Add vertical diagnostics

Project.toml

@@ -49,7 +49,7 @@ ArtifactWrappers = "0.2"
 Artifacts = "1"
 AtmosphericProfilesLibrary = "0.1.6"
 ClimaComms = "0.6.2"
-ClimaCore = "0.14.11"
+ClimaCore = "0.14.12"
 ClimaDiagnostics = "0.2"
 ClimaParams = "0.10.12"
 ClimaTimeSteppers = "0.7.33"

config/model_configs/prognostic_edmfx_gcmdriven_column.yml

@@ -42,7 +42,7 @@ diagnostics:
     period: 10mins
   - short_name: [entr, detr, lmix, bgrad, strain, edt, evu]
     period: 10mins
-  - short_name: [rlut, rlutcs, rsut, rsutcs]
+  - short_name: [rlut, rlutcs, rsut, rsutcs, clwvi, lwp, clivi, dsevi, clvi, prw, hurvi, husv]
     period: 10mins
   - reduction_time: max
     short_name: tke

perf/flame.jl

@@ -38,15 +38,15 @@ ProfileCanvas.html_file(joinpath(output_dir, "flame.html"), results)
 #####
 
 allocs_limit = Dict()
-allocs_limit["flame_perf_target"] = 1_458_344
-allocs_limit["flame_perf_target_tracers"] = 1_595_760
+allocs_limit["flame_perf_target"] = 1_674_376
+allocs_limit["flame_perf_target_tracers"] = 1_820_752
 allocs_limit["flame_perf_diagnostics"] = 12_301_560
-allocs_limit["flame_perf_target_diagnostic_edmfx"] = 2_285_552
-allocs_limit["flame_perf_target_frierson"] = 1_632_920
+allocs_limit["flame_perf_target_diagnostic_edmfx"] = 2_555_280
+allocs_limit["flame_perf_target_frierson"] = 1_849_976
 allocs_limit["flame_perf_target_threaded"] = 2_306_856
-allocs_limit["flame_perf_target_callbacks"] = 1_662_096
+allocs_limit["flame_perf_target_callbacks"] = 1_879_184
 allocs_limit["flame_perf_gw"] = 882_938_744
-allocs_limit["flame_perf_target_prognostic_edmfx_aquaplanet"] = 2_225_384
+allocs_limit["flame_perf_target_prognostic_edmfx_aquaplanet"] = 2_490_248
 allocs_limit["flame_gpu_implicit_barowave_moist"] = 336_378
 # Ideally, we would like to track all the allocations, but this becomes too
 # expensive there is too many of them. Here, we set the default sample rate to

post_processing/ci_plots.jl

@@ -42,7 +42,7 @@ import CairoMakie
 import CairoMakie.Makie
 import ClimaAnalysis
 import ClimaAnalysis: Visualize as viz
-import ClimaAnalysis: SimDir, slice, read_var
+import ClimaAnalysis: SimDir, slice, read_var, average_xy
 import ClimaAnalysis.Utils: kwargs as ca_kwargs
 
 import ClimaCoreSpectra: power_spectrum_2d
@@ -1311,3 +1311,50 @@ function make_plots(::EDMFSpherePlots, output_paths::Vector{<:AbstractString})
         MAX_NUM_ROWS = 4,
     )
 end
+
+
+function make_plots(
+    ::Val{:gcm_driven_scm},
+    output_paths::Vector{<:AbstractString},
+)
+    simdirs = SimDir.(output_paths)
+    short_names_2D = [
+        "rlut",
+        "rlutcs",
+        "rsut",
+        "rsutcs",
+        "clwvi",
+        "lwp",
+        "clivi",
+        "dsevi",
+        "clvi",
+        "prw",
+        "hurvi",
+    ]
+    short_names_3D = ["husv", "thetaa", "ta", "hur", "hus", "clw", "cl"]
+    reduction = "inst"
+    vars_2D = map_comparison(simdirs, short_names_2D) do simdir, short_name
+        average_xy(get(simdir; short_name, reduction))
+    end
+    vars_3D = map_comparison(simdirs, short_names_3D) do simdir, short_name
+        data = window(
+            get(simdir; short_name, reduction),
+            "z",
+            left = 0,
+            right = 4000,
+        )
+        return average_xy(data)
+    end
+    make_plots_generic(
+        output_paths,
+        vars_2D;
+        MAX_NUM_COLS = 2,
+        output_name = "summary_2D",
+    )
+    make_plots_generic(
+        output_paths,
+        vars_3D;
+        MAX_NUM_COLS = 2,
+        output_name = "summary_3D",
+    )
+end