Global economic impact of weather variability on the rich and the poor

This repository provides data and code to reproduce the results of the publication "L. Quante, S. N. Willner, C. Otto, and A. Levermann (2024). Global economic impact of weather variability on the rich and the poor, Nature Sustainability". This repository contains: - 01_forcing_marginal_effects: marginal effects data to be combined with climate model data to generate the impacts- 02_impact_data - timeseries of production disruption, generated as described in the methods "Estimation of direct production losses", using the code in 03_impact_downscaling- 04_acclimate_settings: example settings for acclimate runs using the impact files. Due to licensing restrictions, we can not provide the EORA network data used for the simulations piublicly. 04b_income_share_generation provides the income data (from the World Bank) used to disaggregate consumption data in the EORA network to five income quintiles.- 05_pre_processed_simulation_output: the output from the acclimate simulations, pre-procesed for analysis using the code provided in 06_analysis-code- 07_figures_tables: figures and supplementary data.- 08_addtional_data: data used for plotting, i.e. the World Bank classification of country income levels. Dependencies: a working environment is provided in environment.yml the Acclimate post-processing package can be downloaded from the respective GitHub repostory with [e-mail]:acclimate/post-processing.git. Switch to the develop branch with git checkout develop and install the package with conda develop . from within the repository本仓库提供了复现论文《L. Quante、S. N. Willner、C. Otto 与 A. Levermann（2024）：全球天气变率对贫富群体的经济影响》（发表于《自然-可持续性》*Nature Sustainability*）结果所需的数据与代码。 本仓库包含以下内容： - `01_forcing_marginal_effects`：边际效应数据集，需与气候模型数据结合以生成影响评估结果 - `02_impact_data`：生产中断时间序列数据，按照“直接生产损失估算”方法学生成，所用代码位于`03_impact_downscaling`目录 - `04_acclimate_settings`：基于影响文件运行Acclimate的示例配置文件。受许可协议限制，我们无法公开提供模拟所用的EORA网络数据集。`04b_income_share_generation`模块提供了源自世界银行的收入数据，用于将EORA网络中的消费数据拆解为五个收入五分位组。 - `05_pre_processed_simulation_output`：经预处理的Acclimate模拟输出结果，可使用`06_analysis-code`中提供的代码开展后续分析 - `07_figures_tables`：论文配图与补充数据集 - `08_additional_data`：绘图所用数据，即世界银行的国家收入水平分类数据。 依赖项： 1. 完整可用的运行环境可通过`environment.yml`文件获取 2. Acclimate后处理工具包可从对应GitHub仓库下载：`[e-mail]:acclimate/post-processing.git`。切换至开发分支执行命令`git checkout develop`，并在该仓库根目录下通过`conda develop .`完成安装。