Remove t_start

docs/src/diagnostics/developers_diagnostics.md

@@ -17,7 +17,7 @@ Internally, this is done by using the [`ClimaDiagnostics.jl`](https://github.com
  `add_diagnostic_variable!`, and dispatch off the type of land\_model to define how to compute a diagnostic (for example, surface temperature is computed in `p.bucket.T_sfc` in the bucket model).
  - compute methods are defined in a separate file, for example, `bucket_compute_methods.jl`.
  - `standard_diagnostic_frequencies.jl` defines standard functions to schedule diagnostics, for example, hourly average or monthly max, these functions are called on a list of diagnostic variables. As developers, we can add more standard functions that users may want to have access to easily in this file.
- - `default_diagnostics.jl` defines default diagnostics functions to use on a model simulation. For example, `default_diagnostics(land_model::BucketModel, t_start; output_writer)`.
+ - `default_diagnostics.jl` defines default diagnostics functions to use on a model simulation. For example, `default_diagnostics(land_model::BucketModel, output_writer)`.
  will return a `ScheduledDiagnostics` that computes hourly averages for all Bucket variables, along with their metadata, ready to be written on a NetCDF file when running a Bucket simulation.
 
 The following section give more details on these functions, along with examples. As developers, we want to extand these functionality as ClimaLand progresses.
@@ -66,7 +66,7 @@ For each model, we define a function `default_diagnostics` which will define wha
 on what schedule (for example, hourly average). For example,
 
 ```Julia
-function default_diagnostics(land_model::BucketModel, t_start; output_writer)
+function default_diagnostics(land_model::BucketModel{FT}; output_writer) where {FT}
 
     define_diagnostics!(land_model)
 
@@ -87,7 +87,7 @@ function default_diagnostics(land_model::BucketModel, t_start; output_writer)
     ]
 
     default_outputs =
-        hourly_averages(bucket_diagnostics...; output_writer, t_start)
+        hourly_averages(FT, bucket_diagnostics...; output_writer)
     return [default_outputs...]
 end
 ```
@@ -103,11 +103,10 @@ If `average_period = :hourly`, `default_outputs` calls `hourly_averages`, et cet
 We defined some functions of diagnostic schedule that may often be used in `standard_diagnostic_frequencies.jl`, for example
 
 ```Julia
-hourly_averages(short_names...; output_writer, t_start) = common_diagnostics(
-    60 * 60 * one(t_start),
+hourly_averages(FT, short_names...; output_writer) = common_diagnostics(
+    60 * 60 * one(FT),
     (+),
     output_writer,
-    t_start,
     short_names...;
     pre_output_hook! = average_pre_output_hook!,
 )

docs/src/diagnostics/users_diagnostics.md

@@ -50,7 +50,7 @@ t0 = 0 # the starting time of your simulation
 
 reference_date = DateTime(2024) # reference_date is the DateTime of your starting time
 
-diags = ClimaLand.default_diagnostics(model, t0, reference_date; output_writer = nc_writer)
+diags = ClimaLand.default_diagnostics(model, reference_date; output_writer = nc_writer)
 
 diagnostic_handler =
     ClimaDiagnostics.DiagnosticsHandler(diags, Y, p, t0; dt = Δt)
@@ -118,11 +118,10 @@ add_diagnostic_variable!(
 ### Define how to schedule your variables. For example, you want the seasonal maximum of your variables, where season is defined as 90 days.
 
 ```Julia
-seasonal_maxs(short_names...; output_writer, t_start) = common_diagnostics(
-    90 * 24 * 60 * 60 * one(t_start),
+seasonal_maxs(FT, short_names...; output_writer) = common_diagnostics(
+    90 * 24 * 60 * 60 * one(FT),
     max,
     output_writer,
-    t_start,
     short_names...,
 )
 ```
@@ -134,7 +133,7 @@ Now, you can call your schedule with your variables.
 ```Julia
 my_custom_diagnostics = ["lhf", "bor"]
 
