Note
Go to the end to download the full example code.
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 editGUI or inrose-suite.conffile.Complete
General setup optionsandCycling and Model optionsdetails - see Configure the workflow.Set required configuration options on
Diagnostics / Surface (2D) fieldspanel: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]](../../../../_images/sphx_glr_plot_line_timeseries_001.png)
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)