Tools
Tools
Hwong, Y.L., Byers, E. 
ORCID: https://orcid.org/0000-0003-0349-5742, Werning, M., & Quilcaille, Y.
(2024).
Data - Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages.
10.5281/zenodo.13988679.
Abstract
This repository contains the data and scripts required to reproduce the results of the manuscript "Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages" submitted to the Environmental Research Letters (ERL).
Brief description of project
This project has two main goals:
Examine the key factors influencing global economic wildfire damages
Projecting future damages under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP370)
Repository structure
/data directory: contains the data to reproduce the regression analyses and plot the figures presented in the manuscript
/data/historical: contains the historical (training) data that was used for fitting the linear regression model
/data/ssp: contains the SSP projection data for all predictors, as well as the projected model output for future wildfire damages
/scripts directory: contains the python scripts to run the regression model and to plot the figures presented in the manuscript
/scripts/linregress: contains the scripts for running the linear regression model and to conduct various model validation steps
/scripts/plotting: contains the scripts to plot all figures presented in the manuscript
plot_map_y_X_hist.py: script to plot Figure 1 (world map of historical wildfire damage and predictors used in this study)
plot_residual_plots.py: script to plot Figure 2 (residual and partial residual plots of the fitted regression model)
plot_beta_coef_model_prediction.py: script to plot Figure 3 (standardized beta coefficients of the fitted regression model and the scatterplots for reported vs. model-estimated wildfire damages)
plot_predictor_ssp_trend.py: script to plot Figure 4 (time-series of the SSP projections of the predictors)
plot_map_y_X_ssp.py: script to plot Figure 5 (world map of wildfire damages and predictor values for the three SSPs explored in this study)
plot_ssp_damage_projection_by_region.py: script to plot Figure 6 (projected wildfire damages under the three SSPs and for the six IPCC AR6 regions)
plot_ssp_damage_projection_per_predictor.py: script to plot Figure 7 (time-series of global mean projected wildfire damage with all predictors changing and only individual predictors changing)
plot_ssp3_ssp1_difference.py: script to plot Figure 8 (time-series of mean avoided wildfire damage in SSP126 compared to SSP370)
| Item Type: | Data |
|---|---|
| Additional Information: | Creative Commons Attribution 4.0 International |
| Research Programs: | Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Exploratory Modeling of Human-natural Systems (EM) Energy, Climate, and Environment (ECE) Energy, Climate, and Environment (ECE) > Integrated Assessment and Climate Change (IACC) Energy, Climate, and Environment (ECE) > Integrated Climate Impacts (ICI) Energy, Climate, and Environment (ECE) > Sustainable Service Systems (S3) |
| Depositing User: | Luke Kirwan |
| Date Deposited: | 10 Jan 2025 10:00 |
| Last Modified: | 10 Jan 2025 10:00 |
| URI: | https://pure.iiasa.ac.at/20246 |
Actions (login required)
 |
View Item |