, Number) # already a string, just returns...
+#         dim_num = dim
+#     elseif isa(dim, String)
+#         if isa(nc_data, NC.CFVariable) # allow finding the number from an ncdataset and a string
+#             dimnames = NC.dimnames(nc_data)
+#             dim_num = findfirst(x -> x == dim, dimnames)
+#         elseif isa(nc_data, NC.NCDataset)
+#             @warn("dimension number for a dataset is not well defined, use a speciifc NC.CFVariable instead")
+#         elseif isa(nc_data, AbstractArray)
+#             error("cannot find dimension $(dim) in unlabeled data nc_data, pass in a labeled NCDataset instead...")
+#         else
+#             error("unsupported input type for nc_data $(typeof(nc_data))")
+#         end
+#     end
+#     return dim_num
+# end
 
 
 
@@ -592,16 +604,16 @@ To Do : decide types
 """
 function interp_along_dim(
     var,
-    interp_dim,
+    interp_dim::Union{String, Int},
     interp_dim_in;
     interp_dim_out = nothing,
     data = nothing,
-    data_func = nothing,
-    interp_dim_in_is_full_array = true,
-    reshape_ground = true,
-    verbose = false,
-    interp_method = :Spline1D,
-    interp_kwargs = Dict{Symbol, Any}(),
+    data_func::Union{Function, Nothing} = nothing,
+    interp_dim_in_is_full_array::Bool = true,
+    reshape_ground::Bool = true,
+    verbose::Bool = false,
+    interp_method::Symbol = :Spline1D,
+    interp_kwargs::Dict = Dict{Symbol, Any}(),
 )
     # would use kwargs but doesn't play nice w/ ODE solver for some reason... instead we get out the parameters we want explicitly and pass them all the time (splatting gives a union typle type object that apparently can't be handled?)
     f_enhancement_factor = get(interp_kwargs, :f_enhancement_factor, 1) # default to 1.0
@@ -627,32 +639,50 @@ function interp_along_dim(
     if !interp_dim_in_is_full_array
         if isnothing(interp_dim_out)
             return mapslices(
-                d ->
-                    dd -> pyinterp(
-                        dd,
-                        interp_dim_in,
-                        d;
-                        method = interp_method,
-                        f_enhancement_factor = f_enhancement_factor,
-                        f_p_enhancement_factor = f_p_enhancement_factor,
-                        bc = bc,
-                        k = k,
-                    ),
+                let interp_dim_in = interp_dim_in,
+                    interp_method = interp_method,
+                    f_enhancement_factor = f_enhancement_factor,
+                    f_p_enhancement_factor = f_p_enhancement_factor,
+                    bc = bc,
+                    k = k
+                    # let block for performance of captured variables
+                    d -> let d = d
+                        dd -> pyinterp(
+                            dd,
+                            interp_dim_in,
+                            d;
+                            method = interp_method,
+                            f_enhancement_factor = f_enhancement_factor,
+                            f_p_enhancement_factor = f_p_enhancement_factor,
+                            bc = bc,
+                            k = k,
+                        )
+                    end
+                end,
                 vardata,
                 dims = [interp_dim_num],
             ) # will return a lambda fcn that can be evaluated along that dimensoin
         else
             return mapslices(
-                d -> pyinterp(
-                    interp_dim_out,
-                    interp_dim_in,
-                    d;
-                    method = interp_method,
+                let interp_dim_out = interp_dim_out,
+                    interp_dim_in = interp_dim_in,
+                    interp_method = interp_method,
                     f_enhancement_factor = f_enhancement_factor,
                     f_p_enhancement_factor = f_p_enhancement_factor,
                     bc = bc,
-                    k = k,
-                ),
+                    k = k
+                    # let block for performance of captured variables
+                    d -> pyinterp(
+                        interp_dim_out,
+                        interp_dim_in,
+                        d;
+                        method = interp_method,
+                        f_enhancement_factor = f_enhancement_factor,
+                        f_p_enhancement_factor = f_p_enhancement_factor,
+                        bc = bc,
+                        k = k,
+                    )
+                end,
                 vardata,
                 dims = [interp_dim_num],
             ) # lambda fcn will evaluate
@@ -664,17 +694,25 @@ function interp_along_dim(
         if isnothing(interp_dim_out)
             return dropdims(
                 mapslices(
-                    d ->
-                        dd -> pyinterp(
-                            dd,
-                            d[:, 1],
-                            d[:, 2];
-                            method = interp_method,
-                            f_enhancement_factor = f_enhancement_factor,
-                            f_p_enhancement_factor = f_p_enhancement_factor,
-                            bc = bc,
-                            k = k,
-                        ),
+                    let interp_method = interp_method,
+                        f_enhancement_factor = f_enhancement_factor,
+                        f_p_enhancement_factor = f_p_enhancement_factor,
+                        bc = bc,
+                        k = k
+                        # let block for performance of captured variables
+                        d -> let d = d
+                            dd -> pyinterp(
+                                dd,
+                                d[:, 1],
+                                d[:, 2];
+                                method = interp_method,
+                                f_enhancement_factor = f_enhancement_factor,
+                                f_p_enhancement_factor = f_p_enhancement_factor,
+                                bc = bc,
+                                k = k,
+                            )
+                        end
+                    end,
                     _input,
                     dims = [interp_dim_num, catd],
                 );
@@ -683,16 +721,24 @@ function interp_along_dim(
         else
             return dropdims(
                 mapslices(
-                    d -> pyinterp(
-                        interp_dim_out,
-                        d[:, 1],
-                        d[:, 2];
-                        method = interp_method,
+                    let interp_dim_out = interp_dim_out,
+                        interp_method = interp_method,
                         f_enhancement_factor = f_enhancement_factor,
                         f_p_enhancement_factor = f_p_enhancement_factor,
                         bc = bc,
-                        k = k,
-                    ),
+                        k = k
+                        # let block for performance of captured variables
+                        d -> pyinterp(
+                            interp_dim_out,
+                            d[:, 1],
+                            d[:, 2];
+                            method = interp_method,
+                            f_enhancement_factor = f_enhancement_factor,
+                            f_p_enhancement_factor = f_p_enhancement_factor,
+                            bc = bc,
+                            k = k,
+                        )
+                    end,
                     _input,
                     dims = [interp_dim_num, catd],
                 );
@@ -734,12 +780,13 @@ if coord_new is nothing, then will return functions...
 function var_to_new_coord(
     var,
     coord_in,
-    interp_dim;
+    interp_dim::Union{String, Number},
+    ;
     coord_new = nothing,
     data = nothing,
-    data_func = nothing,
-    interp_method = :Spline1D,
-    interp_kwargs = Dict{Symbol, Any}(),
+    data_func::Union{Function, Nothing} = nothing,
+    interp_method::Symbol = :Spline1D,
+    interp_kwargs::Dict = Dict{Symbol, Any}(),
 )
     vardata = isa(var, String) ? data[var] : var
     if ~isnothing(data)
@@ -772,19 +819,19 @@ to vectorize properly over z_new, it should be the same shape as vardata+vardata
 function get_data_new_z_t(
     var,
     z_new,
-    z_dim,
-    time_dim,
-    flight_number;
-    thermo_params,
+    z_dim::Union{String, Number},
+    time_dim::Union{String, Number},
+    flight_number::Int;
+    thermo_params::TDPS,
     varg = nothing,
     z_old = nothing,
     t_old = nothing,
     data = nothing,
-    initial_condition = false,
-    assume_monotonic = false,
-    interp_method = :Spline1D,
-    Spline1D_interp_kwargs = Dict{Symbol, Any}(),
-    pchip_interp_kwargs = Dict{Symbol, Any}(),
+    initial_condition::Bool = false,
+    assume_monotonic::Bool = false,
+    interp_method::Symbol = :Spline1D,
+    Spline1D_interp_kwargs::Dict = Dict{Symbol, Any}(),
+    pchip_interp_kwargs::Dict = Dict{Symbol, Any}(),
     ground_indices = :end,
 )
 
@@ -935,7 +982,7 @@ function calc_qg_extrapolate_pq(pg, p, q; interp_method = :Spline1D, interp_kawr
     return qg
 end
 
-function calc_qg_from_pgTg(pg, Tg, thermo_params)
+function calc_qg_from_pgTg(pg, Tg, thermo_params::TDPS)
     ρg = TD.air_density(thermo_params, Tg, pg) # original T?
     qg = TD.q_vap_saturation_generic(thermo_params, Tg, ρg, TD.Liquid()) # surface specific humidity over liquid
     return qg
diff --git a/src/les_reader_helper.jl b/src/les_reader_helper.jl
index e99f7ac..fc3195a 100644
--- a/src/les_reader_helper.jl
+++ b/src/les_reader_helper.jl
@@ -6,17 +6,6 @@ Read LES output file instead of the forcing input to set things
 
 
 
-# function read_LES_output(
-#     flight_number::Int;
-#     forcing_type::Symbol = :obs_data,
-# )
-
-#     LES_data = open_atlas_les_output(flight_number)[forcing_type]
-
-# end
-
-
-
 
 """
 This function is for reading things from LES since they don't have the same time setup and already have a z (which should match our desired output)
@@ -25,26 +14,26 @@ LES data only has dimensions (time, z), no lev etc, but we keepthe syntax the sa
 function get_data_new_z_t_LES(
     var,
     z_new, # you'd htink this would be the same as our desired output z, but RF09 was run on a taller grid for some reason
-    z_dim,
-    time_dim,
-    flight_number;
-    thermo_params,
+    z_dim::Union{Int, String},
+    time_dim::Union{Int, String},
+    flight_number::Int,
+    forcing_type::Symbol;
     varg = nothing,
     z_old = nothing,
     t_old = nothing,
     data = nothing,
-    initial_condition = false,
-    assume_monotonic = false,
-    interp_method = :Spline1D,
-    Spline1D_interp_kwargs = Dict{Symbol, Any}(:bc => "extrapolate"), # default to extrapolate bc RF09 was run on a different grid for some reason, we're not necessarily guaranteed to have the same z
-    pchip_interp_kwargs = Dict{Symbol, Any}(:bc => "extrapolate"),
+    initial_condition::Bool = false,
+    assume_monotonic::Bool = false,
+    interp_method::Symbol = :Spline1D,
+    Spline1D_interp_kwargs::Dict = Dict{Symbol, Any}(:bc => "extrapolate"), # default to extrapolate bc RF09 was run on a different grid for some reason, we're not necessarily guaranteed to have the same z
+    pchip_interp_kwargs::Dict = Dict{Symbol, Any}(:bc => "extrapolate"),
     ground_indices = :end,
 )
 
 
 
     if isa(var, String) && isnothing(data)
-        data = open_atlas_les_output(flight_number)[forcing_type]
+        data = open_atlas_les_output(flight_number, forcing_type)[forcing_type]
     end
 
     # get the data and dimensions we're working on,
diff --git a/src/open_atlas_les_inputs.jl b/src/open_atlas_les_inputs.jl
index f68cdc9..696699f 100644
--- a/src/open_atlas_les_inputs.jl
+++ b/src/open_atlas_les_inputs.jl
@@ -3,7 +3,52 @@ open_atlas_les_input(flight_number::Int)
 
 opens the files downloaded in download_atlas_les_profiles.jl
 """
-function open_atlas_les_input(flight_number::Int)
+function open_atlas_les_input(
+    flight_number::Int,
+    forcing_type::Symbol;
+    open_files::Bool = true,
+    include_grid::Bool = true,
+)
+    FT = Float64 # idk how to pass on a type here without necessarily having to give a variable...
+    atlas_dir = joinpath(dirname(@__DIR__), "Data", "Atlas_LES_Profiles", "Input_Data") # doesn't seem to work to use @__DIR__ directly as a variable
+    RF_num = "RF" * string(flight_number, pad = 2)
+
+    if forcing_type == :obs_data
+        data_filename = joinpath(atlas_dir, RF_num * "_obs-based_SAM_input.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_obs-based_SAM_input.nc
+    elseif forcing_type == :ERA5_data
+        data_filename = joinpath(atlas_dir, RF_num * "_ERA5-based_SAM_input_mar18_2022.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_ERA5-based_SAM_input_mar18_2022.nc
+    else
+        error("forcing_type must be :obs_data or :ERA5_data")
+    end
+
+
+    data = isfile(data_filename) ? (open_files ? NC.Dataset(data_filename, "r") : data_filename) : nothing
+
+    if include_grid
+        grid_filename = joinpath(atlas_dir, RF_num * "_grd.txt")
+        grid_data = isfile(grid_filename) ? (open_files ? vec(readdlm(grid_filename, FT)) : grid_filename) : nothing
+        return NamedTuple{(forcing_type, :grid_data)}((data, grid_data))
+    else
+        return NamedTuple{(forcing_type,)}((data,))
+    end
+end
+
+
+function open_atlas_les_grid(flight_number::Int; open_files::Bool = true)
+    FT = Float64 # idk how to pass on a type here without necessarily having to give a variable...
+    atlas_dir = joinpath(dirname(@__DIR__), "Data", "Atlas_LES_Profiles", "Input_Data") # doesn't seem to work to use @__DIR__ directly as a variable
+    RF_num = "RF" * string(flight_number, pad = 2)
+    grid_filename = joinpath(atlas_dir, RF_num * "_grd.txt")
+
+    grid_data = isfile(grid_filename) ? (open_files ? vec(readdlm(grid_filename, FT)) : grid_filename) : nothing
+
+    return (; grid_data)
+end
+
+
+function open_atlas_les_input(flight_number::Int; open_files::Bool = true)
+
+
     FT = Float64 # idk how to pass on a type here without necessarily having to give a variable...
     atlas_dir = joinpath(dirname(@__DIR__), "Data", "Atlas_LES_Profiles", "Input_Data") # doesn't seem to work to use @__DIR__ directly as a variable
     RF_num = "RF" * string(flight_number, pad = 2)
@@ -13,30 +58,12 @@ function open_atlas_les_input(flight_number::Int)
 
     # @show(obs_filename, ERA5_filename, grid_filename)
 
-    local obs_data, ERA5_data, grid_data # initialize cause try catch scope is closed
+    # local obs_data, ERA5_data, grid_data # initialize cause try catch scope is closed
     # can't use do blocks here cause will close the files...
-    try  # obs
-        # obs_data = NC.Dataset(obs_filename,"r") do ds; ds; end
-        obs_data = NC.Dataset(obs_filename, "r")
-    catch e
-        @warn e
-        obs_data = nothing
-    end
 
-    try  # ERA5
-        ERA5_data = NC.Dataset(ERA5_filename, "r")
-    catch e
-        @warn e
-        ERA5_data = nothing
-    end
-
-    try  # grid
-        grid_data = vec(readdlm(grid_filename, FT)) # is a txt file...
-    catch e
-        @warn e
-        grid_data = nothing
-    end
+    obs_data = isfile(obs_filename) ? (open_files ? NC.Dataset(obs_filename, "r") : obs_filename) : nothing
+    ERA5_data = isfile(ERA5_filename) ? (open_files ? NC.Dataset(ERA5_filename, "r") : ERA5_filename) : nothing
+    grid_data = isfile(grid_filename) ? (open_files ? vec(readdlm(grid_filename, FT)) : grid_filename) : nothing
 
     return (; obs_data = obs_data, ERA5_data = ERA5_data, grid_data = grid_data)
-
 end
diff --git a/src/open_atlas_les_outputs.jl b/src/open_atlas_les_outputs.jl
index df861e1..3161ab7 100644
--- a/src/open_atlas_les_outputs.jl
+++ b/src/open_atlas_les_outputs.jl
@@ -21,52 +21,72 @@ SOCRATES_flight_observations_Box_links = Dict( # The raw observational data from
 
 
 """
-open_atlas_les_output(flight_number::Int)
+open_atlas_les_output(flight_number::Int, forcing_type::Symbol; open_files::Bool = true, include_grid::Bool = true)
 
 opens the files downloaded in download_atlas_les_profiles.jl
 """
-function open_atlas_les_output(flight_number::Int)
+function open_atlas_les_output(
+    flight_number::Int,
+    forcing_type::Symbol;
+    open_files::Bool = true,
+    include_grid::Bool = true,
+)
     FT = Float64 # idk how to pass on a type here without necessarily having to give a variable...
     atlas_dir = joinpath(dirname(@__DIR__), "Data", "Atlas_LES_Profiles", "Output_Data") # doesn't seem to work to use @__DIR__ directly as a variable
     RF_num = "RF" * string(flight_number, pad = 2)
-    obs_filename = joinpath(atlas_dir, RF_num * "_Obs_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_obs-based_SAM_input.nc
-    ERA5_filename = joinpath(atlas_dir, RF_num * "_ERA5_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_ERA5-based_SAM_input_mar18_2022.nc
-    grid_filename = joinpath(atlas_dir, RF_num * "_grd.txt")
 
-    # @show(obs_filename, ERA5_filename, grid_filename)
+    if forcing_type == :obs_data
+        data_filename = joinpath(atlas_dir, RF_num * "_Obs_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_obs-based_SAM_input.nc
+    elseif forcing_type == :ERA5_data
+        data_filename = joinpath(atlas_dir, RF_num * "_ERA5_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_ERA5-based_SAM_input_mar18_2022.nc
+    else
+        error("forcing_type must be :obs_data or :ERA5_data")
+    end
+
 
     # check if file exists and if not, download it
-    if !isfile(obs_filename)
-        # download(SOCRATES_flight_observations_Box_links[flight_number], obs_filename) # box link
-        download_atlas_les_outputs(; cases = [flight_number]) # Atlas website
-    end
-    if !isfile(ERA5_filename)
-        # download(SOCRATES_flight_observations_Box_links[flight_number], ERA5_filename) # box link
-        download_atlas_les_outputs(; cases = [flight_number]) # Atlas website
+    # The data is quite large so we'll try to load it from Box
+    if !isfile(data_filename)
+        download_atlas_les_outputs(; cases = [flight_number], forcing_type = forcing_type) # Atlas website
     end
 
 
-    # The data is quite large so we'll try to load it from Box
+    data = isfile(data_filename) ? (open_files ? NC.Dataset(data_filename, "r") : data_filename) : nothing
 
-    local obs_data, ERA5_data, grid_data # initialize cause try catch scope is closed
-    # can't use do blocks here cause will close the files...
-    try  # obs
-        # obs_data = NC.Dataset(obs_filename,"r") do ds; ds; end
-        obs_data = NC.Dataset(obs_filename, "r")
-        grid_data = obs_data["z"][:] # read here cause no grid file
-    catch e
-        @warn e
-        obs_data = nothing
+    if include_grid
+        grid_filename = joinpath(atlas_dir, RF_num * "_grd.txt")
+        grid_data = isfile(grid_filename) ? (open_files ? vec(readdlm(grid_filename, FT)) : grid_filename) : nothing
+        return NamedTuple{(forcing_type, :grid_data)}((data, grid_data))
+    else
+        return NamedTuple{(forcing_type,)}((data,))
     end
+end
+
 
-    try  # ERA5
-        ERA5_data = NC.Dataset(ERA5_filename, "r")
-        grid_data = ERA5_data["z"][:] # read here cause no grid file
-    catch e
-        @warn e
-        ERA5_data = nothing
+function open_atlas_les_output(flight_number::Int; open_files::Bool = true, include_grid::Bool = true)
+    FT = Float64 # idk how to pass on a type here without necessarily having to give a variable...
+    atlas_dir = joinpath(dirname(@__DIR__), "Data", "Atlas_LES_Profiles", "Output_Data") # doesn't seem to work to use @__DIR__ directly as a variable
+    RF_num = "RF" * string(flight_number, pad = 2)
+    obs_filename = joinpath(atlas_dir, RF_num * "_Obs_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_obs-based_SAM_input.nc
+    ERA5_filename = joinpath(atlas_dir, RF_num * "_ERA5_" * "SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc") # e.g. https://atmos.uw.edu/~ratlas/RF12_ERA5-based_SAM_input_mar18_2022.nc
+
+    # check if file exists and if not, download it
+    # The data is quite large so we'll try to load it from Box
+    if !isfile(obs_filename)
+        download_atlas_les_outputs(; cases = [flight_number], forcing_type = :obs_data) # Atlas website
+    end
+    if !isfile(ERA5_filename)
+        download_atlas_les_outputs(; cases = [flight_number], forcing_type = :ERA5_data) # Atlas website
     end
 
-    return (; obs_data = obs_data, ERA5_data = ERA5_data, grid_data = grid_data)
+    obs_data = isfile(obs_filename) ? (open_files ? NC.Dataset(obs_filename, "r") : obs_filename) : nothing
+    ERA5_data = isfile(ERA5_filename) ? (open_files ? NC.Dataset(ERA5_filename, "r") : ERA5_filename) : nothing
 
+    if include_grid
+        grid_filename = joinpath(atlas_dir, RF_num * "_grd.txt")
+        grid_data = isfile(grid_filename) ? (open_files ? vec(readdlm(grid_filename, FT)) : grid_filename) : nothing
+        return (; obs_data, ERA5_data, grid_data)
+    else
+        return (; obs_data, ERA5_data)
+    end
 end
diff --git a/src/process_case.jl b/src/process_case.jl
index 98345e7..995f793 100644
--- a/src/process_case.jl
+++ b/src/process_case.jl
@@ -2,7 +2,7 @@
 """
     process_case(
         flight_number::Int;
-        obs_or_ERA5 = "Obs"::Union{String,Symbol},
+        forcing_type::Symbol = :obs_data,
         new_z::Union{Nothing,AbstractArray}=nothing,
         initial_condition::Bool=false,
         thermo_params,
@@ -13,26 +13,30 @@ Processes the flight data for that case
 If new_z is not specified, will use Rachel Atlas default grid
 If initial_condition is false, returns the data at time 0, if true, returns full spline interpolations over the time dimension
 
-Some things are always forced by ERA5, otherwise we pull from whatever obs_or_ERA5 specifies... (list which is which?)
+Some things are always forced by ERA5, otherwise we pull from whatever forcing_type specifies... (list which is which?)
 """
 function process_case(
     flight_number::Int;
-    obs_or_ERA5 = "Obs"::Union{String, Symbol},
+    forcing_type::Symbol = :obs_data,
     new_z::Union{Nothing, AbstractArray, NamedTuple} = nothing,
     initial_condition::Bool = false,
-    thermo_params,
-    surface = nothing,
-    use_LES_output_for_z = false,
-    return_old_z = false,
+    thermo_params::TDPS,
+    surface::Union{String, Nothing} = nothing,
+    use_LES_output_for_z::Bool = false,
+    return_old_z::Bool = false,
+    fail_on_missing_data::Bool = true,
 )
 
     # initial conditions
-    data = open_atlas_les_input(flight_number)
+    (forcing_type ∈ (:obs_data, :ERA5_data)) || error("forcing_type must be :obs_data or :ERA5_data")
+
+
+    data = open_atlas_les_input(flight_number, forcing_type) # it's no longer our understanding that's there any need for ERA5 in obs and vice versa so just load the one you need
 
     # get the new grid we want from the atlas les grid file
     return_values =
         (:dTdt_hadv, :H_nudge, :dqtdt_hadv, :qt_nudge, :subsidence, :u_nudge, :v_nudge, :ug_nudge, :vg_nudge, :dTdt_rad)
-    if isnothing(new_z)
+    if new_z isa Nothing # better than isnothing() for JET.jl
         new_z = data[:grid_data]
         # named tuple repeated for each in return values
         new_z = NamedTuple{return_values}((new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z))
@@ -40,71 +44,69 @@ function process_case(
         new_z = NamedTuple{return_values}((new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z, new_z))
     end
 
