Forecast Plotting

Importing the Forecast Plotting Module

To help participants visualize their sub-seasonal forecasts, the AI-WQ-Package includes a dedicated module called plotting_forecast. This module allows you to easily plot global probabilistic forecasts.

To import the necessary plotting function, use:

from AI_WQ_package.plotting_forecast import plot_forecast

Plotting a forecast

The plot_forecast function generates a map showing the probability forecast for a given quantile range. The resulting figure matches the format used on the AI Weather Quest Forecast Portal.

The plot_forecast function only has three inputs:

plot_forecast(<<forecast>>,<<quintile_num>>,local_destination=None)

  • forecast (xarray.dataarray): Your submitted forecast to the AI Weather Quest.

  • quintile_num (int or str): The selected quintile where 1 refers to < 20%, 2 refers to 20 <= x < 40% etc.

  • local_destination (str, optional): Path to the local folder where the figure will be saved. If not provided, the figure will be saved in the current working directory.

The figure filename is automatically created using forecast attributes. The format is:

<<variable>>_<<fc_init_date}>>_p<<fcwin>>_<<teamname>>_<<modelname>>_quintile_<<quintile_value>>.jpg

where:

  • variable: Forecasted variable (e.g. tas, mslp or pr).

  • fc_init_date: Forecast initialisation date in format YYYYMMDD (e.g. 20250403).

  • fcwin: The sub-seasonal forecasting window (either ‘1’ or ‘2’).

  • teamname: The teamname associated with the submitted forecast.

  • modelname: The modelname associated with the submitted forecast.

  • quintile_value: Upper limit of the selected quintile (e.g. 20, 40 etc.)

Note

The plot_forecast function only works with dataarray templates provided through the AI-WQ-package.

Example Usage

Here is how you might use the function to generate a forecast plot for the 60–80% quintile range:

from AI_WQ_package.plotting_forecast import plot_forecast

# Plot the 4th quintile (60 to 80%) and save to a local folder ('/home/test_figures/')
plot_forecast(submitted_forecast,4,local_destination='/home/test_figures/'

Below is an example forecast figure showing predicted probabilities of mean sea level pressure being between 80.0 and 100.0% of climatological conditions for the week commencing 22nd January 2024. The forecast was initialised on the 4th January 2024 and based on ECMWF dynamical sub-seasonal forecasts.

Forecast example for mean sea level pressure