The IIASA Energy, Climate, and Environment program has established itself as a community data hub for more than a decade, providing crucial scenario services to the global modeling community and international institutions related to climate-change mitigation scenarios and air pollution analysis.
The research theme “Scenario Services & Scientific Software” supports the development of state-of-the-art modelling tools and implements the database infrastructure for model comparison projects and scenario analysis. Recognizing that models, tools and packages built collaboratively according to best practices of scientific software development is becoming increasingly important in the emerging research landscape, we facilitate dissemination of research output in stakeholder-focused formats and foster the adoption of FAIR principles for Open Science and reproducible research at IIASA and in the wider community.
Scenario ensembles and data resources
The Energy, Climate, and Environment program serves as a community data hub for global and regional transformation pathways and related reference data sources, for example hosting key datasets and scenario ensembles for the Intergovernmental Panel on Climate Change (IPCC) and numerous international model comparison projects.
Visit https://data.ece.iiasa.ac.at for an overview of scenarios ensembles and database resources.
The Scenario Explorer database infrastructure and related tools follow the data format and naming conventions established by the Integrated Assessment Modeling Consortium (IAMC). More
We also host two “communities” on Zenodo to make data and tools available in line with the FAIR principles for open science.
Flagship modeling tools of the ECE program
The research theme “Scenario Services & Scientific Software” supports researchers in the Energy, Climate, and Environment program to develop and maintain of state-of-the-art modelling tools.
Open-source scientific software and tools
We support best-practice scientific software development in modeling and scenario analysis tools across the Energy Climate Environment program and other groups at IIASA by developing and maintaining several open-source, community-driven tools and packages for research, scenario analyses and data visualization.
The Scenario Explorer database infrastructure
The Scenario Explorer is a web-based user interface to access and manage scenario data. It provides intuitive visualizations and display of timeseries data and download of the data in multiple formats.
The database infrastructure also has an interface for uploading and managing scenario data as a central data repository in multi-institution model comparison exercises. The software stack includes data version control and allows to execute scenario post-processing on any uploaded data (e.g., validation, consistency, meta-analysis).
More information: https://software.ece.iiasa.ac.at/ixmp-server
The pyam package for scenario analysis & data visualization
This package provides a suite of tools and functions for analyzing and visualizing input data (i.e., assumptions, parametrization) and results (model output) of integrated-assessment scenarios, energy systems analysis, and sectoral studies.
The package is based on the timeseries data format developed by the Integrated Assessment Modeling Consortium (IAMC), but it supports additional features such as sub-annual time resolution.
The iam-units package for unit conversion
This package provides a simple and intuitive way to convert units frequently used in research on integrated assessment, energy systems research, climate change mitigation and sustainable development. It includes conversion of greenhouse gas species to carbon-dioxide equivalent using any Global Warming Potential (GWP) factors determined in recent IPCC assessment reports.
GitHub repository: github.com/IAMconsortium/units
Capacity-building towards best-practice of collaborative scientific software development
The research theme “Scenario Services & Scientific Software” supports researchers in adopting the FAIR principles and best-practice of scientific software development. This includes trainings for researchers, pair-programming between researchers and research software engineers and weekly “code-and-tell” sessions to share tips and tricks.