Time series plot

Generate time series of region-averaged field.

References

General functionality is provided using CSET recipe generic_surface_domain_mean_time_series.yaml

The following CSET operators are used:

Using cset bake on the command line

  • Access recipe file using cset cookbook.

  • Set required recipe inputs on command line.

Example to generate time series plot of domain averaged temperature_at_screen_level for any number of input models:

cset cookbook generic_surface_domain_mean_time_series.yaml
cset -v bake -i "/path/to/input/data1" "..." "/path/to/input/dataN" \
             -o "./output_path" \
             -r generic_surface_domain_mean_time_series.yaml \
             --VARNAME="temperature_at_screen_level" \
             --MODEL_NAME="['my_model_label1', '...', 'my_model_labelN']" \
             --METHOD="SEQ" \
             --SUBAREA_TYPE='None' --SUBAREA_EXTENT='None' --SUBAREA_NAME=''

Configuring the cset_workflow

  • Update workflow configuration settings via rose edit GUI or in rose-suite.conf file.

  • Complete General setup options and Cycling and Model options details - see Configure the workflow.

  • Set required configuration options on Diagnostics / Surface (2D) fields panel:

    SURFACE_FIELDS = ["temperature_at_screen_level", ...]
    TIMESERIES_SURFACE_FIELD = True
    

Example python code

air_temperature  [2022-01-01 03:00:00 to 2022-01-06 03:00:00]
from CSET import sample_data_path
from CSET.operators import collapse, plot, read

# Set paths to input data
filename1 = sample_data_path("air_temperature_fcst_1.nc")
filename2 = sample_data_path("air_temperature_fcst_2.nc")

# Read selected variable(s) of interest for 2 models
cubes = read.read_cubes(
    [filename1, filename2],
    ["temperature_at_screen_level"],
    model_names=["model_fcst_1", "model_fcst_2"],
)

# Collapse input data over selected dimensions
collapsed_cubes = collapse.collapse(cubes, ["grid_latitude", "grid_longitude"], "MEAN")

# Plot domain mean time series using plot_line_series
plot.plot_line_series(collapsed_cubes)

Total running time of the script: (0 minutes 0.375 seconds)

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