Run Examples

Start up

Follow these simple steps to quickly get started:

  1. Installation: Install the toolbox using the provided installation instructions or simply type the following command in your terminal:
pip install MJOcast

  1. Configuration: Customize your forecasting experience by configuring the toolbox:

    2.1. Manual Configuration: Edit the YAML configuration file directly to define your forecast parameters, data paths, and other settings.

    2.2. YAML Generator Tool: Alternatively, use the provided YAML generator tool in the preprocessor Jupyter Notebook for a user-friendly configuration process.

  2. Quick Start Usage: Begin forecasting with ease:

    Import the necessary modules:

import MJOcast.utils.ProcessForecasts as ProFo
import MJOcast.utils.ProcessOBS as ProObs

Load the YAML configuration file:

yaml_file_path = './settings.yaml'

Create Observational MJO and EOFs [from either user specified data or provide ERA5]:

MJO_obs = ProObs.MJOobsProcessor(yaml_file_path)
OBS_DS, eof_list, pcs, MJO_fobs, eof_dict = MJO_obs.make_observed_MJO()

Generate Hindcast .nc Files for each forecast:

MJO_for = ProFo.MJOforecaster(yaml_file_path, MJO_obs.eof_dict, MJO_obs.MJO_fobs)
DS_CESM_for, OLR_cesm_anom_filtered, U200_cesm_anom_filtered, U850_cesm_anom_filtered = MJO_for.create_forecasts(num_files=1)
  1. Documentation: For in-depth guidance, explore the code API documentation. It provides detailed usage instructions, function explanations, and examples.

Follow these steps to make the most of MJOforecaster in your projects. Happy forecasting!