-    # resolve forcing keyword
-    if obs_or_ERA5 ∈ ["Obs", :obs_data]
-        forcing = :obs_data
-        # data = data[(:obs_data, :ERA5_data)]
-        data = data[(:obs_data,)] # drop ERA if we're doing obs cause we don't need it (11 has no obs either i think)        
-    elseif obs_or_ERA5 ∈ ["ERA5", :ERA5_data]
-        forcing = :ERA5_data
-        data = data[(:ERA5_data,)] # drop obs if we're doing era5 cause we don't need it (11 has no obs either i think)        
-    else
-        if obs_or_ERA5 ∉ [:obs_data, :ERA5_data, "Obs", "ERA5"]
-            error("obs_or_ERA5 must be either \"Obs\"/[:obs_data] or \"ERA5\"/[:ERA5_data]")
-        else
-            forcing = obs_or_ERA5
-        end
-    end
+    # (new_z isa NamedTuple) || error("") # To help union split
+
+    data = data[(forcing_type,)] # drop the other forcing_type type and grid, keeps as a named tuple
 
     # specify our action dimensions
-    z_dim_num = get_dim_num("lev", data[forcing]["T"])
-    time_dim_num = get_dim_num("time", data[forcing]["T"])
+    z_dim_num = get_dim_num("lev", data[forcing_type]["T"])
+    time_dim_num = get_dim_num("time", data[forcing_type]["T"])
 
-    # We use map here a lot to map over all forcings in our data, but that could maybe be deprecated if we stop carrying it around as a named tuple
+    # We use map here a lot to map over all forcing_types in our data, but that could maybe be deprecated if we stop carrying it around as a named tuple
 
     ## For surface values, adjust to the time period of interest and return only the surface values, these are called in TC.jl
     if ~isnothing(surface)
-        initial_ind = get_initial_ind(data[forcing], flight_number) # should the reference be the first timestep? or what is the reference meant to be...
+        initial_ind = get_initial_ind(data[forcing_type], flight_number) # should the reference be the first timestep? or what is the reference meant to be...
         summary_file = joinpath(dirname(@__DIR__), "Data", "SOCRATES_summary.nc")
         SOCRATES_summary = NC.Dataset(summary_file, "r")
         flight_ind = findfirst(SOCRATES_summary["flight_number"][:] .== flight_number)
         Tg_offset = SOCRATES_summary[:deltaT][flight_ind]  # I think this is backwards in table 2 in the paper... is really T_2m - SST as in Section 3
         if surface ∈ ["reference_state", "reference", "ref"]  # we just want the surface reference state and we'll just return that
-            Tg = data[forcing]["Tg"][:][initial_ind] + Tg_offset # might have to drop lon,lat dims or sum
-            pg = data[forcing]["Ps"][:][initial_ind]
+            Tg = data[forcing_type]["Tg"][:][initial_ind] + Tg_offset # might have to drop lon,lat dims or sum
+            pg = data[forcing_type]["Ps"][:][initial_ind]
 
             if Tg_offset < 0  # SST/T_orig > Tg, assume SST sets qg at ground level and serves as a source
                 qg = calc_qg_from_pgTg(pg, Tg, thermo_params)
             else # SST/T_orig < Tg, stable boundary layer, assume latent air RH controls things... not SST
-                p = vec(data[forcing]["lev"])[:]
-                q = vec(selectdim(data[forcing]["q"], time_dim_num, initial_ind))[:] # select our q value subset along the time dimension
+                p = vec(data[forcing_type]["lev"])[:]
+                q = vec(selectdim(data[forcing_type]["q"], time_dim_num, initial_ind))[:] # select our q value subset along the time dimension
                 q = q ./ (1 .+ q) # mixing ratio to specific humidity
                 qg = calc_qg_extrapolate_pq([pg], p, q)
                 qg = collect(qg)[]  # Thermodynamics 0.10.2 returns a tuple rather than scalar, so this can collapse to scalar in either 0.10.1<= or 0.10.2>=
             end
             return TD.PhaseEquil_pTq(thermo_params, pg, Tg, qg)
         elseif surface ∈ ["surface_conditions", "conditions", "cond"]
-            pg = vec(data[forcing]["Ps"])[:][initial_ind:end]
-            Tg_orig = vec(data[forcing]["Tg"])[:][initial_ind:end] # SST
+            pg = vec(data[forcing_type]["Ps"])[:][initial_ind:end]
+            Tg_orig = vec(data[forcing_type]["Tg"])[:][initial_ind:end] # SST
             Tg = Tg_orig .+ Tg_offset # might have to drop lon,lat dims or sum
             # before we were extrapolating to surface to get qg which looks ok at first but after ts 1, the LES diverges, maybe it's supposed to be going towards Tg SST
             if Tg_offset < 0  # SST > Tg, assume SST sets qg at ground level going forward and serves as a source (so use full Tg not Tg_orig)
                 qg = calc_qg_from_pgTg.(pg, Tg, thermo_params)  # surface specific humidity over liquid
             else # SST < Tg, so stable boundary layer, so still set qg to the exigent air RH value not the SST saturation so that it doesnt serve as a source of moisture (even if SST saturation value is greater) (Not sure why boundary layer parameterization doesn't just handle it but we were getting huge moisture spikes at sfc from SST when RH was low, maybe it's a subsidence thing)
-                p = vec(data[forcing]["lev"])[:]
-                q = selectdim(data[forcing]["q"], time_dim_num, initial_ind:size(data[forcing]["q"], time_dim_num)) # select our q value subset along the time dimension
+                p = vec(data[forcing_type]["lev"])[:]
+                q = selectdim(
+                    data[forcing_type]["q"],
+                    time_dim_num,
+                    initial_ind:size(data[forcing_type]["q"], time_dim_num),
+                ) # select our q value subset along the time dimension
                 q = vec.(collect(eachslice(q, dims = time_dim_num))) # turn our q from [lon, lat, lev, time] to a list of vectors along [lon,lat,lev] to match p
                 q = map(mr -> mr ./ (1.0 .+ mr), q) # mixing ratio to specific humidity for each vector we created in q
                 qg = map((pg, q) -> calc_qg_extrapolate_pq([pg], p, q)[1], pg, q) # map the function to get out qg for each time step
             end
 
-            tg = data[forcing]["tsec"][initial_ind:end] # get the time array
+            tg = data[forcing_type]["tsec"][initial_ind:end] # get the time array
             tg = tg .- tg[1] # i think we need this to get the initial time to be 0, so the interpolation works
             # in this interpolation, tsec has to be adjusted to our offsets no? or we clip e.g. pg to be pg[initial_ind:end], tsec would also need to be adjusted no?, subtract the value at initial_ind i guess...
             return (;
-                pg = t -> pyinterp([t], tg, pg; method = :Spline1D)[1], # in time always use spline1d rn...
-                Tg = t -> pyinterp([t], tg, Tg; method = :Spline1D)[1],
-                qg = t -> pyinterp([t], tg, qg; method = :Spline1D)[1],
+                pg = let tg = tg, pg = pg # let block for performance of captured variables
+                    t -> pyinterp([t], tg, pg; method = :Spline1D)[1] # in time always use spline1d rn...
+                end,
+                Tg = let tg = tg, Tg = Tg # let block for performance of capturd variables
+                    t -> pyinterp([t], tg, Tg; method = :Spline1D)[1]
+                end,
+                qg = let tg = tg, qg = qg # let block for performance of captured variables
+                    t -> pyinterp([t], tg, qg; method = :Spline1D)[1]
+                end,
             ) # would use ref and broadcast but doesnt convert back to array
         else
             error(
@@ -120,7 +122,7 @@ function process_case(
     T = map(x -> x["T"], data)
     Tg = map(x -> x["Tg"], data)
     q = map(x -> x["q"], data)
-    q = map(mr -> mr ./ (1 .+ mr), q) # mixing ratio to specific humidity for each forcing
+    q = map(mr -> mr ./ (1 .+ mr), q) # mixing ratio to specific humidity for each forcing_type
 
     #For not surface though, we need to add in the ΔT from the summary table in the Atlas paper (to tsg above?)
     summary_file = joinpath(dirname(@__DIR__), "Data", "SOCRATES_summary.nc")
@@ -142,7 +144,7 @@ function process_case(
             pg,
             p,
             q,
-        ) # iterate over forcings, the pg value, the p value is a fixed array, for the q value we take our slices in z and align them along the time dimension to match the shape of pg for calc_qg broadcasting, 
+        ) # iterate over forcing_types, the pg value, the p value is a fixed array, for the q value we take our slices in z and align them along the time dimension to match the shape of pg for calc_qg broadcasting, 
 
     else # Tg > SST/T_orig, assume SST sets moisture  below last known point (t > t_orig), t_orig = Tg_q_sfc
         # Tg_q_sfc = map((x,y) -> min.(x, y), Tg, Tg_orig) # min of Tg and T (Moisture comes from evaporation, if Tg < SST, SST limits moisture, if Tg > SST, Tg limits moisture) This is important bc it's how we extrapolate from the surface...
@@ -154,25 +156,30 @@ function process_case(
         ) # TESTINGGGG (if p_input < pg, there may be a sfc discontinuity, otherwise we should get cleaner extrapolation...
     end
 
-    # Set up thermodynamic states for easier use (for both forcing and ERA -- note ERA subsidence for example depends on density which relies on T,p,q so need both even if forcing is :obs_data)
+    # Set up thermodynamic states for easier use (for both forcing_type and ERA -- note ERA subsidence for example depends on density which relies on T,p,q so need both even if forcing_type is :obs_data)
     tsg = map((pg, Tg, qg) -> TD.PhaseEquil_pTq.(thermo_params, pg, Tg, qg), pg, Tg, qg)
 
-    # In principle at initiation they assume domination by liquid, so T_l,i ≈ T_l. We are given in the forcing files T_L = T - L q_c/ c_p. Then, θ_L,I ≈ θ_L = θ - θ\T L q_c/ c_p = (θ/T) ( T - L q_c/ c_p) = (θ/T) T_L thus θ_L = T_L (p_0/p)^k, the same as just calculating the dry potential temperature subsitututing T_L
+    # In principle at initiation they assume domination by liquid, so T_l,i ≈ T_l. We are given in the forcing_type files T_L = T - L q_c/ c_p. Then, θ_L,I ≈ θ_L = θ - θ\T L q_c/ c_p = (θ/T) ( T - L q_c/ c_p) = (θ/T) T_L thus θ_L = T_L (p_0/p)^k, the same as just calculating the dry potential temperature subsitututing T_L
     θ = map((T, p) -> TD.dry_pottemp_given_pressure.(thermo_params, T, p), T, p) # should be same as # θ = map((T, p, q) -> TD.dry_pottemp_given_pressure.(thermo_params, T, p, TD.PhasePartition.(q)), T, p, q)
 
     ts = map((p, θ, q) -> TD.PhaseEquil_pθq.(thermo_params, p, θ, q), p, θ, q)
 
     # get indices where the ground would get inserted in... (and convert to same shape/dims.)
     ground_indices =
-        map((ts) -> get_ground_insertion_indices(ts, tsg[forcing], z_dim_num; thermo_params, data = data), ts) # 
-
-    q_full = combine_air_and_ground_data(q[forcing], qg[forcing], z_dim_num; insert_location = ground_indices[forcing]) # full q_array/qt_nudge -- is used from the chosen forcing dataset
+        map((ts) -> get_ground_insertion_indices(ts, tsg[forcing_type], z_dim_num; thermo_params, data = data), ts) # 
+
+    q_full = combine_air_and_ground_data(
+        q[forcing_type],
+        qg[forcing_type],
+        z_dim_num;
+        insert_location = ground_indices[forcing_type],
+    ) # full q_array/qt_nudge -- is used from the chosen forcing_type dataset
     qt_nudge = q_full
 
 
     ts_full = map(
         (ts, ground_indices) ->
-            combine_air_and_ground_data(ts, tsg[forcing], z_dim_num; insert_location = ground_indices),
+            combine_air_and_ground_data(ts, tsg[forcing_type], z_dim_num; insert_location = ground_indices),
         ts,
         ground_indices,
     ) # is it era5? their output les plots sure don't look it...
@@ -181,22 +188,22 @@ function process_case(
 
     # old_z  => Precompute old z coordinate (precompute to save us some trouble later (get_data_new_z_t func can self-calculate it but it's redundant to keep calculating z)
     if !use_LES_output_for_z
-        z_old = map((ts, data) -> lev_to_z(ts, tsg[forcing]; thermo_params, data = data), ts, data) # should this be tsg[:ERA5_data] cause surface is always ERA5 (is it?) 
+        z_old = map((ts, data) -> lev_to_z(ts, tsg[forcing_type]; thermo_params, data = data), ts, data) # should this be tsg[:ERA5_data] cause surface is always ERA5 (is it?) 
     else
         z_old = map(
             (ts, data, ground_indices) -> lev_to_z_from_LES_output(
                 ts,
-                tsg[forcing];
+                tsg[forcing_type];
                 thermo_params,
                 data = data,
                 flight_number = flight_number,
-                forcing_type = forcing,
+                forcing_type = forcing_type,
                 ground_indices = ground_indices,
             ),
             ts,
             data,
             ground_indices,
-        ) # should this be tsg[:ERA5_data] cause surface is always ERA5 (is it?) [ + Testing getting z from the forcing data ]
+        ) # should this be tsg[:ERA5_data] cause surface is always ERA5 (is it?) [ + Testing getting z from the forcing_type data ]
     end
 
     if return_old_z
@@ -205,13 +212,13 @@ function process_case(
 
 
     # ω (subsidence) # always forced by era5
-    ρ = TD.air_density.(thermo_params, ts[forcing])
-    ρg = TD.air_density.(thermo_params, tsg[forcing])
-    ρ = combine_air_and_ground_data(ρ, ρg, z_dim_num; insert_location = ground_indices[forcing])
-    ω = data[forcing]["omega"]
-    dpdt_g = data[forcing]["Ptend"]
+    ρ = TD.air_density.(thermo_params, ts[forcing_type])
+    ρg = TD.air_density.(thermo_params, tsg[forcing_type])
+    ρ = combine_air_and_ground_data(ρ, ρg, z_dim_num; insert_location = ground_indices[forcing_type])
+    ω = data[forcing_type]["omega"]
+    dpdt_g = data[forcing_type]["Ptend"]
     dpdt_g = add_dim(dpdt_g, z_dim_num) # should be lon lat lev time (hopefully order was already correct)
-    ω = combine_air_and_ground_data(ω, dpdt_g, z_dim_num; insert_location = ground_indices[forcing])
+    ω = combine_air_and_ground_data(ω, dpdt_g, z_dim_num; insert_location = ground_indices[forcing_type])
 
     p_grid = map((p,) -> add_dim(align_along_dimension(p, z_dim_num), time_dim_num), p) # align on dimension 3 lev, add time dimensino 4
     p_full = map(
@@ -233,12 +240,12 @@ function process_case(
     L = 2.2 # maximum value (shape parameter)
     a = -L / 2
     p0 = 250.0 * 100
-    p1 = add_dim(pg[forcing][:], z_dim_num)
+    p1 = add_dim(pg[forcing_type][:], z_dim_num)
     (p1, y1) = (p1, 1) # use our ground pressure (can't use pfull cause would need to pull)
     (p2, y2) = (p0, 0)
     k = @. log((L / 2 + 1) / (L / 2 - 1)) / (p1 - p0) # ps is an array so we have an array of ks
-    f_p = @. cos(π / 2 * (p1 - p_full[forcing]) / (p1 - p0)) * (p_full[forcing] >= p0) # atlas email
-    f_p_alt = @. (a + L / (1 + exp(-k * (p_full[forcing] - p0)))) * (p_full[forcing] >= p0) # my original
+    f_p = @. cos(π / 2 * (p1 - p_full[forcing_type]) / (p1 - p0)) * (p_full[forcing_type] >= p0) # atlas email
+    f_p_alt = @. (a + L / (1 + exp(-k * (p_full[forcing_type] - p0)))) * (p_full[forcing_type] >= p0) # my original
 
 
 
@@ -260,10 +267,10 @@ function process_case(
 
 
     # u, v # always forced by ERA5
-    u = data[forcing]["u"]
-    v = data[forcing]["v"]
-    u = combine_air_and_ground_data(u, FT(0), z_dim_num; insert_location = ground_indices[forcing])
-    v = combine_air_and_ground_data(v, FT(0), z_dim_num; insert_location = ground_indices[forcing])
+    u = data[forcing_type]["u"]
+    v = data[forcing_type]["v"]
+    u = combine_air_and_ground_data(u, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
+    v = combine_air_and_ground_data(v, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
     u_nudge, v_nudge = u, v
 
     #=
@@ -271,33 +278,34 @@ function process_case(
         "forced by ERA5-derived geostrophic winds and nudged toward the ERA5 horizontal winds with a nudging
         timescale of 1 hr for the ERA5-based simulation and 20 min for the Obs-based simulation."
     means so we're just using u,v not ug,vg for now...
-    What does it mean to have both the forcing and the nudging? are they not overlapping/competing?
+    What does it mean to have both the forcing_type and the nudging? are they not overlapping/competing?
     =#
 
     # u_g, v_g # always forced by ERA5
-    ug = data[forcing]["ug"]
-    vg = data[forcing]["vg"]
-    ug = combine_air_and_ground_data(ug, FT(0), z_dim_num; insert_location = ground_indices[forcing])
-    vg = combine_air_and_ground_data(vg, FT(0), z_dim_num; insert_location = ground_indices[forcing])
+    ug = data[forcing_type]["ug"]
+    vg = data[forcing_type]["vg"]
+    ug = combine_air_and_ground_data(ug, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
+    vg = combine_air_and_ground_data(vg, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
     ug_nudge, vg_nudge = ug, vg
 
     # H (nudge)
-    θ_liq_ice = TD.liquid_ice_pottemp.(thermo_params, ts_full[forcing])
+    θ_liq_ice = TD.liquid_ice_pottemp.(thermo_params, ts_full[forcing_type])
     H_nudge = θ_liq_ice
 
 
     # dTdt_hadv (i think these are supposed to be always ERA5)
-    dTdt_hadv = data[forcing]["divT"]
-    dTdt_hadv = combine_air_and_ground_data(dTdt_hadv, FT(0), z_dim_num; insert_location = ground_indices[forcing])
+    dTdt_hadv = data[forcing_type]["divT"]
+    dTdt_hadv = combine_air_and_ground_data(dTdt_hadv, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
 
     # dqdt_hadv (i think these are supposed to be always ERA5)
-    dqtdt_hadv = data[forcing]["divq"]
-    dqtdt_hadv = combine_air_and_ground_data(dqtdt_hadv, FT(0), z_dim_num; insert_location = ground_indices[forcing])
+    dqtdt_hadv = data[forcing_type]["divq"]
+    dqtdt_hadv =
+        combine_air_and_ground_data(dqtdt_hadv, FT(0), z_dim_num; insert_location = ground_indices[forcing_type])
     # expand everything to new z grid and make t operation (initial condition or time splines)
-    # dTdt_hadv  = get_data_new_z_t(dTdt_hadv , new_z, z_dim_num,time_dim_num, flight_number; z_old = z_old[forcing], data=data[forcing], thermo_params,  initial_condition)
+    # dTdt_hadv  = get_data_new_z_t(dTdt_hadv , new_z, z_dim_num,time_dim_num, flight_number; z_old = z_old[forcing_type], data=data[forcing_type], thermo_params,  initial_condition)
 
     # ======================================================================================================================== #
-    LES_data = open_atlas_les_output(flight_number)[forcing]
+    LES_data = open_atlas_les_output(flight_number, forcing_type)[forcing_type]
     dTdt_rad = LES_data["RADQR"] ./ (24 * 3600) # convert to K/s from K/day (dividing drops nc dim data tho but converts it to array from ncvariable)
 
     z_dim_num_LES = get_dim_num("z", LES_data["RADQR"]) # assume it's same for all LES 2D vars?
@@ -308,26 +316,27 @@ function process_case(
         new_z[:dTdt_rad],
         z_dim_num_LES,
         time_dim_num_LES,
-        flight_number;
+        flight_number,
+        forcing_type,
+        ;
         z_old = nothing,
         data = LES_data,
-        thermo_params,
         initial_condition,
     )[:]
 
     # ======================================================================================================================== #
 
     dTdt_hadv = get_data_new_z_t(
-        dTdt_hadv,#.* (forcing == :ERA5_data),
+        dTdt_hadv,#.* (forcing_type == :ERA5_data),
         new_z[:dTdt_hadv],
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
-    )[:]  # testing not using forcing for obs to see if fixes anything
+    )[:]  # testing not using forcing_type for obs to see if fixes anything
 
     H_nudge = get_data_new_z_t(
         H_nudge,
@@ -335,8 +344,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
         # interp_method = :pchip_smooth, # testing if this is the one that breaks things
@@ -347,18 +356,18 @@ function process_case(
         ),  # not too high to avoid cusps (changed to high to keep model fidelity)
     )[:]
 
-    # dqtdt_hadv = get_data_new_z_t(dqtdt_hadv, new_z, z_dim_num,time_dim_num, flight_number; z_old = z_old[forcing], data=data[forcing], thermo_params,  initial_condition)
+    # dqtdt_hadv = get_data_new_z_t(dqtdt_hadv, new_z, z_dim_num,time_dim_num, flight_number; z_old = z_old[forcing_type], data=data[forcing_type], thermo_params,  initial_condition)
     dqtdt_hadv = get_data_new_z_t(
-        dqtdt_hadv,#.* (forcing == :ERA5_data),
+        dqtdt_hadv,#.* (forcing_type == :ERA5_data),
         new_z[:dqtdt_hadv],
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
-    )[:] # testing not using forcing for obs to see if fixes anything
+    )[:] # testing not using forcing_type for obs to see if fixes anything
 
     qt_nudge = get_data_new_z_t(
         qt_nudge,
@@ -366,8 +375,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
         # interp_method = :pchip_smooth,
@@ -384,8 +393,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
         interp_method = :Spline1D, # verifying if this is still unstable
@@ -402,8 +411,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
     )[:]
@@ -414,8 +423,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
     )[:]
@@ -426,8 +435,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
     )[:]
@@ -437,8 +446,8 @@ function process_case(
         z_dim_num,
         time_dim_num,
         flight_number;
-        z_old = z_old[forcing],
-        data = data[forcing],
+        z_old = z_old[forcing_type],
+        data = data[forcing_type],
         thermo_params,
         initial_condition,
     )[:]
@@ -449,7 +458,7 @@ end
 
 
 function get_default_new_z(flight_number::Int;)
-    data = open_atlas_les_input(flight_number)
+    data = open_atlas_les_grid(flight_number)
     new_z = data[:grid_data]
     return new_z
 end
@@ -457,12 +466,12 @@ end
 """
     surface_ref_state(
         flight_number::Int;
-        obs_or_ERA5 = "Obs"::Union{String,Symbol},
+        forcing_type::Symbol = :obs_data,
         thermo_params
     )
 
