Open Accesspyam: Analysis and visualisation of integrated assessment and macro-energy scenarios
Author(s) -
Daniel Huppmann,
MJ Gidden,
Zebedee Nicholls,
Jonas Hörsch,
Robin Lamboll,
Paul Natsuo Kishimoto,
Thorsten Burandt,
Oliver Fricko,
Edward Byers,
Jarmo Kikstra,
Maarten Brinkerink,
Maik Budzinski,
Florian Maczek,
Sebastian Zwickl-Bernhard,
Lara Welder,
EF Álvarez Quispe,
Christopher J. Smith
Publication year - 2021
Publication title -
open research europe
Language(s) - English
Resource type - Journals
ISSN - 2732-5121
DOI - 10.12688/openreseurope.13633.1
Subject(s) - python (programming language) , suite , visualization , computer science , macro , data visualization , systems engineering , data science , data mining , software engineering , engineering , geography , archaeology , programming language , operating system
The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages.The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for timeseries aggregation, downscaling and unit conversion. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.