Structure for collaboratively collecting and processing up-to-date historical reference data on energy supply and demand and emissions into the IAMC format, for assessing the plausibility of near-term scenario trajectories

Overview presentation given at the IAMC Conference in November 2024

• data: location to put original data sources, links are available in src/process_hist_data.R script

• figures: location where comparison and near-term forecast analysis figures are created

• mappings: location of mappings for regions / countries, as well as energy system and emissions variables to IAMC template

• output: location of processed data files: both R objects for detailed data (structure close to original, but cleaned up), and csv files for harmonized IAMC format

• runs: location to put scenario data in IAMC format to compare against historic data

• src: location of R scripts for primary creation of data and to make comparison plots

After cloning this repository to your local computer:

1. Double-click rhistiamc.Rproj to load the project in Rstudio

• to make comparison plots with IAMs, etc

2. Download the processed historical data in IAMC format from: PUBLIC_output_rhistiamc into your local output/ folder

3. Open and run the src/combine_and_plot.R script, following the comments inside

• to add / update a dataset
• to aggregate to new regions that match IAM / analysis

2. Open src/process_hist_data.R

3. Download the open access historical data files from the original sources shown in the comments throughout the script, or for a quick start from this data_rhistiamc folder (shared internally at CGS).

4. Run the src/process_hist_data.R script

5. If desired to make figures or perform analysis on the historical and IAM data (optional), then open and run the src/combine_and_plot.R script. Make any additional src/fig_...R scripts based on the ones provided or with a different setup.

• Only the files in mappings and src are git managed, others are ignored to reduce repository size (see .gitignore).

• This repository somewhat similar to model-internal code such as gcamdata, which provide a harmonized platform for processing data for use with that model. However, this repository enables comparisons at the IAMC format output level (allowing for checks on historic calibration, and correctness of our reporting), and allows for faster updates, given its lower complexity, and focus on fewer key variables.

• This repository also produces historical data at an aggregate region level of the user's choice, in addition to the the country level, so that it can also be used for analysis of IAM results. However, be aware that not all datasets are comprehensive by country, which means that the aggregate mapped results, for example into five global regions (R5), may not be the fully complete values.

The script process_hist_data.R reads data from publicly available sources, and converts them into a common format, in line with the IAMC variable template as used in the IPCC AR6 database (https://data.ene.iiasa.ac.at/ar6). Add the dataset to both source-specific sections of this code, noting the comment lines on top of this script, which give a short explanation on the structure.

We invite collaboration on and improvement of this community repository. Please use the Issues tab for any questions / comments regarding useage or improvement. To contribute to the repository, first fork this one (umd-cgs/rhistiamc) to your local organization's GitHub, then push commits to that one and start a pull request to this repository. We will consider these pull requests and discuss any questions that we have with your team.