 In Cases.jl from TurbulenceConvection.jl you're asked to provide a surface reference state so I'm gonna provide one based off just whatever our base profile is
 """
-function surface_ref_state(flight_number::Int; obs_or_ERA5 = "Obs"::Union{String, Symbol}, thermo_params)
+function surface_ref_state(flight_number::Int; forcing_type::Symbol = :obs_data, thermo_params::TDPS)
     return nothing
 end
diff --git a/test/pchip_test.jl b/test/pchip_test.jl
deleted file mode 100644
index 0b39c04..0000000
--- a/test/pchip_test.jl
+++ /dev/null
@@ -1,389 +0,0 @@
-
-
-using Dierckx
-include("../src/interpolating_methods.jl")
-using NCDatasets
-
-# ============================================== #
-using Plots
-dpi = 600
-
-outpath = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/test/")
-if !isdir(joinpath(outpath, "pchip_test"))
-    mkdir(joinpath(outpath, "pchip_test"))
-end
-
-
-# ============================================================================================ #
-
-FT = Float64
-flight_number = 13
-forcing_str = "Obs"
-initial_condition = true
-
-reload_SSCF = true
-if @isdefined(old_flight_number) && flight_number != old_flight_number
-    reload_SSCF = true # force reload if flight number changes and we forgot to update
-    old_flight_number = flight_number
-    @info("flight number changed, forcing reload of SSCF")
-end
-if reload_SSCF
-    using Pkg
-    using Revise
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/test"))
-    import CLIMAParameters as CP # use CLIMAParameters = "0.7, 0.8, 0.9, 0.10"
-    # import ClimaParams as CPP # would using this trouble w/ TC.jl? it's a different uuid technically..., use ClimaParams = "0.10"
-    import Thermodynamics as TD
-    import Thermodynamics.Parameters as TDP
-    # FT = Float64
-
-    toml_dict = CP.create_toml_dict(FT; dict_type = "alias") # CP 0.7 and below, Thermodynamics 0.11 and above
-    aliases = string.(fieldnames(TDP.ThermodynamicsParameters))
-    param_pairs = CP.get_parameter_values!(toml_dict, aliases, "Thermodynamics")
-    thermo_params = TDP.ThermodynamicsParameters{FT}(; param_pairs...)
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/"))
-    include(
-        "/home/jbenjami/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/src/SOCRATESSingleColumnForcings.jl",
-    )
-
-    # get sscf output
-    SSCFout = Main.SOCRATESSingleColumnForcings.process_case(
-        flight_number;
-        thermo_params = thermo_params,
-        initial_condition = initial_condition,
-        use_LES_output_for_z = false,
-    )
-    SSCFout_lesz = Main.SOCRATESSingleColumnForcings.process_case(
-        flight_number;
-        thermo_params = thermo_params,
-        initial_condition = initial_condition,
-        use_LES_output_for_z = true,
-    )
-    # get old z
-    SSCFout_z_old = Main.SOCRATESSingleColumnForcings.process_case(
-        flight_number;
-        thermo_params = thermo_params,
-        initial_condition = initial_condition,
-        use_LES_output_for_z = false,
-        return_old_z = true,
-    )
-    SSCFout_z_old_lesz = Main.SOCRATESSingleColumnForcings.process_case(
-        flight_number;
-        thermo_params = thermo_params,
-        initial_condition = initial_condition,
-        use_LES_output_for_z = true,
-        return_old_z = true,
-    )
-end
-redo_SSCF_postprocessing = false
-if redo_SSCF_postprocessing | reload_SSCF
-    @info("redoing post processing")
-    z_SSCF = Main.SOCRATESSingleColumnForcings.open_atlas_les_input(flight_number)[:grid_data]
-    old_z = SSCFout_z_old[:obs_data][:, :, :, 1][:]
-    old_z_lesz = SSCFout_z_old_lesz[:obs_data][:, :, :, 1][:]
-
-    old_z = reverse(old_z) # so it can be used for interpolation, it must be increasing
-
-    # read input data
-    SOCRATES_input_path = "/home/jbenjami/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/Data/Atlas_LES_Profiles/Input_Data/"
-    LES_forcing_str = forcing_str == "Obs" ? "obs" : "ERA5"
-    LES_forcing_suffix = forcing_str == "Obs" ? ".nc" : "_mar18_2022.nc"
-    LES_input_file =
-        "RF" * string(flight_number, pad = 2) * "_" * LES_forcing_str * "-based_SAM_input" * LES_forcing_suffix
-    LES_in_data = NCDatasets.Dataset(joinpath(SOCRATES_input_path, LES_input_file), "r") # technically there's some time editing we should do for this but we can put it off for obs
-    input_lev = LES_in_data["lev"][:] / 100
-    input_p_L = LES_in_data["lev"][:] / 100
-
-    # cutoff top of plot in p
-    p_cutoff = 550
-    valid = input_p_L .> p_cutoff
-    old_z_L = reverse(old_z[2:end])# take off the surface value (though it may have been inserted somewhere.... so technically this isn't right...)
-    input_p_L = input_p_L[valid]
-
-end
-
-# ============================================================================================ #
-
-
-
-# x_0 = FT.(collect(1:100:450))
-x_0 = FT.(collect(100:100:550))
-
-x_0 = FT.(collect(1:100:450))
-y_0 = []
-
-f(x) = sind(x) * x - log(abs(x))
-y_0 = f.(x_0)
-xx = (x_0[1] - 50):1:(x_0[end] + 50)
-
-spl_extrap = pyinterp(xx, x_0, y_0; method = :pchip, bc = "extrapolate", return_spl = true)
-y_spl_extrap = spl_extrap.(xx)
-
-spl_smooth = pyinterp(
-    xx,
-    x_0,
-    y_0;
-    method = :pchip_smooth_derivative,
-    bc = "extrapolate",
-    return_spl = true,
-    f_enhancement_factor = 2,
-    f_p_enhancement_factor = 4,
-)
-
-y_spl_smooth = spl_smooth.(xx)
-
-
-
-# plot fcn
-plot(
-    x_0,
-    y_0,
-    label = "y(x)",
-    lw = 2,
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 5.0,
-    markerstrokewidth = 0.2,
-    color = :black,
-)
-plot!(xx, y_spl_extrap, label = "pchip_extrap(x)", lw = 2, linestyle = :dot, color = :red)
-plot!(xx, y_spl_smooth, label = "pchip_smooth(x)", lw = 2, linestyle = :dot, color = :blue)
-
-savefig(joinpath(outpath, "pchip_test", "f(x).png"))
-
-# plot derivative
-dspl_extrap_dx = ForwardDiff.derivative.(Ref(spl_extrap), xx)
-dspl_smooth_dx = ForwardDiff.derivative.(Ref(spl_smooth), xx)
-
-
-dfdx = ForwardDiff.derivative.(f, xx)
-dfdx_x_0 = ForwardDiff.derivative.(f, x_0)
-
-plot(
-    xx,
-    dfdx,
-    label = "df/dx",
-    lw = 2,
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    color = :black,
-)
-
-scatter!(x_0, dfdx_x_0, markersize = 5.0, markerstrokewidth = 0.2, color = :black, label = :none)
-plot!(
-    xx,
-    dspl_extrap_dx,
-    lw = 1,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    label = "dspl_extrap_dx",
-    color = :red,
-)
-plot!(
-    xx,
-    dspl_smooth_dx,
-    lw = 1,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    label = "dspl_smooth_dx",
-    color = :blue,
-)
-savefig(joinpath(outpath, "pchip_test", "dfdx.png"))
-
-
-# ================================================================================================================================================================ #
-# new_z = [6.25, 24.48, 47.875, 70.11, 91.135, 110.92500000000001, 129.47, 146.775, 162.875, 177.825, 191.69, 204.565, 216.57, 227.835, 238.51, 248.775, 258.83, 268.83, 278.83, 288.83, 298.83, 308.83, 318.83, 328.83, 338.83, 348.83, 358.83, 368.83, 378.83, 388.83, 398.83, 408.83, 418.83, 428.83, 438.83, 448.83, 458.83, 468.83, 478.83, 488.83, 498.83, 508.83000000000004, 518.83, 528.83, 538.83, 548.83, 558.83, 568.83, 578.83, 588.83, 598.83, 608.83, 618.83, 628.83, 638.83, 648.83, 658.83, 668.83, 678.83, 688.83, 698.83, 708.83, 718.83, 728.83, 738.83, 748.83, 758.83, 768.83, 778.83, 788.83, 798.83, 808.83, 818.83, 828.83, 838.83, 848.83, 858.83, 868.83, 878.83, 888.83, 898.83, 908.83, 918.83, 928.83, 938.83, 948.83, 958.83, 968.83, 978.83, 988.83, 998.83, 1008.83, 1018.83, 1028.83, 1038.83, 1048.83, 1058.83, 1068.83, 1078.83, 1088.83, 1098.83, 1108.83, 1118.83, 1128.83, 1138.83, 1148.83, 1158.83, 1168.83, 1178.83, 1188.83, 1198.83, 1208.83, 1218.83, 1228.83, 1238.83, 1248.83, 1258.83, 1268.83, 1278.83, 1288.83, 1298.83, 1308.83, 1318.83, 1328.83, 1338.83, 1348.83, 1358.83, 1368.83, 1378.83, 1388.83, 1398.83, 1408.83, 1418.83, 1428.83, 1438.83, 1448.83, 1458.83, 1468.83, 1478.83, 1488.83, 1498.83, 1508.83, 1518.83, 1528.83, 1538.83, 1548.83, 1558.83, 1568.83, 1578.83, 1588.83, 1598.83, 1608.83, 1618.83, 1628.83, 1638.83, 1648.83, 1658.83, 1668.83, 1678.83, 1688.83, 1698.83, 1708.83, 1718.83, 1728.83, 1738.83, 1748.83, 1758.83, 1768.83, 1778.83, 1788.83, 1798.83, 1808.83, 1818.83, 1828.83, 1838.83, 1848.83, 1858.83, 1868.83, 1878.83, 1888.83, 1898.83, 1908.83, 1918.83, 1928.83, 1938.83, 1948.83, 1958.83, 1968.83, 1978.83, 1988.83, 1998.83, 2008.83, 2018.83, 2028.83, 2038.83, 2048.83, 2058.83, 2068.83, 2078.83, 2088.83, 2098.83, 2108.83, 2118.83, 2128.83, 2138.83, 2148.83, 2158.83, 2168.83, 2178.83, 2188.83, 2198.83, 2208.83, 2218.83, 2228.83, 2238.83, 2248.83, 2258.83, 2268.83, 2278.83, 2288.83, 2298.83, 2308.83, 2318.83, 2328.83, 2338.83, 2348.83, 2358.83, 2368.83, 2378.83, 2388.83, 2398.83, 2408.83, 2418.83, 2428.83, 2438.83, 2448.83, 2458.83, 2468.83, 2478.83, 2488.83, 2498.83, 2508.83, 2518.83, 2528.83, 2538.83, 2548.83, 2558.83, 2568.83, 2578.83, 2588.83, 2598.83, 2608.83, 2618.83, 2628.83, 2638.83, 2648.83, 2658.83, 2668.8450000000003, 2678.91, 2689.075, 2699.395, 2709.915, 2720.685, 2731.75, 2743.1549999999997, 2754.9449999999997, 2767.16, 2779.8450000000003, 2793.04, 2806.79, 2821.13, 2836.095, 2851.725, 2868.05, 2885.1099999999997, 2902.9449999999997, 2921.58, 2941.04, 2961.365, 2982.58, 3004.71, 3027.79, 3051.8450000000003, 3076.895, 3102.96, 3130.0699999999997, 3158.25, 3187.51, 3217.87, 3249.3599999999997, 3281.99, 3315.77, 3350.72, 3386.8549999999996, 3424.1899999999996, 3462.7349999999997, 3502.5, 3543.495, 3585.7250000000004, 3629.2, 3673.9300000000003, 3719.915, 3767.16, 3815.675, 3865.455, 3916.5, 3968.8100000000004, 4022.385, 4077.225, 4133.33, 4190.6900000000005, 4249.295, 4309.145, 4370.23, 4432.545, 4496.075000000001, 4560.8099999999995, 4626.74, 4693.85, 4762.13]
-# old_z = [49016.5793075644, 43524.14361418918, 40344.120985314774, 36465.48750332606, 34004.69901079954, 31469.227732031584, 26681.360259984187, 23948.867484796476, 20546.016457980706, 18314.765750099687, 15947.088241232785, 14462.409337912199, 13247.745148906668, 12218.240268020056, 11321.214934309339, 10526.942113769623, 9815.733965004321, 8586.05974489884, 7549.196022619308, 6646.141731635911, 5835.645597342913, 5097.115540454137, 4418.035274282339, 3789.5593785950255, 3205.2628845210947, 2658.6015095883554, 2274.725705348264, 2254.4560470016236, 2234.2751069551605, 2143.9829150366454, 1897.2927276143064, 1656.4887170530435, 1421.4847412639022, 1191.9652889438523, 967.367547294151, 747.5683513351748, 532.2462079677715, 321.0786444349109, 114.04799823594456, 0.0]
-
-
-# lev = [100.0, 200.0, 300.0, 500.0, 700.0, 1000.0, 2000.0, 3000.0, 5000.0, 7000.0, 10000.0, 12500.0, 15000.0, 17500.0, 20000.0, 22500.0, 25000.0, 30000.0, 35000.0, 40000.0, 45000.0, 50000.0, 55000.0, 60000.0, 65000.0, 70000.0, 73700.0, 73900.0, 74100.0, 75000.0, 77500.0, 80000.0, 82500.0, 85000.0, 87500.0, 90000.0, 92500.0, 95000.0, 97500.0, 98897.29226050233]
-# lev = reverse(lev)
-# ================================================================================================================================================================ #
-
-
-
-# ================================================================================================================================================================ #
-
-
-# --------------------------------------------------------------------------- #
-#input
-# don't have bc have to convert
-# omega = [0.0689441324567163, 0.018601494247351285, 0.021586949767148585, -0.0198081700590118, 0.0008729602420883373, 0.02371155785651021, -0.00855045241800271, -0.005811092472464776, 0.0006139748555038891, 0.0168843919504238, -0.009646556206486205, -0.006270549174022626, 0.006732173115450085, 0.010498548457957849, 0.013839470816738654, 0.009499773542600834, -0.003270777650673191, -0.022438284639654672, -0.018138221828806828, -0.025622008450603178, -0.022464950321425904, -0.008664653834707478, 0.001407488342779453, 0.003940785549045592, 0.00868309884126105, 0.00870066686057692, 0.008735713112905568, 0.00871763285360348, 0.008718068996567185, 0.008731641354188078, 0.007564288199206238, 0.006104646460491195, 0.004425989321448251, 0.0029448475972575702, 0.0017023783729773387, 0.0009601629876168848, 0.0009264094911733292, 0.0006414507277809865, 0.0002316123582038783, -0.0]
-# what we got 
-# omega_nudge = [0.0689441324567163, 0.018601494247351285, 0.021586949767148585, -0.0198081700590118, 0.0008729602420883373, 0.02371155785651021, -0.00855045241800271, -0.005811092472464776, 0.0006139748555038891, 0.0168843919504238, -0.009646556206486205, -0.006270549174022626, 0.006732173115450085, 0.010498548457957849, 0.013839470816738654, 0.009499773542600834, -0.003270777650673191, -0.022438284639654672, -0.018138221828806828, -0.025622008450603178, -0.022464950321425904, -0.008664653834707478, 0.001407488342779453, 0.003940785549045592, 0.00868309884126105, 0.00870066686057692, 0.008735713112905568, 0.00871763285360348, 0.008718068996567185, 0.008731641354188078, 0.007564288199206238, 0.006104646460491195, 0.004425989321448251, 0.0029448475972575702, 0.0017023783729773387, 0.0009601629876168848, 0.0009264094911733292, 0.0006414507277809865, 0.0002316123582038783, -0.0]
-# omega_nudge = reverse(omega_nudge)
-# w = pyinterp(old_z, old_z, omega; method=:Dierckx, bc="extrapolate", return_spl=true)
-# spl_smooth = pyinterp(new_z, old_z, omega_nudge; method=:pchip_smooth_derivative, bc="extrapolate", return_spl=true, f_enhancement_factor=1, f_p_enhancement_factor=1)
-
-
-# plot(
-#     omega_nudge,
-#     old_z,
-#     label="omega(z)",
-#     lw=2,
-#     legend = :bottomright,
-#     dpi = dpi,
-#     marker = :circle,
-#     markersize = 5.0,
-#     markerstrokewidth = 0.2,
-#     color = :black,
-#     ylims = (-100, 4900),
-#     xlim = (-0.0041, .0091),
-#     minorgrid = true,
-# )
-# plot!(spl_smooth.(new_z), new_z, label="omega_smooth(z)", lw=2, linestyle=:dot, color=:red, marker = :circle, markersize = 1.0, markerstrokewidth = 0.2)
-# plot!()
-# vertical line at 0
-# vline!([0], label="w = 0", color="black", linestyle=:dash)
-# savefig(joinpath(outpath, "pchip_test", "omega(z).png"))
-
-# --------------------------------------------------------------------------- #
-
-# q_in_real = reverse(LES_in_data["q"][:][1,1,:,1][:])
-
-input_q_L = LES_in_data["q"][1, 1, :, 1][:]
-
-input_q_L = input_q_L ./ (1 .+ input_q_L) # input to mixing ratio
-# SSCFout.qt_nudge[:] .= SSCFout.qt_nudge ./(1 .- SSCFout.qt_nudge)
-
-#input 
-# q_in = [4.0570837325538955e-6, 3.878708196813387e-6, 3.7003326610728776e-6, 3.521957125333236e-6, 3.343581589592727e-6, 3.165206053852218e-6, 3.022505625259811e-6, 2.986830518111709e-6, 2.8084549823712e-6, 2.8084549823712e-6, 2.630079446630691e-6, 2.630079446630691e-6, 2.630079446630691e-6, 2.8084549823712e-6, 3.3328790574482965e-6, 4.14270398970934e-6, 5.894351750679611e-6, 1.6175917630754325e-5, 3.2158365633090786e-5, 4.273603490249429e-5, 5.2553824389643806e-5, 7.573550901446149e-5, 9.979123376440675e-5, 0.00013670069961980265, 0.00023155472919533413, 0.0003542429059743881, 0.0007306963205337525, 0.0010847300291061401, 0.0015356799733095786, 0.0015924761862504625, 0.0017141961145682625, 0.0018768185277631942, 0.002072617620229721, 0.0019257424473762513, 0.0021404151916503905, 0.00241292142868042, 0.0023815269470214844, 0.0021495237350463866, 0.0026412579650232334]
-# # qg_in = does not exist 
-# qg = 0.0029078267131820972
-# q_in = [q_in; qg]
-# # what we got
-# qt_nudge = [4.057067272692262e-6, 3.878693152494463e-6, 3.7003189686617413e-6, 3.5219447211949303e-6, 3.34357041009226e-6, 3.165196035354565e-6, 3.0224964897471683e-6, 2.9868215969818115e-6, 2.808447094973964e-6, 2.808447094973964e-6, 2.6300725293309885e-6, 2.6300725293309885e-6, 2.6300725293309885e-6, 2.808447094973964e-6, 3.3328679494025067e-6, 4.142686827784091e-6, 5.894317007501839e-6, 1.6175655974675654e-5, 3.2157331505866436e-5, 4.273420861186352e-5, 5.255106263032685e-5, 7.572977358151175e-5, 9.978127646772145e-5, 0.00013668201509271403, 0.00023150112401525437, 0.00035411746237545995, 0.0007301627932673214, 0.0010835546648230285, 0.0015333252763900572, 0.0015899442379141181, 0.001711262674740217, 0.001873302678587912, 0.0020683307614490784, 0.0019220410912612084, 0.002135843599562897, 0.0024071132535297174, 0.002375868751567041, 0.002144913193227929, 0.00263430009890474, 0.0029078267131820972]
-
-# q_in = reverse(q_in)
-# qt_nudge = reverse(qt_nudge)
-# q_in = pyinterp(old_z, old_z, q_in; method=:Dierckx, bc="extrapolate", return_spl=true)
-# spl_smooth = pyinterp(new_z, old_z, q_in; method=:pchip_smooth_derivative, bc="extrapolate", return_spl=true, f_enhancement_factor=5, f_p_enhancement_factor=8)
-plot(
-    # q_in,
-    # old_z,
-    input_q_L,
-    old_z_L,
-    label = "q_in(z)",
-    lw = 0.25,
-    legend = :topright,
-    dpi = dpi * 4,
-    marker = :circle,
-    markersize = 0.25,
-    markerstrokewidth = 0.025,
-    color = :black,
-    ylims = (-100, 4900),
-    # xlim = (0, 0.0028), # 9
-    xlim = (0, 0.005), # 13
-    minorgrid = true,
-)
-# plot!(spl_smooth.(new_z), new_z, label="q_smooth(z)", lw=.5, linestyle=:dot, color=:red, marker = :circle, markersize = 0.25, markerstrokewidth = 0.025)
-# plot!(qt_nudge, old_z, label="q_nudge(z)", lw=.5, linestyle=:dot, color=:blue, marker = :circle, markersize = 0.25, markerstrokewidth = 0.025)
-
-# plot!( q_in_real, old_z[2:end], label="q_in_real(z)", lw=.25, linestyle=:dot, color=:purple, marker = :circle, markersize = 0.25, markerstrokewidth = 0.025)
-
-plot!(
-    SSCFout.qt_nudge,
-    z_SSCF,
-    label = "q_sscf(z)",
-    lw = 0.03,
-    color = :cyan,
-    marker = :circle,
-    markersize = 0.1,
-    markerstrokewidth = 0.005,
-)
-plot!(
-    SSCFout_lesz.qt_nudge,
-    z_SSCF,
-    label = "q_sscf_lesz(z)",
-    lw = 0.03,
-    color = :magenta,
-    marker = :circle,
-    markersize = 0.1,
-    markerstrokewidth = 0.005,
-)
-savefig(joinpath(outpath, "pchip_test", "q(z).png"))
-
-# --------------------------------------------------------------------------- #
-# input 
-# T_in = [270.1995358747312, 271.491853711981, 264.66169192367835, 254.39951764043985, 245.56318333855592, 240.3947700616327, 231.80883957877097, 228.891149357076, 226.4982927915522, 226.82898764053874, 226.96912919780084, 227.87329200240646, 227.56650058982146, 228.99123733564977, 230.2427048129979, 230.75570933269347, 230.7010072378514, 230.36445911148962, 229.45073493232331, 232.86006980810896, 237.54183363624094, 241.56144163061776, 245.3625783453703, 248.3100559262735, 250.56016043185605, 253.59022494950955, 255.7461354302619, 255.22323726581826, 254.41980685337265, 255.08936691847282, 257.4900041725251, 259.58967728526727, 261.06013908864617, 263.6792255439185, 265.3640244587275, 267.3134081104423, 269.18683252198093, 271.42147063283096, 272.67124007894427]
-# Tg_in = 278.3704840626871
-# Tg = 274.3204840626871
-# T_in = [T_in; Tg_in]
-
-# T_in_real = reverse(LES_in_data["T"][:][1,1,:,1][:])
-
-input_q_T = LES_in_data["T"][1, 1, :, 1][:] .* (1000 ./ input_lev) .^ 0.286
-
-#  what we got
-# θ_nudge = [1944.5835710665965, 1602.8407093918106, 1391.595245076395, 1155.9867693177894, 1013.5589888761049, 896.093129986276, 708.8423198654262, 623.3570815972575, 533.0740425693108, 484.9202476135982, 438.2085983376255, 412.7803095729882, 391.3007482909537, 376.7849606884522, 364.66277508553725, 353.3808232892484, 342.8201851026278, 324.9442209141309, 309.70963044731946, 302.54570367068675, 298.41522748036755, 294.465624449812, 291.0640848421155, 287.3277443129354, 283.3755290509006, 280.7930868142308, 279.0415072417078, 278.25342445813305, 277.16070341286894, 276.93217585959337, 276.9333890511754, 276.67086727628293, 275.8029519235561, 276.2056440134155, 275.6783137734898, 275.47785551306595, 275.2466480289731, 275.4264077960204, 274.64953535062017, 275.1903215901881]
-# T_in = reverse(T_in)
-# θ_nudge = reverse(θ_nudge)
-
-# θ_in = pyinterp(old_z, old_z, θ; method=:Dierckx, bc="extrapolate", return_spl=true)
-f_enhancement_factor = 5
-f_p_enhancement_factor = 6
-# spl_smooth_T = pyinterp(new_z, old_z, T_in; method=:pchip_smooth_derivative, bc="extrapolate", return_spl=true, f_enhancement_factor=f_enhancement_factor, f_p_enhancement_factor=f_p_enhancement_factor)
-# spl_smooth_θ = pyinterp(new_z, old_z, θ_nudge; method=:pchip_smooth_derivative, bc="extrapolate", return_spl=true, f_enhancement_factor=f_enhancement_factor, f_p_enhancement_factor=f_p_enhancement_factor)
-# spl_smooth_θ = pyinterp(new_z, old_z, θ_nudge; method=:Spline1D, bc="extrapolate", return_spl=true, f_enhancement_factor=f_enhancement_factor, f_p_enhancement_factor=f_p_enhancement_factor)
-
-plot(
-    # T_in,
-    # old_z,
-    input_q_T,
-    old_z_L,
-    label = "θ(z)",
-    lw = 0.5,
-    legend = :right,
-    dpi = dpi * 4,
-    marker = :circle,
-    markersize = 0.25,
-    markerstrokewidth = 0.025,
-    color = :black,
-    ylims = (-100, 4900),
-    # xlim = (270, 295), # 9
-    xlim = (275, 300), # 13
-    minorgrid = true,
-)
-# plot!(spl_smooth_T.(new_z), new_z, label="θ_smooth(z)", lw=.5, linestyle=:dot, color=:red, marker = :circle, markersize = .25, markerstrokewidth = 0.05)
-# twin axis
-ax2 = twiny()
-# plot!( ax2, θ_nudge, old_z, label="θ_nudge(z)", lw=.5, linestyle=:dot, color=:blue, marker = :circle, markersize = .25, markerstrokewidth = 0.025, ylims = (-100, 4900),xlim = (270, 300))
-# plot!( ax2, spl_smooth_θ.(new_z), new_z, label="θ_nudge_smooth(z)", lw=.5, linestyle=:dot, color=:green, marker = :circle, markersize = 0.25, markerstrokewidth = 0.025, ylims = (-100, 4900),xlim = (270, 300))
-# plot!( T_in_real, old_z[2:end], label="q_in_real(z)", lw=.5, linestyle=:dot, color=:purple, marker = :circle, markersize = .25, markerstrokewidth = 0.025)
