PyCPT 2: The Python Interface to the Climate Predictability Tool (CPT)

PyCPT 2 is a set of python libraries designed to interface with CPT to facilitate operational climate forecasting and research in Python. It is the principal tool used to implement the IRI’s “NextGen” approach to climate forecasting in partner countries around the world. In version two, PyCPT has been re-designed from the ground up, and packaged with Anaconda to lower the barriers to Python climate forecasting.

PyCPT is typically implemented in a Juypter Notebook, which allows the user to visualize variables and data structures dynamically, and run code one step at a time. PyCPT version 1 could not be decoupled from Jupyter Notebook since it relied on ipython system commands. PyCPT version 2 is pure-python (except for CPT, of course), modular, and portable.

CPT-IO is a library for reading and writing CPTv10-formatted TSV files in python. It is part of PyCPT, but is packaged separately to facilitate reuse in other applications.

The PyCPT 2 GitHub code repositories, including example Jupyter Notebooks, can be found here: https://github.com/iri-pycpt

Acknowledgments:

PyCPT development is funded in part by:

• Columbia World Projects - ACToday
• United Nations World Food Programme
• World Bank - AICCRA
• World Meteorological Organization - ENANDES (Enhancing Adaptive Capacity of Andean Communities through Climate Services)

GCM Data Cataloging is funded in part by:

• The North American Multi-Model Ensemble (NMME) Project
• SubX
• S2S