Data - Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages

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 Climate Journal (ERCL). 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 /data/source: contains all raw data used in this study /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 run_linregress.py: script to run the linear regression model run_nonlinregress.py: script to run the nonlinear models (preliminary) inspect_model.py: script to conduct model validation /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_timeseries_global.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 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) SI_plot_ssp_damage_projection_lin_vs_nonlin.py: script to plot Figure S1 (comparison of time-series of mean projected wildfire damage with the linear and nonlinear models) SI_plot_beta_coef_pop_wui.py: script to plot Figure S2 (same as Figure 3 but for the model using pop_wui instead of PDforest) SI_plot_ssp_population.py: script to plot Figure S3 (population projection under the three SSP scenarios) SI_plot_ssp_map_pop_wui.py: script to plot Figure S4 (world map of the pop_wui predictor under three SSP scenarios) SI_plot_ssp_damage_projection_pop_wui.py: script to plot Figure S5 (comparison of the time-series of projected wildfire damage using pop_wui vs PDforest as predictor) SI_plot_predictor_ssp_trend_by_dev_region.py: script to plot Figure S6 (time-series of the SSP projections of the predictors by developmental regions)本仓库包含用于复现投稿至《环境研究气候期刊》（Environmental Research Climate Journal, ERCL）的论文《可持续发展：限制气候变化引发的野火损失的关键》所需的数据与脚本。 项目简要说明 本项目包含两大核心目标： 1. 探究影响全球经济层面野火损失的关键驱动因子 2. 基于三种共享社会经济路径（Shared Socioeconomic Pathways, SSP126、SSP245、SSP370），对未来野火损失进行预测 仓库目录结构 `/data` 目录：存储用于复现论文中回归分析与图表绘制的相关数据 - `/data/historical`：存储用于拟合线性回归模型的历史（训练）数据集 - `/data/ssp`：存储所有预测因子的SSP投影数据，以及未来野火损失的模型预测输出结果 - `/data/source`：存储本研究使用的全部原始数据 `/scripts` 目录：存储用于运行回归模型与绘制论文中所有图表的Python脚本 - `/scripts/linregress`：包含用于运行线性回归模型及执行各类模型验证步骤的脚本 - `run_linregress.py`：用于运行线性回归模型的脚本 - `run_nonlinregress.py`：用于运行非线性预实验模型的脚本 - `inspect_model.py`：用于执行模型验证的脚本 - `/scripts/plotting`：包含用于绘制论文中所有图表的脚本 - `plot_map_y_X_hist.py`：用于绘制图1（本研究所用历史野火损失与预测因子的全球分布图）的脚本 - `plot_residual_plots.py`：用于绘制图2（拟合回归模型的残差与偏残差图）的脚本 - `plot_beta_coef_model_prediction.py`：用于绘制图3（拟合回归模型的标准化β系数，以及实际报告野火损失与模型估算野火损失的散点图）的脚本 - `plot_predictor_ssp_timeseries_global.py`：用于绘制图4（预测因子的SSP投影全球时间序列图）的脚本 - `plot_map_y_X_ssp.py`：用于绘制图5（本研究探索的三种SSP情景下预测因子的全球分布图）的脚本 - `plot_ssp_damage_projection_by_region.py`：用于绘制图6（三种SSP情景下，IPCC第六次评估报告（AR6）划定的六大区域的野火损失预测结果）的脚本 - `plot_ssp_damage_projection_per_predictor.py`：用于绘制图7（所有预测因子均变化，以及仅单个预测因子变化时的全球平均野火损失预测时间序列图）的脚本 - `plot_ssp3_ssp1_difference.py`：用于绘制图8（SSP126相较于SSP370情景下可避免的平均野火损失时间序列图）的脚本 - `SI_plot_ssp_damage_projection_lin_vs_nonlin.py`：用于绘制补充图S1（线性模型与非线性模型的平均野火损失预测时间序列对比图）的脚本 - `SI_plot_beta_coef_pop_wui.py`：用于绘制补充图S2（与图3一致，但模型使用`pop_wui`而非`PDforest`作为预测因子）的脚本 - `SI_plot_ssp_population.py`：用于绘制补充图S3（三种SSP情景下的人口投影图）的脚本 - `SI_plot_ssp_map_pop_wui.py`：用于绘制补充图S4（三种SSP情景下`pop_wui`预测因子的全球分布图）的脚本 - `SI_plot_ssp_damage_projection_pop_wui.py`：用于绘制补充图S5（使用`pop_wui`与`PDforest`作为预测因子的野火损失预测时间序列对比图）的脚本 - `SI_plot_predictor_ssp_trend_by_dev_region.py`：用于绘制补充图S6（按发展区域划分的预测因子SSP投影时间序列图）的脚本