-
-# H_nudge_320 =  [275.13104980901556, 275.0174376588642, 274.9091836777308, 274.80657237016504, 274.70979340586666, 274.67378262369425, 274.7410235730707, 274.80364921174777, 274.8618471539815, 274.9158425368792, 274.9658980203994, 275.01246387875665, 275.0559903861655, 275.097002862543, 275.1361016735085, 275.17403727608644, 275.2115601273009, 275.2490829785155, 275.28660582973004, 275.32412868094457, 275.3616515321591, 275.3991743833736, 275.4240736489235, 275.41556163404044, 275.40704961915736, 275.3985376042742, 275.39002558939114, 275.38151357450806, 275.373001559625, 275.3644895447419, 275.3559775298588, 275.34746551497574, 275.33895350009266, 275.3304414852096, 275.32192947032644, 275.3134174554434, 275.3049054405603, 275.29639342567714, 275.28788141079406, 275.27936939591103, 275.2708573810279, 275.2623453661448, 275.25383335126173, 275.24832149912095, 275.2590584270762, 275.26979535503136, 275.28053228298654, 275.2912692109417, 275.3020061388969, 275.3127430668521, 275.32347999480726, 275.3342169227625, 275.3449538507177, 275.35569077867285, 275.3664277066281, 275.3771646345832, 275.38790156253845, 275.3986384904936, 275.4093754184488, 275.420112346404, 275.43084927435916, 275.4415862023144, 275.4523231302696, 275.4630600582248, 275.47379698617993, 275.483527897143, 275.4926474421566, 275.5017669871703, 275.5108865321839, 275.5200060771976, 275.52912562221127, 275.5382451672249, 275.5473647122385, 275.5564842572522, 275.5656038022658, 275.5747233472795, 275.5838428922931, 275.5929624373067, 275.60208198232044, 275.61120152733406, 275.6203210723477, 275.62944061736135, 275.63856016237503, 275.64767970738865, 275.6567992524023, 275.66591879741594, 275.6750383424296, 275.6933591678578, 275.71683700423796, 275.7403148406182, 275.7637926769984, 275.7872705133786, 275.8107483497588, 275.834226186139, 275.8577040225192, 275.88118185889937, 275.9046596952796, 275.9281375316598, 275.95161536804, 275.9750932044202, 275.99857104080036, 276.02204887718057, 276.0455267135608, 276.0690045499409, 276.0924823863212, 276.11596022270135, 276.13943805908156, 276.16291589546177, 276.1863937318419, 276.20248632579853, 276.18495002488606, 276.16741372397365, 276.1498774230612, 276.13234112214866, 276.1148048212362, 276.0972685203238, 276.0797322194113, 276.06219591849884, 276.0446596175863, 276.02712331667385, 276.00958701576144, 275.992050714849, 275.9745144139365, 275.956978113024, 275.93944181211157, 275.92190551119904, 275.90436921028663, 275.88683290937416, 275.8692966084617, 275.85176030754917, 275.83422400663676, 275.81668770572423, 275.8109543331821, 275.84787894076004, 275.8848035483379, 275.9217281559159, 275.9586527634938, 275.9955773710717, 276.0325019786496, 276.0694265862275, 276.10635119380544, 276.14327580138337, 276.18020040896124, 276.21712501653917, 276.2540496241171, 276.290974231695, 276.32789883927296, 276.36482344685083, 276.40174805442877, 276.43867266200664, 276.47559726958457, 276.5125218771625, 276.54944648474043, 276.5863710923183, 276.62329569989623, 276.66022030747416, 276.6786234273401, 276.6895221552136, 276.700420883087, 276.7113196109605, 276.72221833883395, 276.7331170667074, 276.74401579458083, 276.7549145224543, 276.76581325032777, 276.77671197820126, 276.7876107060747, 276.7985094339482, 276.8094081618216, 276.8203068896951, 276.8312056175685, 276.842104345442, 276.85300307331545, 276.86390180118894, 276.8748005290623, 276.8856992569358, 276.89659798480926, 276.9074967126827, 276.9183954405562, 276.9292941684297, 276.9333583590354, 276.93330919488255, 276.9332600307296, 276.93321086657676, 276.9331617024239, 276.93311253827096, 276.9330633741181, 276.9330142099652, 276.9329650458123, 276.9329158816594, 276.9328667175065, 276.93281755335363, 276.93276838920076, 276.9327192250479, 276.932670060895, 276.9326208967421, 276.9325717325892, 276.9325225684363, 276.9324734042834, 276.93242424013056, 276.9323750759777, 276.93232591182476, 276.9322767476719, 276.932227583519, 276.9321784193661, 276.9561531605606, 276.9814474287444, 277.0067416969282, 277.03203596511196, 277.0573302332958, 277.0826245014796, 277.10791876966334, 277.13321303784716, 277.15850730603097, 277.65476439413584, 278.19579927445426, 278.6008544047283, 278.9896999758492, 279.0810554166068, 279.1266826714774, 279.172309926348, 279.2179371812187, 279.2635644360894, 279.30919169095995, 279.35481894583063, 279.40044620070125, 279.4460734555719, 279.49170071044256, 279.5373279653132, 279.58295522018386, 279.6285824750545, 279.6742097299251, 279.71983698479573, 279.7654642396664, 279.81109149453704, 279.8567187494077, 279.90234600427834, 279.94797325914897, 279.9936005140196, 280.03922776889027, 280.0848550237609, 280.1304822786316, 280.1761095335022, 280.2217367883728, 280.26736404324345, 280.3129912981141, 280.35861855298475, 280.40424580785543, 280.44987306272606, 280.4955003175967, 280.5411275724673, 280.586754827338, 280.6323820822086, 280.67800933707923, 280.7236365919499, 280.76926384682054, 280.8156634478242, 280.86304863050503, 280.9107645173521, 280.9590945690794, 281.0082750029485, 281.05849479276867, 281.110037399254, 281.16304455276133, 281.2177997140046, 281.27444461334096, 281.33321546803177, 281.3943012518865, 281.45789093871434, 281.524220745777, 281.5933851599791, 281.66562039858223, 281.7410681919434, 281.81987027041953, 281.90226285127227, 281.9883876648586, 282.0783391980832, 282.17225918130293, 282.27038383177955, 282.37271314951295, 282.47948335176477, 282.59078892543977, 282.70677160089474, 282.82747862158215, 282.95305171785884, 283.0836326200819, 283.219315815156, 283.36010130308097, 283.5626233351589, 283.77952333505823, 284.00413593632646, 284.23659644775955, 284.4770401781533, 284.72553478190576, 284.9822155678129, 285.24708253587465, 285.520270994887, 285.80178094485007, 286.09168004016163, 286.39003593521977, 286.69691628442234, 287.0122534333715, 287.33516042874476, 287.62739869784286, 287.92712873131654, 288.2344099876133, 288.5491830082857, 288.87150725178117, 289.2013232596523, 289.53869049034654, 289.8834305685216, 290.23560295262484, 290.59514818420894, 290.9620068048264, 291.29336721208136, 291.6146789164077, 291.94205310572124, 292.275339470477, 292.6145380106749, 292.95954851995145]
-# plot!(ax2, H_nudge_320, new_z, label="H_nudge_320(z)", lw=.5, linestyle=:dot, color=:cyan, marker = :circle, markersize = 0.25, markerstrokewidth = 0.025)
-
-plot!(
-    SSCFout.H_nudge,
-    z_SSCF,
-    label = "q_sscf(z)",
-    lw = 0.03,
-    color = :cyan,
-    marker = :circle,
-    markersize = 0.1,
-    markerstrokewidth = 0.005,
-)
-plot!(
-    SSCFout_lesz.H_nudge,
-    z_SSCF,
-    label = "q_sscf_lesz(z)",
-    lw = 0.03,
-    color = :magenta,
-    marker = :circle,
-    markersize = 0.1,
-    markerstrokewidth = 0.005,
-)
-savefig(joinpath(outpath, "pchip_test", "θ(z).png"))
-
-# --------------------------------------------------------------------------- #
-
-
-
-# construct thermodynamic states, then calcualte T from them...
diff --git a/test/random_test.jl b/test/random_test.jl
deleted file mode 100644
index 4af2a3b..0000000
--- a/test/random_test.jl
+++ /dev/null
@@ -1,3176 +0,0 @@
-a = [
-    6.25 1.2692701855051111e-5 344.5726759079331 0.003622583654954105
-    24.48 4.97147746258642e-5 343.83788070682715 0.003561342988890416
-    47.875 9.72260962096915e-5 342.90329351546205 0.003483122571131849
-    70.11 0.00014238165232922134 342.01715233411124 0.003409096709105384
-    91.135 0.0001850799013696133 341.18111837181493 0.00333938183561283
-    110.92500000000001 0.00022527007252344714 340.3958633655331 0.003274012272282246
-    129.47 0.00026214179031762165 339.8235231019965 0.0032136331863819945
-    146.775 0.0002963988103083523 339.31445799184155 0.0031575459404652837
-    162.875 0.00032827040937514 338.85356560863056 0.003105640724996747
-    177.825 0.00035786546565144293 338.42020741248996 0.0030575290578638606
-    191.69 0.00038531265329498404 337.9521504842157 0.0030124365776040218
-    204.565 0.0004108000345362817 337.57074450542115 0.002971147521730923
-    216.57 0.0004345651616665169 337.2154573578035 0.0029327406099777997
-    227.835 0.00045686538300113584 336.88237449203496 0.0028967818593268442
-    238.51 0.0004779976389041146 336.5670084261369 0.002862778443831147
-    248.775 0.000498318257812225 336.2640042125891 0.0028301470046177583
-    258.83 0.0005182231602107685 335.9674359734023 0.0027982457722790584
-    268.83 0.000538019184475854 335.6727227931577 0.0027665804337840207
-    278.83 0.0005578152087409396 335.37824173866716 0.002734976237945195
-    288.83 0.0005776112330060252 335.0842104297892 0.0027034348557095425
-    298.83 0.0005974072572711107 334.79022740408277 0.0026719529415005884
-    308.83 0.0006172032815361964 334.49647765888784 0.0026405319189527487
-    318.83 0.0006369993058012818 334.2029610842402 0.0026091717022533266
-    328.83 0.0006519107466375208 333.86641982533143 0.0026103602174730807
-    338.83 0.000665405184827977 333.5176630016966 0.002620958617858943
-    348.83 0.0006788996230184332 333.1692520099049 0.002631532704611388
-    358.83 0.0006923940612088896 332.82118657249447 0.002642082514476489
-    368.83 0.0007058884993993457 332.4734664108339 0.0026526080841514556
-    378.83 0.000719382937589802 332.1260912453956 0.00266310945028658
-    388.83 0.0007328773757802583 331.77906079600916 0.0026735866494871003
-    398.83 0.0007463718139707144 331.4323747821006 0.0026840397183149995
-    408.83 0.0007598662521611707 331.086032922903 0.002694468693290634
-    418.83 0.0007733606903516268 330.74003493765525 0.002704873610894312
-    428.83 0.0007868551285420832 330.3943805457698 0.002715254507567672
-    438.83 0.0008003495667325395 330.0490694669768 0.0027256114197148967
-    448.83 0.0008138440049229956 329.7041014214407 0.0027359443837037412
-    458.83 0.0008273384431134519 329.3594761299436 0.0027462534358671407
-    468.83 0.0008408328813039081 329.0151933139151 0.002756538612503577
-    478.83 0.0008543273194943643 328.67125269550223 0.002766799949877794
-    488.83 0.0008678217576848205 328.32765399762275 0.002777037484221381
-    498.83 0.0008813161958752768 327.98439694400844 0.0027872512517332945
-    508.83000000000004 0.0008948106340657331 327.6414812592272 0.0027974412885801957
-    518.83 0.0009083050722561893 327.29890666869966 0.0028076076308967634
-    528.83 0.0009217995104466455 326.9566728986944 0.00281775031478581
-    538.83 0.0009274415540976042 326.62981935896914 0.0028204582768689337
-    548.83 0.0009290091353930385 326.31107146273257 0.002819316114847624
-    558.83 0.0009305767166884729 325.99261726521803 0.0028181732204950686
-    568.83 0.0009321442979839071 325.67445656288703 0.0028170295967807307
-    578.83 0.0009337118792793412 325.35658915285035 0.0028158852466749398
-    588.83 0.0009352794605747756 325.0390148328214 0.0028147401731485003
-    598.83 0.00093684704187021 324.7217334010665 0.0028135943791722834
-    608.83 0.0009384146231656441 324.40474465629666 0.0028124478677162947
-    618.83 0.0009399822044610783 324.0880483976675 0.002811300641749694
-    628.83 0.0009415497857565127 323.77164442472997 0.0028101527042403724
-    638.83 0.0009431173670519469 323.455532537348 0.0028090040581542535
-    648.83 0.0009446849483473812 323.1397125356406 0.0028078547064547955
-    658.83 0.0009462525296428156 322.8241842199248 0.0028067046521025015
-    668.83 0.0009478201109382497 322.5089473906601 0.0028055538980544465
-    678.83 0.0009493876922336839 322.194001848395 0.00280440244726381
-    688.83 0.0009509552735291183 321.87934739371116 0.0028032503026794004
-    698.83 0.0009525228548245525 321.5649838271754 0.002802097467245233
-    708.83 0.0009540904361199868 321.2509109492897 0.0028009439439000933
-    718.83 0.0009556580174154211 320.93712856044596 0.0027997897355771487
-    728.83 0.0009572255987108552 320.62363646088073 0.0027986348452035442
-    738.83 0.0009587931800062896 320.3104344506362 0.0027974792757000646
-    748.83 0.0009644233082512129 319.9972852522195 0.002794301652304971
-    758.83 0.0009981911927114903 319.682785862424 0.0027771413469767354
-    768.83 0.0010319590771717675 319.36857977450995 0.002760012890377515
-    778.83 0.0010657269616320445 319.0546667818306 0.0027429162381512654
-    788.83 0.0010994948460923218 318.7410466773804 0.002725851345981782
-    798.83 0.001133262730552599 318.42771925377656 0.0027088181695926047
-    808.83 0.0011670306150128765 318.11468430323464 0.002691816664746894
-    818.83 0.0012007984994731537 317.8019416175547 0.0026748467872473956
-    828.83 0.001234566383933431 317.48949098810044 0.0026579084929363576
-    838.83 0.001268334268393708 317.1773322057902 0.002641001737695539
-    848.83 0.0013021021528539854 316.8654650610844 0.0026241264774462037
-    858.83 0.0013358700373142624 316.55388934397564 0.0026072826681491344
-    868.83 0.0013696379217745397 316.24260484398417 0.002590470265804695
-    878.83 0.001403405806234817 315.93161135015214 0.002573689226452876
-    888.83 0.0014371736906950944 315.62090865103795 0.0025569395061733617
-    898.83 0.0014709415751553714 315.3104965347141 0.0025402210610856
-    908.83 0.0015047094596156484 315.00037477506004 0.0025235338472391097
-    918.83 0.001538477344075926 314.69064204275395 0.002506878608558256
-    928.83 0.001572245228536203 314.3810789462991 0.0024902535517853574
-    938.83 0.0016060131129964801 314.07180879834505 0.0024736596223617247
-    948.83 0.0016397809974567574 313.7628311648407 0.002457096774451791
-    958.83 0.0016735488819170348 313.4541455841644 0.0024405649620891233
-    968.83 0.0017104686256470064 313.1481368744625 0.0024245329901064782
-    978.83 0.0017657883815427745 312.8563252061238 0.0024112652953038813
-    988.83 0.0018211081374385429 312.56477103731913 0.002398021984814805
-    998.83 0.0018764278933343112 312.2734739420615 0.002384803022489697
-    1008.83 0.0019317476492300796 311.982433492304 0.0023716083722344697
-    1018.83 0.0019870674051258477 311.69315774968766 0.0023584494121256143
-    1028.83 0.0020423871610216154 311.40119742418494 0.002345292440874166
-    1038.83 0.002097706916917384 311.1098214735451 0.0023321622408839318
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-
-
-# pchip
-a_pchip = [
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-    2498.83 0.008716596838443169 272.356669566529 0.00040626918522740493
-    2508.83 0.008715339849591273 272.1031210303046 0.00040038685552395574
-    2518.83 0.00871409259729529 271.84927362821765 0.00039490457202970443
-    2528.83 0.008712860519909233 271.59537393836376 0.0003897835622793993
-    2538.83 0.008711649055787116 271.3416675306338 0.0003849852099741078
-    2548.83 0.008710463643282962 271.08839896915646 0.00038047105460343593
-    2558.83 0.00870930972075078 270.8358118147322 0.0003762027910686656
-    2568.83 0.008708192726544583 270.58414862726573 0.00037214226930681996
-    2578.83 0.008707118099018396 270.3336509681858 0.0003682514939156495
-    2588.83 0.008706091276526221 270.08455940286757 0.00036449262377955726
-    2598.83 0.00870511769742208 269.8371135030409 0.00036082797169644816
-    2608.83 0.008704202800059986 269.59155184919695 0.0003572200040055213
-    2618.83 0.00870335202279396 269.3481120329874 0.0003536313402159986
-    2628.83 0.008702570803978012 269.10703065961724 0.0003500247526367978
-    2638.83 0.008701864581966158 268.86854335023315 0.0003463631660071528
-    2648.83 0.008701238795112408 268.63288474430243 0.0003426096571281797
-    2658.83 0.008700698881770785 268.40028850200747 0.00033872745449542235
-    2668.8450000000003 0.008700219002462472 268.1691414749626 0.00033479726900601496
-    2678.91 0.00869975990768105 267.9368077349054 0.0003309490049139973
-    2689.075 0.008699318690597087 267.70214029350814 0.00032716373826547935
-    2699.395 0.00869889277582794 267.46388416751927 0.0003234220596800806
-    2709.915 0.00869848036054807 267.221016361235 0.0003197100313616346
-    2720.685 0.008698079730972683 266.9724003959461 0.0003160135627052084
-    2731.75 0.008697689616697021 266.7170180422872 0.00031232188504977523
-    2743.1549999999997 0.008697308939248536 266.453854830659 0.00030862566332549667
-    2754.9449999999997 0.008696936767094753 266.1819011229348 0.0003049169413413
-    2767.16 0.008696572408439634 265.9002685916029 0.00030119058035255
-    2779.8450000000003 0.008696215035638128 265.60796091622166 0.0002974410368059388
-    2793.04 0.008695863913449956 265.30410588134066 0.0002936653185071391
-    2806.79 0.008695518032659827 264.9877267380884 0.00028985990918091903
-    2821.13 0.008695176392780961 264.65808938787114 0.0002860247958138688
-    2836.095 0.00869483760303617 264.3144739518743 0.0002821602865442487
-    2851.725 0.008694499648715652 263.9560625468504 0.00027826557097864184
-    2868.05 0.008694160067137562 263.58228602819963 0.00027434222041856644
-    2885.1099999999997 0.008693815339356783 263.192368420428 0.0002703888934986016
-    2902.9449999999997 0.008693460910480812 262.78556029542483 0.00026640359006112715
-    2921.58 0.008693091243175181 262.3614837874171 0.00026238638699233675
-    2941.04 0.00869269926494849 261.9197924458573 0.00025833531705752216
-    2961.365 0.008692275784817004 261.4598362378217 0.0002542428908588362
-    2982.58 0.008691809776932893 260.9813472470083 0.00025010173755263027
-    3004.71 0.008691287747271492 260.4841026713124 0.00024590066886861177
-    3027.79 0.008690693089605815 259.967706765055 0.00024162213173425782
-    3051.8450000000003 0.00869000611886979 259.43204626609804 0.00023724517950008536
-    3076.895 0.008689203563856508 258.87718104204566 0.00023274351102733445
-    3102.96 0.008688257978465634 258.3032375279255 0.00022808361621618096
-    3130.0699999999997 0.008687136781488162 257.71019713850404 0.00022322201339170848
-    3158.25 0.008685802127820065 257.09823589459796 0.00021810681215730422
-    3187.51 0.008684210960606521 256.46794318216655 0.00021267842471413853
-    3217.87 0.008677694834982817 255.82003906425567 0.00020687964137542535
-    3249.3599999999997 0.008621723699496221 255.1570373920644 0.00020080910133719244
-    3281.99 0.008504906032832714 254.47950016931108 0.0001945197380926647
-    3315.77 0.008327852968293446 253.7871897982238 0.00018803836122217944
-    3350.72 0.008092281781492702 253.07950801654414 0.00018139555575209953
-    3386.8549999999996 0.007801229417748655 252.35578855202596 0.00017462910696311898
-    3424.1899999999996 0.007459204780139134 251.61517383793222 0.00016778358454968032
-    3462.7349999999997 0.00707241828009648 250.85677137125214 0.00016091183818328278
-    3502.5 0.006648929471242567 250.0791979839971 0.0001540743528071706
-    3543.495 0.006198835014109467 249.2811044572207 0.00014734013942477498
-    3585.7250000000004 0.005734521697541734 248.46086031638063 0.0001407877724523672
-    3629.2 0.005270759411679333 247.61644709528767 0.00013450434010732205
-    3673.9300000000003 0.004824972374729601 246.74553664386664 0.00012858687338857571
-    3719.915 0.004417551681712786 245.84566755728815 0.00012314400982634793
-    3767.16 0.004071913558510835 244.9139369197189 0.00011829430519133672
-    3815.675 0.003803535866713628 243.9488896055676 0.00011407731938430107
-    3865.455 0.0035708602813748123 242.95832904886058 0.00011011496950673853
-    3916.5 0.0033625360503933776 241.94341050513486 0.0001063434206328568
-    3968.8100000000004 0.003173182404879927 240.90399835887675 0.00010275617806668274
-    4022.385 0.0029963361986903303 239.83993344616374 9.934365867690981e-5
-    4077.225 0.0028243822151999827 238.75103227615318 9.609307035391325e-5
-    4133.33 0.002648481788703748 237.63708631684136 9.298829844026875e-5
-    4190.6900000000005 0.0024585343490284755 236.49805995167546 9.001030352939265e-5
-    4249.295 0.0022430865762322946 235.33381966890892 8.713638868607657e-5
-    4309.145 0.001989230713877442 234.14421464689227 8.433981432280302e-5
-    4370.23 0.0016826148161914406 232.9290686973363 8.15905857992635e-5
-    4432.545 0.0013041965750993723 231.68804385989884 7.885906950634664e-5
-    4496.075000000001 0.0007745090574093201 230.41932700901617 7.621157740203683e-5
-    4560.8099999999995 7.546095827403658e-5 229.12351210172926 7.367390853816816e-5
-    4626.74 -0.0007767757565831984 227.80241459384467 7.123315535710575e-5
-    4693.85 -0.001763261742331813 226.45809574917268 6.88747854037773e-5
-    4762.13 -0.002862336716346668 225.09265980550614 6.658229454801531e-5
-]
-
-# pchip_smooth_w
-a_pchip = [
-    6.25 -0.0 344.5726759079331 0.003622583654954105
-    24.48 -0.0 343.83788070682715 0.003561342988890416
-    47.875 -0.0 342.90329351546205 0.003483122571131849
-    70.11 -0.0 342.01715233411124 0.003409096709105384
-    91.135 -0.0 341.18111837181493 0.00333938183561283
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-    129.47 0.0 339.8235231019965 0.0032136331863819945
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-    162.875 0.0 338.85356560863056 0.003105640724996747
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-    278.83 0.0 335.37824173866716 0.002734976237945195
-    288.83 0.0 335.0842104297892 0.0027034348557095425
-    298.83 0.0 334.79022740408277 0.0026719529415005884
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-    448.83 0.0 329.7041014214407 0.0027359443837037412
-    458.83 0.0 329.3594761299436 0.0027462534358671407
-    468.83 0.0 329.0151933139151 0.002756538612503577
-    478.83 0.0 328.67125269550223 0.002766799949877794
-    488.83 0.0 328.32765399762275 0.002777037484221381
-    498.83 0.0 327.98439694400844 0.0027872512517332945
-    508.83000000000004 0.0 327.6414812592272 0.0027974412885801957
-    518.83 0.0 327.29890666869966 0.0028076076308967634
