Data for The missing risks of climate change

This repository contains the data behind the quantitative figures (figures 1, 3, and 4) in Rising, James, et al. "The missing risks of climate change." Nature 610.7933 (2022): 643-651. https://www.nature.com/articles/s41586-022-05243-6.

The figures directory contains the figures (in their accepted paper form). The data directory contains CSV files with the associated data. The rows and columns are defined as follows:

 - fig1-mc.csv: Rows describe Monte Carlo draws describing the uncertainty for each scenario (SSP1-2.6 and SSP3-7.0) and outcome variable (in the "variable" column). The "run" column describes the basis for each draw of the uncertainty (e.g., model used). The "unit" column provides the units for the "value" column. The "compound" column is TRUE if the rows report compounded uncertainty, and false if the uncertainty is only from the individual analysis stage.

 - fig3-zscores.csv: Each row is a grid cell across the globe, reporting z-scores for various hazards and the population from GPW v4.0 (https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). The z-scores are calculated compared to the recent history (1980-2010) from either longer historical data from CRU TS, with the column prefix "hist.", or from SSP3-7.0 estimates from WorldClim bioclimatic variables for 2050, with the column prefix "ssp370.". Column suffixes describe various hazards: "wet" is average precipitation in the wettest month, "dry" is annual precipitation, "logwet" is as "wet" but evaluated in logs, "logdry" is as "dry" but evaluated in logs, "pcv" is precipitation seasonality (coefficient of variation), "hot" is the maximum temperature of the warmest month, and "cld" is the minimum temperature of the coldest month. "topcol" reports the column with the most extreme z-score (with the z-score in "topscore" and a label in "toplabel").

 - fig4-dmgfunc.csv: Monte Carlo draws of the uncertainty in number of people affected across 16 impacts, reported in "affected" as a fraction of the global population, for each temperature change from preindustrial, reported in "temp".

 - fig4-pdfs.csv: Monte Carlo draws of the uncertainty in the number of people affected for each of 16 impacts and four aggregates. The fraction of the global population affected in reported in "affected" for the temperature change from preindustrial reported in "temp". The impact is labeled in "name" and the aggregate category is reported in "rname".

Additional details on the generation of these data are included in the SI of the paper.