Reduced global fire activity due to human demography slows global warming by enhanced land carbon uptake

<b>Data availability for the paper:</b>Wu C, Sitch S, Huntingford C, Mercado LM, Venevsky S, Lasslop G, Archibald S, Staver AC (2022) Reduced global fire activity due to human demography slows global warming by enhanced land carbon uptake.If you have more questions, please contact Chao Wu (chaowu[dot]thu[at]gmail[dot]com)<b>Summary of this dataset</b>DATA: All raw data used to generate the figures and tables in the main text and SI Appendix.This DATA includes the results from the 34 ESMs, 1 offline, and 3 factorial simulations.Each ESM includes the results from the 3 experiments (“standard” [rcp_*], “constant fire” [pi_rcp_*], and “without fire” [nf_rcp_*]) × 4 RCP scenarios (RCP2.6, 4.5, 6.0, and 8.5).For the model CESM1_BGC, the results from additional 3 experiments × 4 RCP scenarios × 9 SSP combinations are provided.For each scenario, there are two global results "SEVERGlobe.out" and “CO2.dat”, and one grid-based result for annual NBP ("anep.dat"; 34 ESMs; for coupling needs in the model, values in "anep.dat" multiplied by -1 will be the real NBP), or annual burned area ("aburntarea.dat"; offline) and fire carbon emissions ("afire.dat"; offline).Each column in "SEVERGlobe.out" represents the “Year”, global annual “nbp”, “npp”, “gpp”, “ra”, “rh”, “biomass”, “soil carbon”, “total carbon”, “fire carbon emissions”, “burned area”, and “temperature over land” in the 34 ESMs simulations. Global annual “fire carbon emissions” and “burned area” are provided in the offline simulation.Each column in “CO2.dat” represents “year” and annual atmospheric “co2” concentration.Factorial analysis results for global annual “fire carbon emissions” based on 3 ESMs are shown in “test_driver_*”, each of that includes 6 scenarios: fixed temperature (“rcp6_tem”), precipitation (“rcp6_pre”), wind speed (“rcp6_wind”), population density (“rcp6_pop”), ratio of rural population to total population (“rcp6_rur”), and distance to cities (“rcp6_dis”).ESM runs from 1860 to 2100; offline runs from 1950-2016.Satellite-based GFED4s, GFED4 datasets were accessed from http://www.globalfiredata.org/index.html; FireCCI50 dataset was accessed from https://www.esa-fire-cci.org/node/4. FEER1 dataset was accessed from https://feer.gsfc.nasa.gov/data/emissions/. European Space Agency's Land Cover Climate Change Initiative dataset was accessed from https://www.esa-landcover-cci.org/. The ILAMB was accessed from https://www.ilamb.org/.The python code to interpret data and prepare the figures are available on request from the corresponding author.