-    528.83 0.0 326.9566728986944 0.00281775031478581
-    538.83 0.0 326.62981935896914 0.0028204582768689337
-    548.83 0.0 326.31107146273257 0.002819316114847624
-    558.83 0.0 325.99261726521803 0.0028181732204950686
-    568.83 0.0 325.67445656288703 0.0028170295967807307
-    578.83 0.0 325.35658915285035 0.0028158852466749398
-    588.83 0.0 325.0390148328214 0.0028147401731485003
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-    618.83 0.0 324.0880483976675 0.002811300641749694
-    628.83 0.0 323.77164442472997 0.0028101527042403724
-    638.83 0.0 323.455532537348 0.0028090040581542535
-    648.83 0.0 323.1397125356406 0.0028078547064547955
-    658.83 0.0 322.8241842199248 0.0028067046521025015
-    668.83 0.0 322.5089473906601 0.0028055538980544465
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-    688.83 0.0 321.87934739371116 0.0028032503026794004
-    698.83 0.0 321.5649838271754 0.002802097467245233
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-    718.83 0.0 320.93712856044596 0.0027997897355771487
-    728.83 0.0 320.62363646088073 0.0027986348452035442
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-    748.83 0.0 319.9972852522195 0.002794301652304971
-    758.83 0.0 319.682785862424 0.0027771413469767354
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-    948.83 0.0 313.7628311648407 0.002457096774451791
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-    1908.83 0.0 285.82528161518724 0.001760352483196975
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-]
-# pchip in time broke things
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-    3350.72 -7.987535460528337e-8 253.15989862011907 0.00018508630871845146
-    3386.8549999999996 -1.018890944485715e-7 252.43570630943051 0.00017919718955318958
-    3424.1899999999996 -1.1764819265906663e-7 251.6890947965046 0.00017315555480761245
-    3462.7349999999997 -1.2389340196392432e-7 250.92009103338117 0.00016696383468502087
-    3502.5 -1.180689269774097e-7 250.12846988940842 0.00016062442721914052
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-    3916.5 1.3080646983187112e-10 241.90644532591816 0.00010851500916277713
-    3968.8100000000004 2.502875975697813e-9 240.85669375314754 0.00010536250080711701
-    4022.385 6.683086582577602e-9 239.78495533713414 0.00010216539559902081
-    4077.225 1.0568203068570372e-8 238.69143266046467 9.89257185882252e-5
-    4133.33 1.503862331892752e-8 237.57632805448324 9.564551708833496e-5
-    4190.6900000000005 2.1396710681053314e-8 236.44004172554074 9.232743474440798e-5
-    4249.295 3.062384025291715e-8 235.28289878182107 8.897408241322871e-5
-    4309.145 4.34039518708285e-8 234.1052318084964 8.558758012047449e-5
-    4370.23 6.008037794286728e-8 232.90737029067014 8.217054374418121e-5
-    4432.545 8.102394196495548e-8 231.67879601666522 7.899431652737028e-5
-    4496.075000000001 1.1739931273144347e-7 230.39466950584827 7.669201260505208e-5
-    4560.8099999999995 1.722735106843547e-7 229.09125185326798 7.43732223260257e-5
-    4626.74 2.3896907125122515e-7 227.76895690037279 7.203958892656594e-5
-    4693.85 3.0498584764271574e-7 226.42829288493243 6.969291773503679e-5
-    4762.13 3.5117852238980756e-7 225.06965693368878 6.733482120250924e-5
-]
-# pchip in vertical not in time
-a_pchip = [
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-    1078.83 0.002164724731761468 309.95229977649717 0.002279923536442439
-    1088.83 0.002222445218730781 309.66329700326486 0.0022669220913740227
-    1098.83 0.002280434367241987 309.37454701246594 0.002253944636665445
-    1108.83 0.002338642528365203 309.0860493814815 0.0022409911369756113
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-    1128.83 0.0024555704095916902 308.50980952192504 0.0022151558617359035
-    1138.83 0.0025142438519293823 308.2220664624515 0.0022022740159568168
-    1148.83 0.0025730437513479245 307.93457410150575 0.002189415984740596
-    1158.83 0.0026319734306269335 307.6473320323855 0.002176581733206992
-    1168.83 0.002691046797210989 307.3603398523032 0.0021637712265712566
-    1178.83 0.0027502883432096326 307.07359716259504 0.002150984430144895
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-    1208.83 0.0029294574065295968 306.13817059789227 0.0021424770546932463
-    1218.83 0.002989901821767439 305.8070716814573 0.0021473538878615476
-    1228.83 0.0030508298984106767 305.476512302684 0.0021522198575346743
-    1238.83 0.0031122913083588837 305.14613046794346 0.002157072440077767
-    1248.83 0.003174318122896533 304.8160917380353 0.002161912819476801
-    1258.83 0.003236924812692997 304.4863958281436 0.0021667410151411477
-    1268.83 0.0033001082478025475 304.1570424325075 0.0021715570463092743
-    1278.83 0.0033638476976643548 303.82803123370786 0.0021763609321127884
-    1288.83 0.0034281048311024893 303.4993619091982 0.0021811526916219975
-    1298.83 0.0034928237163259213 303.1710341416253 0.0021859323439197085
-    1308.83 0.0035579309055488793 302.8430476151386 0.002190699908075137
-    1318.83 0.0036233529642897286 302.5154020121663 0.0021954554031206777
-    1328.83 0.003689048202187828 302.18809701476954 0.002200198848061553
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-    1358.83 0.003887509070280025 301.2082224710498 0.002214357071899139
-    1368.83 0.003954070936591191 300.88227670908583 0.002219052505927351
-    1378.83 0.004020830770281309 300.5566699573657 0.0022237359844666815
-    1388.83 0.004087796228392516 300.2314018956744 0.002228407526357698
-    1398.83 0.004154982534432888 299.90647220340617 0.0022330671504132544
-    1408.83 0.0042224124783764305 299.58188055956066 0.002237714875418413
-    1418.83 0.004290116416663083 299.2576266427433 0.0022423507201303873
-    1428.83 0.004358138656707799 298.9770809772997 0.0022352928336579537
-    1438.83 0.004426581495598367 298.7124432396562 0.0022240291216213876
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-    1538.83 0.0051437213960850905 296.0778020121606 0.0021125159320486563
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-    1568.83 0.00536419457110258 295.2916657762081 0.0020794586347343443
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-    1608.83 0.005649055811574167 294.2464880131572 0.002035664455387637
-    1618.83 0.005718005675092142 293.98572893825303 0.0020247661166537248
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-    1638.83 0.005853210579645098 293.4648521220433 0.002003029487734218
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-    1658.83 0.005985440919815178 292.9383779679217 0.0019817618765605787
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-    1688.83 0.006180231711993674 292.07754996261565 0.0019543958543386053
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-    1708.83 0.006308295580519674 291.50500843728616 0.001936234135127693
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-    1788.83 0.006807103935681096 289.2255500425848 0.0018642416128242995
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-    1828.83 0.007043249416992811 288.0922175442846 0.0018286353845214035
-    1838.83 0.00710009187717495 287.80954801715666 0.0018197742073044123
-    1848.83 0.00715605768424394 287.52714342158646 0.0018109291363119224
-    1858.83 0.00721121019922146 287.2450035027805 0.0018021001487271073
-    1868.83 0.007265648729157248 286.96312800532456 0.0017932872217576207
-    1878.83 0.0073195085271291005 286.681516673177 0.0017844903326356294
-    1888.83 0.007372960792242868 286.40016924967085 0.0017757094586178968
-    1898.83 0.007426212621152002 286.1173537383611 0.001767232253740821
-    1908.83 0.007479482610084638 285.82528161518724 0.001760352483196975
-    1918.83 0.007532936306535805 285.5334956016088 0.0017534848431040562
-    1928.83 0.007586703950831198 285.24199540464963 0.001746629316425514
-    1938.83 0.007640886927744569 284.95078073073415 0.0017397858861419502
-    1948.83 0.007695557766497727 284.65985128568497 0.001732954535251156
-    1958.83 0.007750760140760537 284.36920677471755 0.0017261352467681345
-    1968.83 0.007806508868650919 284.07884690243924 0.0017193280037251458
-    1978.83 0.007862789912734851 283.78877137284366 0.001712532789171733
-    1988.83 0.007919560380026369 283.498979889311 0.0017057495861747716
-    1998.83 0.00797674852198756 283.2094721546013 0.001698978377818489
-    2008.83 0.008034253734528572 282.920247870881 0.0016922191472046751
-    2018.83 0.008091946558007605 282.63130673970903 0.0016854718774526537
-    2028.83 0.00814949249277905 282.3426484619793 0.001678736551698994
-    2038.83 0.008205397289412485 282.05427273796596 0.0016720131530978367
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-    2058.83 0.00830574555961734 281.47836774907375 0.0016586020700577195
-    2068.83 0.008347779455193846 281.1908378816243 0.0016519143520152839
-    2078.83 0.008383355042036023 280.9035893627442 0.0016452384939184784
-    2088.83 0.008412129885565748 280.6166218895714 0.0016385744790099177
-    2098.83 0.008434106492972644 280.32993515860994 0.001631922290550041
-    2108.83 0.008449632313214061 280.04352886572605 0.0016252819118171417
-    2118.83 0.008459399737015087 279.7574027061456 0.0016186533261074148
-    2128.83 0.008464446096868548 279.4715563744512 0.0016120365167349919
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-    2148.83 0.008466212081208525 278.91299686293365 0.0015981777927892848
-    2158.83 0.008465675839044643 278.65331523129095 0.0015902358781187456
-    2168.83 0.008464706437146178 278.39386042001973 0.001582308454329848
-    2178.83 0.008463398396389014 278.134632196375 0.0015743955007495364
-    2188.83 0.008461822313508845 277.8756303268398 0.0015664969967289942
-    2198.83 0.008460040128875353 277.61685457712895 0.0015586129216437394
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-    2218.83 0.008456150475706135 277.0999804962883 0.0015428879759037978
-    2228.83 0.008454026552685468 276.8418816928227 0.001535047064122921
-    2238.83 0.008451470304362042 276.8174568661556 0.0014287716690216555
-    2248.83 0.008446921237812585 277.0715686775177 0.0012051424185277964
-    2258.83 0.008446957794584405 277.2606415628407 0.0010031046002354806
-    2268.83 0.008457171216922164 277.3665097422118 0.0008286368772392309
-    2278.83 0.008458911249522676 277.330835068376 0.0007216421518183574
-    2288.83 0.008458751975919464 277.09256115467815 0.0007111789125504795
-    2298.83 0.008458433333875784 276.8544712448103 0.0007007362826229436
-    2308.83 0.008457971639827876 276.61656515467183 0.0006903142321037609
-    2318.83 0.008457382333285697 276.3788426992859 0.0006799127311041853
-    2328.83 0.008456679976832908 276.1413036927955 0.000669531749778821
-    2338.83 0.008455878256126894 275.90394794846475 0.0006591712583257446
-    2348.83 0.00845498997989875 275.6667752786754 0.0006488312269866149
-    2358.83 0.008454027079953283 275.4297854949244 0.0006385116260467878
-    2368.83 0.008453000611169019 275.192978407824 0.0006282124258354349
-    2378.83 0.008451920751498195 274.95635382709963 0.0006179335967256578
-    2388.83 0.008450796801966762 274.7199115615876 0.0006076751091346035
-    2398.83 0.008449637186674389 274.48365141923523 0.0005974369335235835
-    2408.83 0.008448449452794453 274.24757320709847 0.0005872190403981894
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-    2428.83 0.008446015433333988 273.77596179724725 0.0005668439838487778
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-    2488.83 0.00843856851120161 272.36547355412745 0.0005062025402627189
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-    2638.83 0.008425135675972547 268.86753009872444 0.00035773829920746796
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-    2678.91 0.008423166401278145 267.9427744314085 0.000333450842828394
-    2689.075 0.00842271287798512 267.709456322259 0.0003309308744055996
-    2699.395 0.008422269794184268 267.47276314000703 0.0003283774593404216
-    2709.915 0.00842183576177864 267.23167205885693 0.00032577971510337446
-    2720.685 0.008421409439854166 266.9850492223517 0.00032312562133688635
-    2731.75 0.008420989934777683 266.7318790865574 0.0003204044937589016
-    2743.1549999999997 0.00842057656497165 266.4711498955205 0.0003176057511510233
-    2754.9449999999997 0.008420168838904526 266.2018539109293 0.0003147189215701552
-    2767.16 0.008419766585874835 265.92310172413966 0.00031173486948310084
-    2779.8450000000003 0.008419369570371621 265.63389412416603 0.0003086433547653599
-    2793.04 0.008418977768851357 265.33335060165257 0.0003054354837438475
-    2806.79 0.008418590987355281 265.0204816908401 0.000302101281097326
-    2821.13 0.008418209198373489 264.69453068213596 0.0002986333380444916
-    2836.095 0.008417832109117812 264.3547458320207 0.00029502438066253406
-    2851.725 0.008417458906607831 264.00026735827623 0.0002912660782606801
-    2868.05 0.008417088445376551 263.63046804896186 0.00028735266156905447
-    2885.1099999999997 0.008416718554615227 263.2445000426994 0.00028327612365018677
-    2902.9449999999997 0.008416346026411002 262.8415224365277 0.0002790286465999648
-    2921.58 0.008415966585971756 262.42103995931274 0.0002746061671442548
-    2941.04 0.008415574164496432 261.98256324961994 0.0002700047826650741
-    2961.365 0.008415159759450402 261.525271899304 0.0002652172324061497
-    2982.58 0.00841471169033219 261.0486907769389 0.0002602400009399265
-    3004.71 0.008414215442875631 260.55235161198914 0.000255069759811069
-    3027.79 0.008413653025905988 260.0355695567649 0.0002497010544796127
-    3051.8450000000003 0.008413002936618305 259.49789209109974 0.00024413098645838086
-    3076.895 0.008412239611602564 258.9389859371834 0.00023835801994738452
-    3102.96 0.008411332810557578 258.35852502737936 0.00023238081718315108
-    3130.0699999999997 0.008410246639659608 257.75596865621014 0.0002261959689801103
-    3158.25 0.008408939370292998 257.13089633202185 0.0002198014571784731
-    3187.51 0.008407363474598847 256.4832280443057 0.0002131988826189025
-    3217.87 0.008405218890420356 255.83588175027643 0.00020709348875087792
-    3249.3599999999997 0.008393271134003458 255.19964330883812 0.00020182612727616482
-    3281.99 0.008351412743288482 254.54164607206658 0.00019640156224556038
-    3315.77 0.008260476495526045 253.8618174159068 0.0001908215535613851
-    3350.72 0.008104623999478046 253.15988884466148 0.00018508636108294612
-    3386.8549999999996 0.00787344063905583 252.43569838883678 0.00017919723809355667
-    3424.1899999999996 0.0075644369243139525 251.68908967024706 0.0001731555994258938
-    3462.7349999999997 0.007186086619568106 250.9200893817243 0.0001669638752849161
-    3502.5 0.006761299010052584 250.1284712878834 0.00016062446370606015
-    3543.495 0.0063229503394740955 249.3142998774209 0.00015414009701953684
-    3585.7250000000004 0.005892523133045965 248.4776361401757 0.00014751435569759807
-    3629.2 0.005486081860045299 247.61844557185518 0.00014075015925435843
-    3673.9300000000003 0.005115471098356842 246.73669767930963 0.00013385056615865994
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-    3767.16 0.004497207916834608 244.9061124719276 0.0001196633936015751
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-    3865.455 0.003992799049897532 242.9340075550911 0.00011162091929331613
-    3916.5 0.0037701773785292275 241.9064458549572 0.00010851500747621877
-    3968.8100000000004 0.003566706102255662 240.85669479320958 0.00010536249730248193
-    4022.385 0.0033793631035100562 239.78495669810397 0.00010216539025281861
-    4077.225 0.0032023886817871793 238.69143421152936 9.892571137828071e-5
-    4133.33 0.003026657687444747 237.57633000765716 9.564550799380334e-5
-    4190.6900000000005 0.0028381775313199797 236.4400442851121 9.232742374611894e-5
-    4249.295 0.002621172533961453 235.28290207757698 8.89740694936877e-5
-    4309.145 0.0023615094882103926 234.10523590260988 8.558756526352608e-5
-    4370.23 0.0020475770133657643 232.90737521220953 8.217052693534798e-5
-    4432.545 0.0016708338495675502 231.67880240976976 7.899430518019319e-5
-    4496.075000000001 0.0012024566425684656 230.3946787391585 7.669199996537603e-5
-    4560.8099999999995 0.0005801758690602509 229.09126349131424 7.437320838759246e-5
-    4626.74 -0.00023039587268771028 227.76896931455786 7.203957368418927e-5
-    4693.85 -0.0012211235795694937 226.42830360420388 6.969290118469227e-5
-    4762.13 -0.0023333882072868813 225.06966783836282 6.733480334122536e-5
-]
-# pchip in vertical, not in time, + add q 
-a_pchip = [
-    6.25 9.606946574196332e-6 344.5726759079332 0.0
-    24.48 4.170153541165986e-5 343.83788070682715 0.0
-    47.875 8.9660462794051e-5 342.90329351546205 0.0
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-    91.135 0.00018225985843190877 341.18111837181493 0.0
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-    278.83 0.0005595889459326096 335.37824173866716 0.0
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-    528.83 0.0008950484682610099 326.9566728986944 0.0
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-    548.83 0.000900288213013848 326.31107146273257 0.0
-    558.83 0.0009024763790838056 325.99261726521803 0.0
-    568.83 0.0009044055721405366 325.67445656288703 0.0
-    578.83 0.0009060994646247153 325.35658915285035 0.0
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-    598.83 0.0009088877052856489 324.7217334010665 0.0
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-    618.83 0.0009110771511821428 324.0880483976675 0.0
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-    658.83 0.0009147872621115542 322.82418421992486 0.0
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-    718.83 0.00092324986002083 320.93712856044596 0.0
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-    738.83 0.0009279648896426939 320.31043445063625 0.0
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-    1118.83 0.002397030686220194 308.79780369032073 0.0
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-    1138.83 0.0025142438519293823 308.2220664624515 0.0
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-    1208.83 0.0029294574065295968 306.13817059789227 0.0
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-    1238.83 0.0031122913083588837 305.14613046794346 0.0
-    1248.83 0.003174318122896533 304.81609173803525 0.0
-    1258.83 0.003236924812692997 304.48639582814354 0.0
-    1268.83 0.0033001082478025475 304.1570424325075 0.0
-    1278.83 0.0033638476976643548 303.82803123370786 0.0
-    1288.83 0.0034281048311024893 303.4993619091982 0.0
-    1298.83 0.0034928237163259213 303.1710341416253 0.0
-    1308.83 0.0035579309055488793 302.8430476151386 0.0
-    1318.83 0.0036233529642897286 302.5154020121663 0.0
-    1328.83 0.003689048202187828 302.18809701476954 0.0
-    1338.83 0.00375498644395565 301.86113230463747 0.0
-    1348.83 0.0038211450807716023 301.53450756308536 0.0
-    1358.83 0.003887509070280025 301.2082224710497 0.0
-    1368.83 0.003954070936591191 300.88227670908583 0.0
-    1378.83 0.004020830770281309 300.5566699573657 0.0
-    1388.83 0.004087796228392516 300.2314018956744 0.0
-    1398.83 0.004154982534432888 299.90647220340617 0.0
-    1408.83 0.0042224124783764305 299.58188055956066 0.0
-    1418.83 0.004290116416663083 299.2576266427433 0.0
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-    1438.83 0.004426581495598367 298.71244323965607 0.0
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-    1458.83 0.004565140327767898 298.18381741240364 0.0
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-    1478.83 0.004706319952692462 297.6560567943727 0.0
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-    1498.83 0.004850172014517561 297.12899547311986 0.0
-    1508.83 0.004922986266769813 296.86587395492637 0.0
-    1518.83 0.004996272431515441 296.60296797345995 0.0
-    1528.83 0.005069903166370782 296.3402773767356 0.0
-    1538.83 0.0051437213960850905 296.0778020121606 0.0
-    1548.83 0.0052175315703356295 295.8155417265301 0.0
-    1558.83 0.005291094374051246 295.55349636602494 0.0
-    1568.83 0.00536419457110258 295.2916657762081 0.0
-    1578.83 0.0054366566750974074 295.03004980201695 0.0
-    1588.83 0.005508344949427074 294.7686482877642 0.0
-    1598.83 0.005579163407266498 294.50746107712945 0.0
-    1608.83 0.005649055811574167 294.2464880131572 0.0
-    1618.83 0.005718005675092142 293.98572893825303 0.0
-    1628.83 0.005786036260346051 293.72518369417685 0.0
-    1638.83 0.005853210579645098 293.4648521220433 0.0
-    1648.83 0.005919631395082053 293.2047340623116 0.0
-    1658.83 0.005985440919815178 292.9383779679218 0.0
-    1668.83 0.006050774726708625 292.65116621035077 0.0
-    1678.83 0.006115691634976708 292.36422362348117 0.0
-    1688.83 0.006180231711993674 292.0775499626157 0.0
-    1698.83 0.0062444258128834555 291.7911449824936 0.0
-    1708.83 0.006308295580519674 291.5050084372861 0.0
-    1718.83 0.006371853445525634 291.2191400805921 0.0
-    1728.83 0.006435102626274328 290.9335396654361 0.0
-    1738.83 0.006498037128888437 290.6482069442613 0.0
-    1748.83 0.006560641747240324 290.3631416689284 0.0
-    1758.83 0.006622892062952041 290.0783435907103 0.0
-    1768.83 0.006684754445395327 289.7938124602886 0.0
-    1778.83 0.006746185905589962 289.5095480277507 0.0
-    1788.83 0.006807103935681096 289.2255500425848 0.0
-    1798.83 0.006867367697971522 288.9418182536758 0.0
-    1808.83 0.006926860823342636 288.6583524093041 0.0
-    1818.83 0.006985502888703895 288.37515225714696 0.0
-    1828.83 0.007043249416992811 288.09221754428455 0.0
-    1838.83 0.00710009187717495 287.80954801715666 0.0