-diags = seasonal_maxs(my_custom_diagnostics...; output_writer, t_start)
+diags = seasonal_maxs(FT, my_custom_diagnostics...; output_writer)
 ```
 
 ### Analyze your simulation output

experiments/benchmarks/land.jl

@@ -72,7 +72,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
     subsurface_space = domain.space.subsurface
 
     ref_time = DateTime(2021)
-    t_start = 0.0
 
     # Forcing data
     era5_artifact_path =
@@ -82,7 +81,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "rf",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
     )
@@ -92,7 +90,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "sf",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
     )
@@ -102,23 +99,20 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "ws",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     q_atmos = TimeVaryingInput(
         joinpath(era5_artifact_path, "era5_2021_0.9x1.25_clima.nc"),
         "q",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     P_atmos = TimeVaryingInput(
         joinpath(era5_artifact_path, "era5_2021_0.9x1.25.nc"),
         "sp",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
 
@@ -127,7 +121,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "t2m",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     h_atmos = FT(10)
@@ -150,7 +143,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "ssrd",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
     )
@@ -159,7 +151,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "strd",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
     )
@@ -493,7 +484,6 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
         "lai",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (;
             preprocess_func = (data) -> data > 0.05 ? data : 0.0,

experiments/benchmarks/richards.jl

@@ -196,14 +196,12 @@ function setup_prob(t0, tf, Δt; nelements = (101, 15))
     # 1. Convert precipitation to be negative (as it is downwards)
     # 2. Convert accumulations over an hour to a rate per second
     ref_time = DateTime(2021)
-    t_start = 0.0
     # Precipitation:
     precip = TimeVaryingInput(
         joinpath(era5_artifact_path, "era5_2021_0.9x1.25.nc"),
         "tp",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
     )

experiments/integrated/global/global_soil_canopy.jl

@@ -57,7 +57,6 @@ surface_space = domain.space.surface
 subsurface_space = domain.space.subsurface
 
 ref_time = DateTime(2021);
-t_start = 0.0
 
 # Forcing data
 era5_artifact_path =
@@ -67,7 +66,6 @@ precip = TimeVaryingInput(
     "rf",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
     file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
 )
@@ -77,7 +75,6 @@ snow_precip = TimeVaryingInput(
     "sf",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
     file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
 )
@@ -87,23 +84,20 @@ u_atmos = TimeVaryingInput(
     "ws",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
 )
 q_atmos = TimeVaryingInput(
     joinpath(era5_artifact_path, "era5_2021_0.9x1.25_clima.nc"),
     "q",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
 )
 P_atmos = TimeVaryingInput(
     joinpath(era5_artifact_path, "era5_2021_0.9x1.25.nc"),
     "sp",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
 )
 
@@ -112,7 +106,6 @@ T_atmos = TimeVaryingInput(
     "t2m",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
 )
 h_atmos = FT(10);
@@ -135,7 +128,6 @@ SW_d = TimeVaryingInput(
     "ssrd",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
     file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
 )
@@ -144,7 +136,6 @@ LW_d = TimeVaryingInput(
     "strd",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
     file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
 )
@@ -241,7 +232,6 @@ LAIfunction = TimeVaryingInput(
     "lai",
     surface_space;
     reference_date = ref_time,
-    t_start,
     regridder_type,
     file_reader_kwargs = (;
         preprocess_func = (data) -> data > 0.05 ? data : 0.0,
@@ -374,7 +364,6 @@ nc_writer = ClimaDiagnostics.Writers.NetCDFWriter(subsurface_space, output_dir)
 
 diags = ClimaLand.default_diagnostics(
     land,
-    t0,
     ref_time;
     output_writer = nc_writer,
     average_period = :hourly,

experiments/long_runs/land.jl

@@ -73,7 +73,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
     subsurface_space = domain.space.subsurface
 
     ref_time = DateTime(2021)
-    t_start = t0
     # Forcing data
     era5_artifact_path =
         ClimaLand.Artifacts.era5_land_forcing_data2021_folder_path(; context)    # Precipitation:
@@ -82,7 +81,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "rf",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
     )
@@ -92,7 +90,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "sf",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> -data / 3600,),
     )
@@ -102,23 +99,20 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "ws",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     q_atmos = TimeVaryingInput(
         joinpath(era5_artifact_path, "era5_2021_0.9x1.25_clima.nc"),
         "q",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     P_atmos = TimeVaryingInput(
         joinpath(era5_artifact_path, "era5_2021_0.9x1.25.nc"),
         "sp",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
 
@@ -127,7 +121,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "t2m",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
     )
     h_atmos = FT(10)
@@ -150,7 +143,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "ssrd",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
     )
@@ -159,7 +151,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "strd",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (; preprocess_func = (data) -> data / 3600,),
     )
@@ -494,7 +485,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
         "lai",
         surface_space;
         reference_date = ref_time,
-        t_start,
         regridder_type,
         file_reader_kwargs = (;
             preprocess_func = (data) -> data > 0.05 ? data : 0.0,
@@ -620,7 +610,6 @@ function setup_prob(t0, tf, Δt; outdir = outdir, nelements = (101, 15))
 
     diags = ClimaLand.default_diagnostics(
         land,
-        t0,
         ref_time;
         output_writer = nc_writer,
         output_vars = :short,