-    1848.83 0.00715605768424394 287.52714342158646 0.0
-    1858.83 0.00721121019922146 287.2450035027805 0.0
-    1868.83 0.007265648729157248 286.96312800532456 0.0
-    1878.83 0.0073195085271291005 286.681516673177 0.0
-    1888.83 0.007372960792242868 286.40016924967085 0.0
-    1898.83 0.007426212621152002 286.1173537383611 0.0
-    1908.83 0.007479482610084638 285.8252816151872 0.0
-    1918.83 0.007532936306535805 285.5334956016088 0.0
-    1928.83 0.007586703950831198 285.24199540464963 0.0
-    1938.83 0.007640886927744569 284.9507807307342 0.0
-    1948.83 0.007695557766497727 284.659851285685 0.0
-    1958.83 0.007750760140760537 284.3692067747176 0.0
-    1968.83 0.007806508868650919 284.07884690243924 0.0
-    1978.83 0.007862789912734851 283.78877137284366 0.0
-    1988.83 0.007919560380026369 283.498979889311 0.0
-    1998.83 0.00797674852198756 283.2094721546013 0.0
-    2008.83 0.008034253734528572 282.92024787088104 0.0
-    2018.83 0.008091946558007605 282.6313067397091 0.0
-    2028.83 0.00814949249277905 282.3426484619793 0.0
-    2038.83 0.008205397289412485 282.05427273796596 0.0
-    2048.83 0.008257940731652357 281.7661792673212 0.0
-    2058.83 0.00830574555961734 281.47836774907375 0.0
-    2068.83 0.008347779455193846 281.1908378816243 0.0
-    2078.83 0.008383355042036023 280.9035893627442 0.0
-    2088.83 0.008412129885565748 280.6166218895713 0.0
-    2098.83 0.008434106492972644 280.32993515860994 0.0
-    2108.83 0.008449632313214061 280.043528865726 0.0
-    2118.83 0.008459399737015087 279.7574027061457 0.0
-    2128.83 0.008464446096868548 279.4715563744512 0.0
-    2138.83 0.008466153667035004 279.18598956458203 0.0
-    2148.83 0.008466212081208525 278.91299686293365 0.0
-    2158.83 0.008465675839044643 278.6533152312909 0.0
-    2168.83 0.008464706437146178 278.39386042001973 0.0
-    2178.83 0.008463398396389014 278.134632196375 0.0
-    2188.83 0.008461822313508845 277.8756303268399 0.0
-    2198.83 0.008460040128875353 277.61685457712895 0.0
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-    2218.83 0.008456150475706135 277.0999804962883 0.0
-    2228.83 0.008454026552685468 276.84188169282277 0.0
-    2238.83 0.008451470304362042 276.8174568661556 0.0
-    2248.83 0.008446921237812585 277.0715686775177 0.0
-    2258.83 0.008446957794584405 277.2606415628407 0.0
-    2268.83 0.008457171216922164 277.3665097422118 0.0
-    2278.83 0.008458911249522676 277.33083506837596 0.0
-    2288.83 0.008458751975919464 277.09256115467815 0.0
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-    2308.83 0.008457971639827876 276.6165651546719 0.0
-    2318.83 0.008457382333285697 276.3788426992859 0.0
-    2328.83 0.008456679976832908 276.1413036927954 0.0
-    2338.83 0.008455878256126894 275.9039479484648 0.0
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-    2358.83 0.008454027079953283 275.4297854949244 0.0
-    2368.83 0.008453000611169019 275.192978407824 0.0
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-    2408.83 0.008448449452794453 274.24757320709847 0.0
-    2418.83 0.00844724027057405 274.01167673134097 0.0
-    2428.83 0.008446015433333988 273.77596179724725 0.0
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-    2448.83 0.008443537582446694 273.30507577109785 0.0
-    2458.83 0.008442291770809652 273.06990428516843 0.0
-    2468.83 0.008441044724081581 272.83491355327277 0.0
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-    2488.83 0.00843856851120161 272.36547355412745 0.0
-    2498.83 0.008437357251271451 272.131023885956 0.0
-    2508.83 0.008436174652198475 271.8967541699728 0.0
-    2518.83 0.008435027528282223 271.66266420351815 0.0
-    2528.83 0.008433921687351485 271.4287537830524 0.0
-    2538.83 0.008432861930764302 271.1950227041551 0.0
-    2548.83 0.00843185205340797 270.96147076152505 0.0
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-    2578.83 0.008429144548535807 270.26188768499924 0.0
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-    2618.83 0.00842628694205311 269.3316055481293 0.0
-    2628.83 0.00842569193799641 269.09947919898616 0.0
-    2638.83 0.008425135675972547 268.86753009872444 0.0
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-    2658.83 0.008424113292288846 268.40419798282977 0.0
-    2668.8450000000003 0.00842363247465228 268.17397337808615 0.0
-    2678.91 0.008423166401278145 267.9427744314085 0.0
-    2689.075 0.00842271287798512 267.70945632225903 0.0
-    2699.395 0.008422269794184268 267.47276314000703 0.0
-    2709.915 0.00842183576177864 267.23167205885693 0.0
-    2720.685 0.008421409439854166 266.9850492223517 0.0
-    2731.75 0.008420989934777683 266.73187908655734 0.0
-    2743.1549999999997 0.00842057656497165 266.4711498955205 0.0
-    2754.9449999999997 0.008420168838904526 266.2018539109293 0.0
-    2767.16 0.008419766585874835 265.9231017241396 0.0
-    2779.8450000000003 0.008419369570371621 265.63389412416603 0.0
-    2793.04 0.008418977768851357 265.33335060165257 0.0
-    2806.79 0.008418590987355281 265.0204816908401 0.0
-    2821.13 0.008418209198373489 264.69453068213596 0.0
-    2836.095 0.008417832109117812 264.3547458320207 0.0
-    2851.725 0.008417458906607831 264.00026735827623 0.0
-    2868.05 0.008417088445376551 263.63046804896186 0.0
-    2885.1099999999997 0.008416718554615227 263.2445000426994 0.0
-    2902.9449999999997 0.008416346026411002 262.8415224365277 0.0
-    2921.58 0.008415966585971756 262.42103995931274 0.0
-    2941.04 0.008415574164496432 261.98256324961994 0.0
-    2961.365 0.008415159759450402 261.525271899304 0.0
-    2982.58 0.00841471169033219 261.0486907769388 0.0
-    3004.71 0.008414215442875631 260.5523516119891 0.0
-    3027.79 0.008413653025905988 260.0355695567649 0.0
-    3051.8450000000003 0.008413002936618305 259.49789209109974 0.0
-    3076.895 0.008412239611602564 258.9389859371834 0.0
-    3102.96 0.008411332810557578 258.35852502737936 0.0
-    3130.0699999999997 0.008410246639659608 257.75596865621014 0.0
-    3158.25 0.008408939370292998 257.13089633202185 0.0
-    3187.51 0.008407363474598847 256.48322804430575 0.0
-    3217.87 0.008405218890420356 255.83588175027643 0.0
-    3249.3599999999997 0.008393271134003458 255.19964330883812 0.0
-    3281.99 0.008351412743288482 254.54164607206658 0.0
-    3315.77 0.008260476495526045 253.8618174159068 0.0
-    3350.72 0.008104623999478046 253.15988884466148 0.0
-    3386.8549999999996 0.00787344063905583 252.43569838883678 0.0
-    3424.1899999999996 0.0075644369243139525 251.68908967024706 0.0
-    3462.7349999999997 0.007186086619568106 250.92008938172435 0.0
-    3502.5 0.006761299010052584 250.12847128788346 0.0
-    3543.495 0.0063229503394740955 249.3142998774209 0.0
-    3585.7250000000004 0.005892523133045965 248.4776361401757 0.0
-    3629.2 0.005486081860045299 247.61844557185518 0.0
-    3673.9300000000003 0.005115471098356842 246.73669767930966 0.0
-    3719.915 0.0047865937975407405 245.8325621824419 0.0
-    3767.16 0.004497207916834608 244.9061124719276 0.0
-    3815.675 0.004235343561188026 243.93917816588527 0.0
-    3865.455 0.003992799049897532 242.9340075550911 0.0
-    3916.5 0.0037701773785292275 241.9064458549572 0.0
-    3968.8100000000004 0.003566706102255662 240.85669479320958 0.0
-    4022.385 0.0033793631035100562 239.78495669810403 0.0
-    4077.225 0.0032023886817871793 238.69143421152936 0.0
-    4133.33 0.003026657687444747 237.57633000765716 0.0
-    4190.6900000000005 0.0028381775313199797 236.4400442851121 0.0
-    4249.295 0.002621172533961453 235.28290207757698 0.0
-    4309.145 0.0023615094882103926 234.10523590260988 0.0
-    4370.23 0.0020475770133657643 232.90737521220953 0.0
-    4432.545 0.0016708338495675502 231.67880240976976 0.0
-    4496.075000000001 0.0012024566425684656 230.3946787391585 0.0
-    4560.8099999999995 0.0005801758690602509 229.09126349131424 0.0
-    4626.74 -0.00023039587268771028 227.7689693145578 0.0
-    4693.85 -0.0012211235795694937 226.42830360420388 0.0
-    4762.13 -0.0023333882072868813 225.06966783836282 0.0
-]
-# pchip vertical, not in time, w, θ, q
-a_pchip = [
-    6.25 9.606946574196332e-6 344.5726759079331 0.003622583654954105
-    24.48 4.170153541165986e-5 343.83788070682715 0.003561342988890416
-    47.875 8.9660462794051e-5 342.903293515462 0.003483122571131849
-    70.11 0.00013785620450788074 342.0171523341112 0.0034090967091053833
-    91.135 0.00018225985843190877 341.1800967199703 0.0033393784501856406
-    110.92500000000001 0.00022248103407824436 340.3950883828092 0.003274005609795846
-    129.47 0.0002597277625922707 339.8044371033823 0.0032134951490935966
-    146.775 0.0002946083545126916 339.3104050667722 0.0031574807711422753
-    162.875 0.0003272527093542365 338.857004731135 0.0031056131538170387
-    177.825 0.00035775906164403073 338.4236823850689 0.0030575017326776627
-    191.69 0.0003862105780829498 337.9556199940157 0.003012409295373976
-    204.565 0.00041273972312789846 337.5742094907327 0.002971120275078853
-    216.57 0.0004375318745889267 337.21891812934354 0.0029327133964604057
-    227.835 0.00046076510357297276 336.8858313139194 0.0028967546768672706
-    238.51 0.000482530061555519 336.5704615091353 0.002862751290772024
-    248.775 0.0005030305687002388 336.267453703888 0.0028301198798016945
-    258.83 0.0005225732399157731 335.97088194988754 0.002798218675101468
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-    2668.8450000000003 0.00842363247465228 268.0519668348617 0.00037995848013433616
-    2678.91 0.008423166401278145 267.8203498966708 0.0003766047346167834
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-    2709.915 0.00842183576177864 267.10917904576263 0.00036839901066326443
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-    2731.75 0.008420989934777683 266.61004594955716 0.0003636513835706316
-    2743.1549999999997 0.00842057656497165 266.3496772657916 0.00036119111053661325
-    2754.9449999999997 0.008420168838904526 266.0807096273862 0.0003585754542614263
-    2767.16 0.008419766585874835 265.8022344683764 0.0003557600771253701
-    2779.8450000000003 0.008419369570371621 265.51324704130707 0.0003527237059706849
-    2793.04 0.008418977768851357 265.21288090039957 0.0003494815152728756
-    2806.79 0.008418590987355281 264.9001818553346 0.0003460853084470474
-    2821.13 0.008418209198373489 264.5744077125561 0.00034255269967227756
-    2836.095 0.008417832109117812 264.2348071772109 0.00033887635312181163
-    2851.725 0.008417458906607831 263.8805209259848 0.00033504777032043856
-    2868.05 0.008417088445376551 263.5109220788324 0.0003310610606506432
-    2885.1099999999997 0.008416718554615227 263.12516322497277 0.00032690805242768854
-    2902.9449999999997 0.008416346026411002 262.72240390719213 0.0003225807647732286
-    2921.58 0.008415966585971756 262.3021491118373 0.00031807504027295177
-    2941.04 0.008415574164496432 261.86390973083536 0.0003133868836748967
-    2961.365 0.008415159759450402 261.4068657875018 0.00030850887647202547
-    2982.58 0.00841471169033219 260.93054239384895 0.00030343741423077077
-    3004.71 0.008414215442875631 260.4344715179935 0.000298169081239976
-    3027.79 0.008413653025905988 259.9179686667514 0.0002926982933451207
-    3051.8450000000003 0.008413002936618305 259.3805815476117 0.0002870220688236047
-    3076.895 0.008412239611602564 258.821955263487 0.0002811378747466814
-    3102.96 0.008411332810557578 258.24059963055265 0.0002749941841609984
-    3130.0699999999997 0.008410246639659608 257.6344378706531 0.0002685213360413485
-    3158.25 0.008408939370292998 257.00550425023556 0.000261830095691364
-    3187.51 0.008407363474598847 256.36357417007963 0.00025538033528252444
-    3217.87 0.008405218890420356 255.71484602305944 0.0002493606313795902
-    3249.3599999999997 0.008393271134003458 255.0642767336829 0.00024367843460528776
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-    3350.72 0.008104623999478046 253.0398821379219 0.00022681832714901962
-    3386.8549999999996 0.00787344063905583 252.3161377532282 0.00022077408863962588
-    3424.1899999999996 0.0075644369243139525 251.5699883310919 0.00021457273101507576
-    3462.7349999999997 0.007186086619568106 250.80146051729776 0.00020821670521181866
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-    3585.7250000000004 0.005892523133045965 248.36050377525567 0.00018824678243315883
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-    3673.9300000000003 0.005115471098356842 246.62101660639516 0.00017414528174511092
-    3719.915 0.0047865937975407405 245.72072581255748 0.000166346024237525
-    3767.16 0.004497207916834608 244.7934914745884 0.00015935392331034343
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-    3865.455 0.003992799049897532 242.82304619023446 0.0001516829739711167
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-    3968.8100000000004 0.003566706102255662 240.74351903083704 0.00014524260088811768
-    4022.385 0.0033793631035100562 239.67240883324266 0.0001418242395940265
-    4077.225 0.0032023886817871793 238.57952598581696 0.00013835916903683957
-    4133.33 0.003026657687444747 237.4650729782608 0.00013484950153396611
-    4190.6900000000005 0.0028381775313199797 236.32944970868166 0.00013129798662632854
-    4249.295 0.002621172533961453 235.17298094556014 0.00012770732862254784
-    4309.145 0.0023615094882103926 233.99727341728564 0.00012404320308549835
-    4370.23 0.0020475770133657643 232.80446442503433 0.00012025903849508776
-    4432.545 0.0016708338495675502 231.57040495650938 0.00011706131890037611
-    4496.075000000001 0.0012024566425684656 230.2907749101704 0.0001144379659749745
-    4560.8099999999995 0.0005801758690602509 228.98407044402916 0.00011194586325552476
-    4626.74 -0.00023039587268771028 227.6623211959436 0.00010935711652662116
-    4693.85 -0.0012211235795694937 226.32240509155994 0.00010674814729582555
-    4762.13 -0.0023333882072868813 224.96452770973593 0.00010412468117006716
-]
-
-
-use_pchip_interpolant = true
-if use_pchip_interpolant
-    a = a_pchip
-    suffix = "_pchip"
-else
-    suffix = ""
-end
-z = a[:, 1]
-w = a[:, 2]
-θ = a[:, 3]
-q = a[:, 4]
-
-
-outpath = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/test/")
-
-if !isdir(joinpath(outpath, "random_test"))
-    mkdir(joinpath(outpath, "random_test"))
-end
-
-using Plots
-dpi = 600
-
-#plot w/ x minor lines every 250m
-plot(
-    w,
-    z,
-    label = "w",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "w (K)",
-    ylabel = "Height (m)",
-    title = "w (m/s?)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-# vertical line at 0
-vline!([0], label = "w = 0", color = "black", linestyle = :dash)
-
-savefig(joinpath(outpath, "random_test", "w$(suffix).png"))
-
-dz = z[2:end] .- z[1:(end - 1)]
-z_mid = z[1:(end - 1)] .+ dz ./ 2
-plot(
-    dz,
-    z_mid,
-    label = "dz",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "dz (m)",
-    ylabel = "Height (m)",
-    title = "dz (m)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "dz$(suffix).png"))
-
-dw = w[2:end] .- w[1:(end - 1)]
-dwdz = dw ./ dz
-plot(
-    -dwdz,
-    z_mid,
-    label = "-dw/dz",
-    legend = :bottomright,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "-dw/dz (m/s/m)",
-    ylabel = "Height (m)",
-    title = "-dw/dz (m/s/m)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "minus_dwdz$(suffix).png"))
-
-dwdz_times_dz = dwdz .* dz
-plot(
-    -dwdz_times_dz,
-    z_mid,
-    label = "-dw/dz * dz",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "-dw/dz * dz (m/s)",
-    ylabel = "Height (m)",
-    title = "-dw/dz * dz (m/s)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "minus_dwdz_times_dz$(suffix).png"))
-
-
-plot(
-    θ,
-    z,
-    label = "θ",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "θ (K)",
-    ylabel = "Height (m)",
-    title = "θ (K)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "θ$(suffix).png"))
-
-
-plot(
-    q,
-    z,
-    label = "q",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "q (kg/kg)",
-    ylabel = "Height (m)",
-    title = "q (kg/kg)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "q$(suffix).png"))
-
-
-
-wq = w .* q
-plot(
-    wq,
-    z,
-    label = "wq",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "wq (K kg/kg)",
-    ylabel = "Height (m)",
-    title = "wq (K kg/kg)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "wq$(suffix).png"))
-
-dwq_dz = (wq[2:end] .- wq[1:(end - 1)]) ./ dz
-plot(
-    -dwq_dz,
-    z_mid,
-    label = "-dwq/dz",
-    legend = :bottomright,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "-dwq/dz (K kg/kg/m)",
-    ylabel = "Height (m)",
-    title = "-dwq/dz (K kg/kg/m)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "minus_dwq_dz$(suffix).png"))
-
-wθ = w .* θ
-plot(
-    wθ,
-    z,
-    label = "wθ",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "wθ (K K)",
-    ylabel = "Height (m)",
-    title = "wθ (K K)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "wθ$(suffix).png"))
-
-dwθ_dz = (wθ[2:end] .- wθ[1:(end - 1)]) ./ dz
-plot(
-    -dwθ_dz,
-    z_mid,
-    label = "-dwθ/dz",
-    legend = :bottomright,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "-dwθ/dz (K K/m)",
-    ylabel = "Height (m)",
-    title = "-dwθ/dz (K K/m)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "minus_dwθ_dz$(suffix).png"))
-
-
-qq = [
-    -2.9979330907619352e-5,
-    -8.744371239134406e-5,
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-    -0.00220670876166807,
-    -0.002214844412839924,
-    -0.002224046805931156,
-    -0.0022338007559707003,
-    -0.002243600884582116,
-    -0.002253401013193531,
-    -0.0022632011418049457,
-    -0.002273001270416361,
-    -0.002282801399027776,
-    -0.002292601527639191,
-    -0.002302401656250606,
-    -0.0023122017848620216,
-    -0.002322001913473436,
-    -0.0023318020420848512,
-    -0.002341602170696266,
-    -0.0023514022993076813,
-    -0.002361202427919096,
-    -0.0023710025565305114,
-    -0.0023808026851419267,
-    -0.002390602813753341,
-    -0.0024004029423647564,
-    -0.0024102030709761716,
-    -0.0024200034385597102,
-    -0.002429890947320584,
-    -0.0024401074882628403,
-    -0.0024507753003777935,
-    -0.002461853192523694,
-    -0.0024731268828756424,
-    -0.002483813639918251,
-    -0.002492816252489583,
-    -0.002499656662384614,
-    -0.0025045437257438232,
-    -0.0025083267671965424,
-    -0.0025116253370591523,
-    -0.0025145204657499864,
-    -0.002517081445466183,
-    -0.002519381137403379,
-    -0.0025215027190615405,
-    -0.002523552158027414,
-    -0.0025256441707118193,
-    -0.0025278631326103636,
-    -0.0025302621861442195,
-    -0.002532877433227971,
-    -0.002535712207629795,
-    -0.00253872576181861,
-    -0.0025418743959836954,
-    -0.0025451575871643832,
-    -0.002548586548445306,
-    -0.0025521680076772443,
-    -0.002555908692710979,
-    -0.002559819816631142,
-    -0.002563908107288514,
-    -0.00256817804991695,
-    -0.002572636372367228,
-    -0.0025772942877239817,
-    -0.0025821517959872123,
-    -0.0025872201102415523,
-    -0.0025925037157208553,
-    -0.0025980093402759017,
-    -0.0026037549000087774,
-    -0.002609836567273308,
-    -0.0026162652721160853,
-    -0.0026227113055602843,
-    -0.00262871209838103,
-    -0.0026343126384142045,
-    -0.002639560537882105,
-    -0.002644743590921885,
-    -0.002650209103971785,
-    -0.0026559678176568163,
-    -0.0026619260831940933,
-    -0.0026680806324585714,
-    -0.0026744314654502505,
-    -0.002680981826528259,
-    -0.002687731715692595,
-    -0.002694682755122824,
-    -0.0027018381865532375,
-    -0.0027095336044658295,
-    -0.0027177162723542063,
-    -0.0027233201006597197,
-    -0.0027267829197218244,
-    -0.0027294558555150967,
-    -0.0027323607659227485,
-    -0.0027354678318175845,
-    -0.0027386495284904035,
-    -0.0027419051771611514,
-    -0.0027452353647504477,
-    -0.002748638330496436,
-    -0.0027521175938509715,
-    -0.002755804088711958,
-    -0.0027593042876840612,
-    -0.0027619409180269466,
-    -0.0027641181825309308,
-    -0.002766388390618102,
-    -0.0027687434019555853,
-    -0.002771140188900077,
-    -0.0027735780433904423,
-]
-plot(
-    qq,
-    z,
-    label = "q",
-    legend = :bottomleft,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "q (kg/kg)",
-    ylabel = "Height (m)",
-    title = "q (kg/kg)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "broqen_q.png"))
-
-
-# w_times_dqdz
-dqdz = (qq[2:end] .- qq[1:(end - 1)]) ./ dz
-w_mid = (w[1:(end - 1)] .+ w[2:end]) ./ 2
-plot(
-    dqdz .* w_mid,
-    z_mid,
-    label = "dqdz * w",
-    legend = :bottomright,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "dqdz * w (kg/kg m/s)",
-    ylabel = "Height (m)",
-    title = "dqdz * w (kg/kg m/s)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "w_times_dqdz$(suffix).png"))
-
-# w_times_dθdz
-dθdz = (θ[2:end] .- θ[1:(end - 1)]) ./ dz
-w_mid = (w[1:(end - 1)] .+ w[2:end]) ./ 2
-plot(
-    dθdz .* w_mid,
-    z_mid,
-    label = "dθdz * w",
-    legend = :bottomright,
-    dpi = dpi,
-    marker = :circle,
-    markersize = 1.0,
-    markerstrokewidth = 0.2,
-    xlabel = "dθdz * w (K m/s)",
-    ylabel = "Height (m)",
-    title = "dθdz * w (K m/s)",
-    # ylim = (ymin, ymax),
-    minorgrid = true,
-)
-savefig(joinpath(outpath, "random_test", "w_times_dθdz$(suffix).png"))
diff --git a/test/runtests.jl b/test/runtests.jl
index c9b6bfe..bdcb92b 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -28,6 +28,50 @@ import Thermodynamics.Parameters as TDP
     # T_new_z_init  = SSCF.get_data_new_z_t("T", new_z,"lev","time"; data, thermo_params,  initial_condition=true)
 
     # these no longer work w/o output_data downloaded
+
+    new_zs = (nothing, collect(1:100:4000))
+
+    initial_conditions = (false, true)
+    surfaces = (nothing, "reference_state", "surface_conditions")
+    use_LES_output_for_zs = (false, true)
+    return_old_zs = (false, true)
+
+    setups = Iterators.product(
+        SSCF.flight_numbers,
+        SSCF.forcing_types,
+        new_zs,
+        initial_conditions,
+        surfaces,
+        use_LES_output_for_zs,
+        return_old_zs,
+    )
+
+    n_setups = length(setups)
+    for (i, setup) in enumerate(setups)
+        @info "Testing combination $i/$n_setups"
+        flight_number, forcing_type, new_z, initial_condition, surface, use_LES_output_for_z, return_old_z = setup
+        data = SSCF.open_atlas_les_input(flight_number, forcing_type; open_files = false)
+        # check files all exist
+        # if isfile(data[forcing_type]) && isfile(data[:grid_data])
+        if (!isnothing(data[forcing_type]) && isfile(data[forcing_type])) &&
+           (!isnothing(data[:grid_data]) && isfile(data[:grid_data]))
+            SSCF.process_case(
+                flight_number;
+                forcing_type = forcing_type,
+                thermo_params = thermo_params,
+                new_z = new_z,
+                initial_condition = initial_condition,
+                surface = surface,
+                use_LES_output_for_z = use_LES_output_for_z,
+                return_old_z = return_old_z,
+                fail_on_missing_data = false,
+            )
+            @test true # if no error, test passes
+        else
+            @warn "Files for flight $flight_number do not exist"
+        end
+    end
+
     data = SSCF.process_case(9; thermo_params = thermo_params, use_LES_output_for_z = false)
     @show(data)
 
diff --git a/test/test_run.jl b/test/test_run.jl
deleted file mode 100644
index 641552b..0000000
--- a/test/test_run.jl
+++ /dev/null
@@ -1,1286 +0,0 @@
-## Run test on cases and plot relative to LES
-
-FT = Float64
-forcing_type = :obs_data
-
-# flight_numbers = 9
-flight_numbers = [1, 9, 10, 12, 13]
-# flight_numbers = 1
-
-
-# convert flight_number to array if it's not already
-if isa(flight_numbers, Int)
-    flight_numbers = [flight_numbers]
-end
-
-
-
-
-if forcing_type == :obs_data
-    forcing_str = "Obs"
-elseif forcing_type == :ERA5_data
-    forcing_str = "ERA5"
-else
-    error("forcing_type must be :obs_data or :ERA5_data")
-end
-
-
-reload_environment = true
-if reload_environment | !isdefined(Main, :TurbulenceConvection)
-    using Pkg
-    # Pkg.activate(expanduser("~/Research_Schneider/CliMa/TurbulenceConvection.jl/integration_tests/")) # this break precomilation of TC.jl for some reason...
-    # Pkg.develop(path = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl"))
-    # Pkg.activate(expanduser("~/Research_Schneider/CliMa/TurbulenceConvection.jl/"))
-    # Pkg.activate(expanduser("~/Research_Schneider/CliMa/TurbulenceConvection.jl/integration_tests/"))
-    # Pkg.develop(path = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl"))
-
-
-    # using Revise
-    # Pkg.resolve()
-    # Pkg.instantiate()
-
-    using Revise
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/TurbulenceConvection.jl/"))
-    using Revise
-    # Pkg.develop(path = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl"))
-    Pkg.resolve()
-    Pkg.instantiate()
-
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/TurbulenceConvection.jl/integration_tests"))
-    using Revise
-    # Pkg.develop(path = expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl"))
-    Pkg.resolve()
-    Pkg.instantiate()
-    using Revise
-    using TurbulenceConvection
-    tc = pkgdir(TurbulenceConvection)
-    include(joinpath(tc, "driver", "main.jl"))
-    include(joinpath(tc, "driver", "generate_namelist.jl"))
-    # includet(joinpath(tc, "driver", "main.jl"))
-    # includet(joinpath(tc, "driver", "generate_namelist.jl"))
-end
-
-# ------------------ #
-reload_SSCF = false
-if reload_SSCF | !isdefined(Main, :SOCRATESSingleColumnForcings)
-    using Pkg
-    using Revise
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/test"))
-    import CLIMAParameters as CP # use CLIMAParameters = "0.7, 0.8, 0.9, 0.10"
-    # import ClimaParams as CPP # would using this trouble w/ TC.jl? it's a different uuid technically..., use ClimaParams = "0.10"
-    import Thermodynamics as TD
-    import Thermodynamics.Parameters as TDP
-    # FT = Float64
-
-    toml_dict = CP.create_toml_dict(FT; dict_type = "alias") # CP 0.7 and below, Thermodynamics 0.11 and above
-    aliases = string.(fieldnames(TDP.ThermodynamicsParameters))
-    param_pairs = CP.get_parameter_values!(toml_dict, aliases, "Thermodynamics")
-    thermo_params = TDP.ThermodynamicsParameters{FT}(; param_pairs...)
-    Pkg.activate(expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/"))
-    include(
-        "/home/jbenjami/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/src/SOCRATESSingleColumnForcings.jl",
-    )
-end
-# ------------------ #
-
-for flight_number in flight_numbers
-
-    setup_environment = true # leave true
-    if setup_environment
-        case_name = "SOCRATES_RF" * string(flight_number, pad = 2) * "_" * forcing_str * "_data"
-
-        if !@isdefined(NameList) # For if we didn't use reload_enviornment (I'm not sure tbf if this also checks for modules lol, I guess we'll find out)
-            @info("NameList not defined by module, defining now as simple Dict()") # This allows plotting even if you haven't gone through the environment loading by allowing you to get the simname/uuid etc in namelist 
-            namelist = Dict{String, Union{Dict, NamedTuple}}(
-                "time_stepping" => Dict(),
-                "stats_io" => Dict(),
-                "microphysics" => Dict(),
-                "user_args" => Dict(),
-                "user_aux" => Dict(),
-                "turbulence" => Dict("EDMF_PrognosticTKE" => Dict()),
-                "thermodynamics" => Dict(),
-                "output" => Dict(),
-                "meta" => Dict("simname" => case_name, "uuid" => ""),
-            )
-        else
-            @info("NameList defined by module, using NameList.default_namelist()")
-            namelist = NameList.default_namelist(
-                case_name,
-                root = "./",  # controls where the namelist gets written if write=true
-                # write = parsed_args["write_namelist"], # controls if the namelist gets written (I'm not sure if this is repetitive -- does it get written again after the namelist overwrite? I think this is the wrong namelist that kept getting written when I ran things earlier separate from the results...)
-                write = false, # don't write the namelist because we only care to write the later one once we've done our overwrites since that's the one that actually runs, though idk where that one gets written tbh...
-            )
-        end
-
-        namelist["time_stepping"]["dt_min"] = 0.5
-        namelist["time_stepping"]["dt_max"] = 2.0
-        namelist["time_stepping"]["t_max"] = 3600.0 * 4.0
-        # namelist["stats_io"]["frequency"] = 600.0
-        namelist["stats_io"]["frequency"] = 300.0
-
-        supersat_type = :Base
-        namelist["microphysics"]["τ_sub_dep"] = 100000.0
-        namelist["microphysics"]["τ_cond_evap"] = 1.0
-        namelist["user_args"] = (; use_supersat = supersat_type, τ_use = :morrison_milbrandt_2015_style)
-        # namelist["user_args"] = (;use_supersat=supersat_type, τ_use=:morrison_milbrandt_2015_style_exponential_part_only) 
-        # namelist["user_args"] = (;use_supersat=supersat_type, τ_use=:standard) 
-
-
-        namelist["user_aux"] = Dict()
-        # namelist["user_aux"]["initial_profile_updraft_area"] = 0.33 # i think either dict or named tuple is fine, we dispatch depending... # doesn't seem to work anyway...
-
-
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["updraft_mixing_frac"] = 0.6
-        # ("turbulence", "EDMF_PrognosticTKE", "max_area", FT(.3)), # stability limiting...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["surface_area_bc"] = "Prognostic" # unstable w/o  setting other params (didn't help lol, was 0 at sfc)
-        # 
-
-        # surface area  
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["max_area"] = FT(0.5) # stability (maybe we need to use the limiter instead tho to not get flat cloud tops?)
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["min_area"] = FT(1e-10) # stability (maybe we need to use the limiter instead tho to not get flat cloud tops?)
-
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["min_area"] = FT(0.3) # testing
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["surface_area"] = 0.3
-
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["updraft_number"] = 2 # testing lol
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["surface_area"] = [0.25, 0.1] # testing lol, maybe they'll combine nicely
-
-
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["limit_min_area"] = true # testing
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["min_area_limiter_scale"] = 5 # testing strong detrainment...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["min_area_limiter_power"] = 2000 # testing strong detrainment...
-
-
-        # # testing broad strong detrainment throughout (kills updraft)
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_scale"] = 5 # testing strong detrainment...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_power"] = 4 # too 
-
-        # # testing broad weak detrainment throughout (still killed very low)
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_scale"] = 1 # testing strong detrainment...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_power"] = 3 # too 
-
-        # # testing broad very weak detrainment throughout (leads to instability no matter what updraft area is seemingly)
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_scale"] = .1 # testing strong detrainment...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_power"] = 10 # too
-
-        # # testing weak detrainment until just before limit (kills updraft very low)
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_scale"] = 20 # testing strong detrainment...
-        # namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_power"] = 30 # too 
-
-        # testing mild detrainment until through limit then strong (runs slower bc updraft?) (big spike at top but at least makes it there -- runs super slow in adaptive mode)...
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_scale"] = 1 # testing strong detrainment...
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["area_limiter_power"] = 10 # too 
-
-
-        # careful, we're getting qt + precip right but not qt, probably bc we're raining/snowing out our cloud lol... (the snow timescale is fast)
-        namelist["microphysics"]["τ_acnv_rai"] = 25000.0
-        namelist["microphysics"]["τ_acnv_sno"] = 10000.0
-        namelist["microphysics"]["q_liq_threshold"] = 1e-4
-        namelist["microphysics"]["q_ice_threshold"] = 1e-5
-
-
-
-
-        # namelist["thermodynamics"]["potential_temperature_reference_pressure"] = 985. * 100 # try changing this...
-
-        namelist["thermodynamics"]["moisture_model"] = "nonequilibrium"
-        namelist["thermodynamics"]["sgs"] = "mean"
-
-        namelist["output"]["output_root"] =
-            expanduser("~/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/test")
-        namelist["meta"]["uuid"] = "" # no uuid
-        uuid = string(namelist["meta"]["uuid"])
-        simname = namelist["meta"]["simname"]
-        @info("simname", simname)
-        outpath = joinpath(namelist["output"]["output_root"], "Output.$simname.$uuid") # no uuid
-        @info("outpath", outpath)
-        simulation_outpath = joinpath(outpath, "stats/Stats." * case_name * ".nc")
-        # simulation_outpath = joinpath(outpath, "stats/Stats."*case_name*"_alt.nc") # testing an old one before any recent changes
-
-
-        # output_relpath   =  "Output."*case_name*".out/stats/Stats."*case_name*".nc" # could try Glob.jl, see https://discourse.julialang.org/t/rdir-search-recursive-for-files-with-a-given-name-pattern/75605/20
-        # simulation_outpath = joinpath(namelist["output"]["output_root"], output_relpath), 
-
-        # @info(namelist)
-
-    end
-
-
-    run_simulation = true
-    if run_simulation
-        main1d(namelist)
-    end
-
-
-
-    SOCRATES_truth_path = "/home/jbenjami/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/Data/Atlas_LES_Profiles/Output_Data/"
-    truth_file = joinpath(
-        SOCRATES_truth_path,
-        "RF" * string(flight_number, pad = 2) * "_" * forcing_str * "_SOCRATES_128x128_100m_10s_rad10_vg_M2005_aj.nc",
-    )
-
-    SOCRATES_input_path = "/home/jbenjami/Research_Schneider/CliMa/SOCRATESSingleColumnForcings.jl/Data/Atlas_LES_Profiles/Input_Data/"
-
-    LES_forcing_str = forcing_str == "Obs" ? "obs" : "ERA5"
-    LES_forcing_suffix = forcing_str == "Obs" ? ".nc" : "_mar18_2022.nc"
-    LES_input_file =
-        "RF" * string(flight_number, pad = 2) * "_" * LES_forcing_str * "-based_SAM_input" * LES_forcing_suffix
-
-
-    # ------------------ #
-    initial_condition = true
-    SSCFout = Main.SOCRATESSingleColumnForcings.process_case(
-        flight_number;
-        thermo_params = thermo_params,
-        initial_condition = initial_condition,
-    )
-    z_SSCF = Main.SOCRATESSingleColumnForcings.open_atlas_les_input(flight_number)[:grid_data]
-
-    # ------------------ #
-
-    make_plots = true
-    # ============================================================================================================================================================= #
-    # create figure
-    simul_ind = 100 # time index to plot
-    # ============================================================================================================================================================= #
-
-    if make_plots
-        # Read output file from SCM run and plot
-
-
-        using Dierckx
-        function pyinterp(x, xp, fp; bc = "error")
-            spl = Dierckx.Spline1D(xp, fp; k = 1, bc = bc)
-            return spl(vec(x))
-        end
-
-        using Plots
-        using NCDatasets
-        # create directory if doesn't exist
-        if !isdir(joinpath(outpath, "Figures"))
-            mkdir(joinpath(outpath, "Figures"))
-        end
-
-        truth_data = NCDatasets.Dataset(truth_file, "r")
-        simul_data = NCDatasets.Dataset(simulation_outpath, "r")
-        z_simul = simul_data.group["profiles"]["zc"][:] # should be same for both but the truth one doesn't match the file atlas gave...
-        z_simul_f = simul_data.group["profiles"]["zf"][:] # should be same for both but the truth one doesn't match the file atlas gave...
-
-        z_truth = truth_data["z"][:] # should be same for both but the truth one doesn't match the file atlas gave...
-        z = z_truth
-
-        lt = length(simul_data.group["timeseries"]["t"])
-        if lt < simul_ind
-            @warn(
-                "Simulation index $simul_ind is out of bounds for simulation data of time index length $lt, reverting to $lt"
-            )
-            simul_ind = lt
-        end
-
-
-        t_simul = simul_data.group["timeseries"]["t"][:]
-        t_simul_ind = t_simul[simul_ind]
-
-        t_truth = truth_data["time"][:]
-        t_truth = (t_truth .- t_truth[1]) .* (24 * 3600) # make it relative to start time
-        truth_ind = argmin(abs.(t_truth .- t_simul_ind))
-        t_truth_ind = t_truth[truth_ind]
-
-
-        LES_in_data = NCDatasets.Dataset(joinpath(SOCRATES_input_path, LES_input_file), "r") # technically there's some time editing we should do for this but we can put it off for obs
-
-
-        # ============================================================================================================================================================= #
-        # test box
-        # import CLIMAParameters as CP
-        # # import Thermodynamics as TD
-        # TD = TC.TD
-        # TDP = TC.TD.Parameters
-
-        # FT = Float64
-        # toml_dict = CP.create_toml_dict(FT; dict_type = "alias")
-        # aliases = string.(fieldnames(TDP.ThermodynamicsParameters))
-        # param_pairs = CP.get_parameter_values!(toml_dict, aliases, "Thermodynamics")
-        # thermo_params = TDP.ThermodynamicsParameters{FT}(; param_pairs...)
-
-        # Tg_simul_start = simul_data.group["timeseries"]["Tsurface"][1]
-        # Tg_simul_start = simul_data.group["profiles"]["temperature_mean"][:,1][1]
-        # pg = simul_data.group["reference"]["p_f"][:][1] # no timeseries
-        # ρg = TD.air_density(thermo_params,Tg_simul_start,pg)
-        # q_sfc = TD.q_vap_saturation_generic(thermo_params, Tg_simul_start, ρg, TD.Liquid()) # surface specific humidity
-        # q_sfc = TD.q_vap_saturation_from_pressure(thermo_params,0. , pg, Tg_simul_start, TD.PhaseEquil) # surface specific humidity
-
-        # ============================================================================================================================================================= #
-
-
-        # figure out simulation time we're plotting and what time that is in the truth_data (start should be same...)
-
-        ### temperature ###
-        data_simul = simul_data.group["profiles"]["temperature_mean"][:, simul_ind]
-        data_truth = truth_data["TABS"][:, truth_ind]
-
-        ymax = 4000.0
-        # ymax = nothing
-        ymax = 4800
-        ymin = -100.0
-        ymaxs = Dict(1 => 4800, 9 => 4800, 10 => 4800, 12 => 3000, 13 => 3000)
-        dpi = 600
-        minorgrid = true
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # temperature
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :topright,
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.2,
-            xlabel = "T (K)",
-            ylabel = "Height (m)",
-            title = "Temperature (K)",
-            ylim = (ymin, ymaxs[flight_number]),
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(
-            data_simul,
-            z_simul,
-            label = "Simulation",
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.2,
-        ) # add simulation data to same plot
-        # vertical line at 5.22 + 273.15 degrees
-        # surface temp dot 
-        plot!(
-            simul_data.group["timeseries"]["Tsurface"][[simul_ind]],
-            [0],
-            label = "Surface Temp",
-            seriestype = :scatter,
-            markersize = 5,
-            markercolor = :red,
-        )
-        plot!(
-            truth_data["SST"][[truth_ind]],
-            [0],
-            label = "SST",
-            seriestype = :scatter,
-            markersize = 5,
-            markercolor = :blue,
-        )
-
-
-
-        savefig(joinpath(outpath, "Figures", "temperature.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # temperature diff
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth, bc = "extrapolate"),
-            z_simul,
-            label = "Truth",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "T diff (K)",
-            ylabel = "Height (m)",
-            title = "Temperature (K) diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "temperature_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-        # temperature on pressure grid
-        data_simul = simul_data.group["profiles"]["temperature_mean"][:, simul_ind]
-        data_truth = truth_data["TABS"][:, truth_ind]
-
-        p_truth = truth_data["PRES"][:, truth_ind]
-        p_truth_alt = truth_data["p"][:]
-
-        p_t = plot(
-            data_truth,
-            p_truth,
-            label = "Truth",
-            legend = :topright,
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.4,
-            markerstrokewidth = 0.05,
-            xlabel = "T (K)",
-            ylabel = "Pressure (Pa)",
-            title = "Temperature (K)",
-            yflip = true,
-            ylim = (500, 1020),
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(
-            data_simul,
-            simul_data.group["reference"]["p_c"] / 100.0,
-            label = "Simulation",
-            marker = :circle,
-            markersize = 0.4,
-            markerstrokewidth = 0.05,
-        ) # add simulation data to same plot
-
-        p_s = plot!(
-            data_truth,
-            p_truth_alt,
-            label = "Truth alt",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.25,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :blue,
-        )
-
-
-        input_T_L = LES_in_data["T"][1, 1, :, 1][:]
-        input_p_L = LES_in_data["lev"][:] / 100
-
-        input_T_L = input_T_L[input_p_L .> minimum(p_truth)]
-        input_p_L = input_p_L[input_p_L .> minimum(p_truth)]
-
-        p_s = plot!(
-            input_T_L,
-            input_p_L,
-            label = "Input",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.75,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :red,
-        )
-
-        savefig(joinpath(outpath, "Figures", "temperature_p.png")) # save to file
-
-
-        # --------------------------------------------------------------------------------------------- #
-
-        ### qt_mean ###
-        data_simul = simul_data.group["profiles"]["qt_mean"][:, simul_ind]
-        data_truth = truth_data["QT"][:, truth_ind] ./ 1000 # probably is mixing ratio
-        data_truth = data_truth ./ (1 .+ data_truth) # convert to specific humidity
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomleft,
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.05,
-            linewidth = 0.25,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qt (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QT (kg/kg)",
-            minorgrid = minorgrid,
-        )
-
-        if initial_condition
-            SSCFout_q = SSCFout.qt_nudge
-        else
-            SSCFout_q = (x -> x([0])[1]).(SSCFout.qt_nudge)
-        end
-
-        p_s = plot!(
-            data_simul,
-            z_simul,
-            label = "Simulation",
-            marker = :square,
-            markersize = 0.5,
-            markerstrokewidth = 0.05,
-            linewidth = 0.25,
-            color = :orange,
-        ) # add simulation data to same plot
-        p_s = plot!(
-            SSCFout_q,
-            z_SSCF,
-            label = "Nudging",
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.05,
-            linewidth = 0.25,
-            color = :green,
-        ) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "qt.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # qt diff 
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth, bc = "extrapolate"),
-            z_simul,
-            label = "diff",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qt diff (K)",
-            ylabel = "Height (m)",
-            title = "qt_diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "qt_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-        # qt on pressure grid
-        data_simul = simul_data.group["profiles"]["qt_mean"][:, simul_ind]
-        data_truth = truth_data["QT"][:, truth_ind] / 1000.0
-
-        p_truth = truth_data["PRES"][:, truth_ind]
-        p_truth_alt = truth_data["p"][:]
-
-        p_t = plot(
-            data_truth,
-            p_truth,
-            label = "Truth",
-            legend = :topright,
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.4,
-            markerstrokewidth = 0.05,
-            xlabel = "qt (kg/kg)",
-            ylabel = "Pressure (Pa)",
-            title = "Temperature (K)",
-            yflip = true,
-            ylim = (500, 1020),
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(
-            data_simul,
-            simul_data.group["reference"]["p_c"] / 100.0,
-            label = "Simulation",
-            marker = :circle,
-            markersize = 0.4,
-            markerstrokewidth = 0.05,
-        ) # add simulation data to same plot
-
-        p_s = plot!(
-            data_truth,
-            p_truth_alt,
-            label = "Truth alt",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.25,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :blue,
-        )
-
-
-        input_q_L = LES_in_data["q"][1, 1, :, 1][:]
-        input_p_L = LES_in_data["lev"][:] / 100
-
-        input_q_L = input_q_L[input_p_L .> minimum(p_truth) - 50]
-        input_p_L = input_p_L[input_p_L .> minimum(p_truth) - 50]
-
-        p_s = plot!(
-            input_q_L,
-            input_p_L,
-            label = "Input",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.75,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :red,
-        )
-
-
-        # --------------------------------------------------------------------------------------------- #
-
-
-        ### ql_mean ### (need to figure out indexing here in particular..., interpolate in t)
-        ql_simul_ind = simul_ind
-        ql_truth_ind = truth_ind
-        # ql_ind = 1
-        data_simul = simul_data.group["profiles"]["ql_mean"][:, ql_simul_ind]
-        data_truth = truth_data["QCL"][:, ql_truth_ind] ./ 1000
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "ql (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QL (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation") # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "ql.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth, bc = "extrapolate"),
-            z_simul,
-            label = "diff",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "ql diff (K)",
-            ylabel = "Height (m)",
-            title = "ql_diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "ql_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        ### qi_mean ### (need to figure out indexing here in particular..., interpolate in t)
-        qi_simul_ind = simul_ind
-        qi_truth_ind = truth_ind
-        # ql_ind = 1
-        data_simul = simul_data.group["profiles"]["qi_mean"][:, qi_simul_ind]
-        data_truth = truth_data["QCI"][:, qi_truth_ind] ./ 1000
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qi (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QI (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation") # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "qi.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth; bc = "extrapolate"),
-            z_simul,
-            label = "diff",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qi diff (K)",
-            ylabel = "Height (m)",
-            title = "qi_diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "qi_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        ### qc_mean ### (need to figure out indexing here in particular..., interpolate in t)
-        qc_simul_ind = simul_ind
-        qc_truth_ind = truth_ind
-        # ql_ind = 1
-        data_simul =
-            simul_data.group["profiles"]["ql_mean"][:, qc_simul_ind] +
-            simul_data.group["profiles"]["qi_mean"][:, qc_simul_ind]
-        data_truth = truth_data["QCL"][:, qc_truth_ind] ./ 1000 + truth_data["QCI"][:, qc_truth_ind] ./ 1000
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qc (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QC (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation") # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "qc.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth; bc = "extrapolate"),
-            z_simul,
-            label = "diff",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qc diff (K)",
-            ylabel = "Height (m)",
-            title = "qc_diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "qc_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # liquid potential Temp
-        data_simul = simul_data.group["profiles"]["thetal_mean"][:, simul_ind]
-        data_truth = truth_data["THETAL"][:, truth_ind]
-
-
-
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            dpi = dpi * 4,
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.2,
-            linewidth = 0.25,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "theta_l (K)",
-            ylabel = "Height (m)",
-            title = "theta_l (K)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(
-            data_simul,
-            z_simul,
-            label = "Simulation",
-            marker = :square,
-            markersize = 0.5,
-            markerstrokewidth = 0.2,
-            linewidth = 0.25,
-            color = :orange,
-        ) # add simulation data to same plot
-
-        if initial_condition
-            SSCFout_θ = SSCFout.H_nudge
-        else
-            SSCFout_θ = (x -> x([0])[1]).(SSCFout.H_nudge)
-        end
-
-        # @info("z_SSCF", length(z_SSCF))
-        # @info("z_simul", length(z_simul))
-        # @info("SSCFout_θ", length(SSCFout_θ))
-        plot!(
-            SSCFout_θ,
-            z_SSCF,
-            label = "Nudging",
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.05,
-            linewidth = 0.25,
-            color = :green,
-        ) # add simulation data to same plot
-
-        # data_simul_θ_offset = (data_simul[1:end-1] + data_simul[2:end])/2
-        # plot!(data_simul_θ_offset, z_simul[2:end], label = "simulation offset", marker = :cross, markersize = .5,  markerstrokewidth = 0.05, linewidth=0.05, color=:purple) # add simulation data to same plot
-
-        # SSCFout_θ_offset = (SSCFout_θ[1:end-1] + SSCFout_θ[2:end])/2
-        # z_offset =  (z_simul[1:end-1] + z_simul[2:end])/2
-
-        # @info("length sscfoffest", length(SSCFout_θ_offset))
-        # @info("length zoffset", length(z_offset))
-        # plot!(SSCFout_θ_offset[2:end], z_offset[2:end], label = "SSCFout_θ offset", marker = :cross, markersize = .5,  markerstrokewidth = 0.05, linewidth=0.05, color=:red) # add simulation data to same plot
-
-        # plot!(SSCFout_θ, z_simul_f[2:end], label = "SSFc offset on simulf", marker = :square, markersize = .5,  markerstrokewidth = 0.05, linewidth=0.05, color=:brown) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "theta_l.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        p_t = plot(
-            data_simul .- pyinterp(z_simul, z_truth, data_truth; bc = "extrapolate"),
-            z_simul,
-            label = "diff",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "theta_l diff (K)",
-            ylabel = "Height (m)",
-            title = "thetal_diff",
-            minorgrid = minorgrid,
-        )
-        savefig(joinpath(outpath, "Figures", "theta_l_diff.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # ql and qi combined on separate axes
-        data_simul_ql = simul_data.group["profiles"]["ql_mean"][:, simul_ind]
-        data_truth_ql = truth_data["QCL"][:, truth_ind] ./ 1000
-
-        data_simul_qi = simul_data.group["profiles"]["qi_mean"][:, simul_ind]
-        data_truth_qi = truth_data["QCI"][:, truth_ind] ./ 1000
-
-        p_t = plot(
-            data_truth_ql,
-            z_truth,
-            label = "Truth liq",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            color = :green,
-            xlabel = "q (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QL and QI (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul_ql, z_simul, label = "Simulation liq", color = :lime) # add simulation data to same plot
-
-        # add ice data on same plot with twin x axis
-        xaxis2 = Plots.twiny()
-        p_s = plot!(
-            xaxis2,
-            data_truth_qi,
-            z_truth,
-            label = "Truth ice",
-            ylim = (ymin, ymaxs[flight_number]),
-            legend = :bottom,
-            color = :blue,
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(xaxis2, data_simul_qi, z_simul, label = "Simulation ice", color = :cyan) # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "ql_qi.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # ql, qi updraft/env
-        data_simul_ql_up = simul_data.group["profiles"]["updraft_ql"][:, simul_ind]
-        data_simul_qi_up = simul_data.group["profiles"]["updraft_qi"][:, simul_ind]
-        data_simul_ql_env = simul_data.group["profiles"]["env_ql"][:, simul_ind]
-        data_simul_qi_env = simul_data.group["profiles"]["env_qi"][:, simul_ind]
-
-        plot(
-            data_simul_ql_up,
-            z_simul,
-            label = "Updraft liq",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            color = :green,
-            xlabel = "q (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QL and QI (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        plot!(data_simul_ql_env, z_simul, label = "Environment liq", color = :green, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_qi_up, z_simul, label = "Updraft ice", color = :blue) # add simulation data to same plot
-        plot!(data_simul_qi_env, z_simul, label = "Environment ice", color = :blue, linestyle = :dash) # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "ql_qi_updraft_env.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # updraft and environmental temperature
-        data_simul_up = simul_data.group["profiles"]["updraft_temperature"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_temperature"][:, simul_ind]
-        data_simul = simul_data.group["profiles"]["temperature_mean"][:, simul_ind]
-
-        data_truth = truth_data["TABS"][:, truth_ind]
-
-        p_t = plot(
-            data_simul_up,
-            z_simul,
-            label = "Updraft",
-            legend = :topright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            color = :red,
-            xlabel = "T (K)",
-            ylabel = "Height (m)",
-            title = "Updraft and Environmental Temperature (K)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-        p_s = plot!(data_simul, z_simul, label = "Simulation", color = :brown, xlim = (250, 280)) # add simulation data to same plot
-
-        plot!(
-            simul_data.group["timeseries"]["Tsurface"][[simul_ind]],
-            [0],
-            label = "Surface Temp",
-            seriestype = :scatter,
-            markersize = 5,
-            markercolor = :red,
-        )
-        plot!(
-            truth_data["SST"][[truth_ind]],
-            [0],
-            label = "SST",
-            seriestype = :scatter,
-            markersize = 2,
-            markercolor = :blue,
-        )
-        plot!(data_truth, z_truth, label = "Truth mean", color = :green) # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "updraft_env_temp.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # updraft and environmental temperature start and now
-        data_simul_up = simul_data.group["profiles"]["updraft_temperature"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_temperature"][:, simul_ind]
-        data_truth = truth_data["TABS"][:, truth_ind]
-
-        data_simul_up_start = simul_data.group["profiles"]["updraft_temperature"][:, 1]
-        data_simul_env_start = simul_data.group["profiles"]["env_temperature"][:, 1]
-        data_truth_start = truth_data["TABS"][:, 1]
-
-
-
-        p_t = plot(
-            data_simul_up,
-            z_simul,
-            label = "Updraft",
-            legend = :topright,
-            ylim = (ymin, ymaxs[flight_number]),
-            color = :red,
-            dpi = dpi,
-            xlabel = "T (K)",
-            ylabel = "Height (m)",
-            title = "Updraft and Environmental Temperature (K)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-
-        plot!(
-            simul_data.group["timeseries"]["Tsurface"][[simul_ind]],
-            [0],
-            label = "Surface Temp",
-            seriestype = :scatter,
-            markersize = 5,
-            markercolor = :red,
-        )
-        plot!(
-            truth_data["SST"][[truth_ind]],
-            [0],
-            label = "SST",
-            seriestype = :scatter,
-            markersize = 2,
-            markercolor = :blue,
-        )
-        plot!(data_truth, z_truth, label = "Truth mean", color = :green) # add simulation data to same plot
-
-        plot!(data_simul_up_start, z_simul, label = "Updraft start", color = :pink, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_env_start, z_simul, label = "Environment start", color = :cyan, linestyle = :dash) # add simulation data to same plot
-        plot!(data_truth_start, z_truth, label = "Truth start", color = :lime, linestyle = :dash, xlim = (250, 280)) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "updraft_env_temp_start_now.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # qt start vs now
-        data_simul = simul_data.group["profiles"]["qt_mean"][:, simul_ind]
-        data_simul_plus_precip =
-            simul_data.group["profiles"]["qt_mean"][:, simul_ind] +
-            simul_data.group["profiles"]["qs_mean"][:, simul_ind] +
-            simul_data.group["profiles"]["qr_mean"][:, simul_ind]
-
-
-        data_simul_up = simul_data.group["profiles"]["updraft_qt"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_qt"][:, simul_ind]
-        data_truth = truth_data["QT"][:, truth_ind] ./ 1000 # + 
-        # truth_data["QS"][:, truth_ind] ./ 1000 +
-        # truth_data["QR"][:, truth_ind] ./ 1000
-
-        data_simul_start = simul_data.group["profiles"]["qt_mean"][:, 1]
-        data_simul_up_start = simul_data.group["profiles"]["updraft_qt"][:, 1]
-        data_simul_env_start = simul_data.group["profiles"]["env_qt"][:, 1]
-        data_truth_start = truth_data["QT"][:, 1] ./ 1000
-
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :topright,
-            ylim = (ymin, ymaxs[flight_number]),
-            dpi = dpi,
-            marker = :circle,
-            markersize = 1.5,
-            xlabel = "qt (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QT (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation", marker = :circle, markersize = 1.5) # add simulation data to same plot
-        plot!(data_simul_up, z_simul, label = "Updraft", color = :red) # add simulation data to same plot
-        plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-        plot!(data_simul_plus_precip, z_simul, label = "simul+Precip", color = :black) # add simulation data to same plot
-
-        plot!(data_truth_start, z_truth, label = "Truth start", color = :green, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_start, z_simul, label = "Simulation start", color = :pink, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_up_start, z_simul, label = "Updraft start", color = :red, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_env_start, z_simul, label = "Environment start", color = :blue, linestyle = :dash) # add simulation data to same plot
-
-
-        data_simul_minus_cloud =
-            simul_data.group["profiles"]["qt_mean"][:, simul_ind] -
-            simul_data.group["profiles"]["qi_mean"][:, simul_ind] #- simul_data.group["profiles"]["qi_mean"][:, simul_ind]
-        plot!(data_simul_minus_cloud, z_simul, label = "simul - cloud", color = :brown, linestyle = :dash) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "qt_start_now.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # qt start vs now vs pressure
-        # data_simul = simul_data.group["profiles"]["qt_mean"][:,simul_ind] 
-        # data_simul_plus_precip = simul_data.group["profiles"]["qt_mean"][:,simul_ind]  + simul_data.group["profiles"]["qs_mean"][:,simul_ind]  + simul_data.group["profiles"]["qr_mean"][:,simul_ind]
-
-        # data_simul_up = simul_data.group["profiles"]["updraft_qt"][:,simul_ind]
-        # data_simul_env = simul_data.group["profiles"]["env_qt"][:,simul_ind]
-        data_truth = truth_data["QT"][:, truth_ind] ./ 1000
-
-        # data_simul_start = simul_data.group["profiles"]["qt_mean"][:,1]
-        # data_simul_up_start = simul_data.group["profiles"]["updraft_qt"][:,1]
-        # data_simul_env_start = simul_data.group["profiles"]["env_qt"][:,1]
-        data_truth_start = truth_data["QT"][:, 1] ./ 1000
-
-        p_truth_start = truth_data["PRES"][:, 1]
-
-        p_t = plot(
-            data_truth_start,
-            p_truth_start,
-            label = "Truth",
-            legend = :bottomleft,
-            dpi = dpi,
-            marker = :circle,
-            markersize = 1.5,
-            yflip = true,
-            xlabel = "qt (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QT (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_truth, p_truth_start, label = "Truth now", marker = :circle, markersize = 1.5)
-
-
-
-        savefig(joinpath(outpath, "Figures", "qt_start_now_vs_p.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-        # ql start vs now
-        data_simul = simul_data.group["profiles"]["ql_mean"][:, simul_ind]
-        data_simul_plus_precip = simul_data.group["profiles"]["ql_mean"][:, simul_ind]
-        # simul_data.group["profies"]["qr_mean"][:, simul_ind]
-
-        data_simul_up = simul_data.group["profiles"]["updraft_ql"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_ql"][:, simul_ind]
-        data_truth = truth_data["QCL"][:, truth_ind] ./ 1000
-        # truth_data["QS"][:, truth_ind] ./ 1000 +
-
-        data_simul_start = simul_data.group["profiles"]["ql_mean"][:, 1]
-        data_simul_up_start = simul_data.group["profiles"]["updraft_ql"][:, 1]
-        data_simul_env_start = simul_data.group["profiles"]["env_ql"][:, 1]
-        data_truth_start = truth_data["QCL"][:, 1] ./ 1000
-
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            ylim = (ymin, ymaxs[flight_number]),
-            dpi = dpi,
-            marker = :circle,
-            markersize = 1.5,
-            xlabel = "qt (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QL (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation", marker = :circle, markersize = 1.5) # add simulation data to same plot
-        plot!(data_simul_up, z_simul, label = "Updraft", color = :red) # add simulation data to same plot
-        plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-        plot!(data_simul_plus_precip, z_simul, label = "simul+Precip", color = :black) # add simulation data to same plot
-
-        plot!(data_truth_start, z_truth, label = "Truth start", color = :green, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_start, z_simul, label = "Simulation start", color = :pink, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_up_start, z_simul, label = "Updraft start", color = :red, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_env_start, z_simul, label = "Environment start", color = :blue, linestyle = :dash) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "ql_start_now.png")) # save to file
-
-
-        # --------------------------------------------------------------------------------------------- #
-        # liquid potential Temp start vs now
-        data_simul = simul_data.group["profiles"]["thetal_mean"][:, simul_ind]
-
-        data_simul_up = simul_data.group["profiles"]["updraft_thetal"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_thetal"][:, simul_ind]
-        data_truth = truth_data["THETAL"][:, truth_ind]
-
-        data_simul_start = simul_data.group["profiles"]["thetal_mean"][:, 1]
-        data_simul_up_start = simul_data.group["profiles"]["updraft_thetal"][:, 1]
-        data_simul_env_start = simul_data.group["profiles"]["env_thetal"][:, 1]
-        data_truth_start = truth_data["THETAL"][:, 1]
-
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :bottomright,
-            ylim = (ymin, ymaxs[flight_number]),
-            dpi = dpi,
-            marker = :circle,
-            markersize = 1.5,
-            xlabel = "T (K)",
-            ylabel = "Height (m)",
-            title = "THETAL (kg/kg)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation", marker = :circle, markersize = 1.5) # add simulation data to same plot
-        plot!(data_simul_up, z_simul, label = "Updraft", color = :red) # add simulation data to same plot
-        plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-
-        plot!(data_truth_start, z_truth, label = "Truth start", color = :green, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_start, z_simul, label = "Simulation start", color = :pink, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_up_start, z_simul, label = "Updraft start", color = :red, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_env_start, z_simul, label = "Environment start", color = :blue, linestyle = :dash) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "thetal_start_now.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-        # temp start vs now 
-        data_simul = simul_data.group["profiles"]["temperature_mean"][:, simul_ind]
-
-        data_simul_up = simul_data.group["profiles"]["updraft_temperature"][:, simul_ind]
-        data_simul_env = simul_data.group["profiles"]["env_temperature"][:, simul_ind]
-        data_truth = truth_data["TABS"][:, truth_ind]
-
-        data_simul_start = simul_data.group["profiles"]["temperature_mean"][:, 1]
-        data_simul_up_start = simul_data.group["profiles"]["updraft_temperature"][:, 1]
-        data_simul_env_start = simul_data.group["profiles"]["env_temperature"][:, 1]
-        data_truth_start = truth_data["TABS"][:, 1]
-
-        p_t = plot(
-            data_truth,
-            z_truth,
-            label = "Truth",
-            legend = :topright,
-            ylim = (ymin, ymaxs[flight_number]),
-            dpi = dpi,
-            marker = :circle,
-            markersize = 1.5,
-            xlabel = "T (k)",
-            ylabel = "Height (m)",
-            title = "Temperature (K)",
-            minorgrid = minorgrid,
-        )
-        p_s = plot!(data_simul, z_simul, label = "Simulation", marker = :circle, markersize = 1.5) # add simulation data to same plot
-        plot!(data_simul_up, z_simul, label = "Updraft", color = :red) # add simulation data to same plot
-        plot!(data_simul_env, z_simul, label = "Environment", color = :blue) # add simulation data to same plot
-
-        plot!(data_truth_start, z_truth, label = "Truth start", color = :green, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_start, z_simul, label = "Simulation start", color = :pink, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_up_start, z_simul, label = "Updraft start", color = :red, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_env_start, z_simul, label = "Environment start", color = :blue, linestyle = :dash) # add simulation data to same plot
-
-        savefig(joinpath(outpath, "Figures", "temp_start_now.png")) # save to file
-
-
-        # --------------------------------------------------------------------------------------------- #
-
-        # updraft area
-        data_simul = simul_data.group["profiles"]["updraft_area"][:, simul_ind]
-
-        plot(
-            data_simul,
-            z_simul,
-            label = "Updraft Area",
-            legend = :topright,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "Area",
-            ylabel = "Height (m)",
-            title = "Updraft Area",
-        )
-        savefig(joinpath(outpath, "Figures", "updraft_area.png")) # save to file
-
-        # --------------------------------------------------------------------------------------------- #
-
-
-        # rain snow (as a qt check)
-        data_simul_rain = simul_data.group["profiles"]["qr_mean"][:, simul_ind]
-        data_simul_snow = simul_data.group["profiles"]["qs_mean"][:, simul_ind]
-        data_truth_rain = truth_data["QR"][:, truth_ind] ./ 1000
-        data_truth_snow = truth_data["QS"][:, truth_ind] ./ 1000
-
-        p_t = plot(
-            data_truth_rain,
-            z_truth,
-            label = "Truth Rain",
-            legend = :bottomright,
-            dpi = dpi,
-            ylim = (ymin, ymaxs[flight_number]),
-            xlabel = "qr (kg/kg)",
-            ylabel = "Height (m)",
-            title = "QR (kg/kg)",
-            color = :green,
-            linestyle = :dash,
-            minorgrid = minorgrid,
-        )
-        plot!(data_simul_rain, z_simul, label = "Simulation Rain", color = :lime)
-        plot!(data_truth_snow, z_truth, label = "Truth Snow", color = :blue, linestyle = :dash) # add simulation data to same plot
-        plot!(data_simul_snow, z_simul, label = "Simulation Snow", color = :cyan) # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "qr_qs.png")) # save to file
-
-
-        # reference states p
-
-        p_truth = truth_data["PRES"][:, truth_ind]
-        p_truth_ref = truth_data["p"][:]
-
-        p_ref_simul = simul_data.group["reference"]["p_c"] / 100.0
-        p_ref_simul_f = simul_data.group["reference"]["p_f"] / 100.0
-
-
-        p = plot(
-            p_truth,
-            z_truth,
-            label = "Truth",
-            legend = :topright,
-            dpi = dpi * 4,
-            marker = :circle,
-            markersize = 0.5,
-            markerstrokewidth = 0.05,
-            xlabel = "Pressure (Pa)",
-            ylabel = "Height (m)",
-            title = "Pressure (Pa)",
-            minorgrid = minorgrid,
-        )
-        plot!(
-            p_truth_ref,
-            z_truth,
-            label = "Truth ref",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.25,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :blue,
-        ) # add simulation data to same plot
-        plot!(
-            p_ref_simul,
-            z_simul,
-            label = "Simulation ref",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.25,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :red,
-        ) # add simulation data to same plot
-        plot!(
-            p_ref_simul_f,
-            z_simul_f,
-            label = "Simulation ref f",
-            dpi = dpi,
-            marker = :circle,
-            markersize = 0.25,
-            markerstrokewidth = 0.05,
-            linewidth = 0.1,
-            color = :green,
-        ) # add simulation data to same plot
-        savefig(joinpath(outpath, "Figures", "p.png")) # save to file
-
-    end
-end