Supplementary Data: zhao-etal_2022_global_environmental_change

Autor: Zhao, Xin, Wise, Marshall A., Waldhoff, Stephanie T., Kyle, G. Page, Huster, Jonathan E., Ramig, Christopher W., Rafelski, Lauren E., Pralit L. Patel, Calvin, Katherine V.
Jazyk: angličtina
Rok vydání: 2021
Předmět:
DOI: 10.5281/zenodo.5673427
Popis: This repository includes the following files for replicating the results provided in the paper: "The impact of agricultural trade approaches on global economic modeling" published in Global Environmental Change. (1)GCAM_files/ (2.9 GB is unzipped) *configurations *gcamdata_xml *queries *README.md (2)Visualize_Rproject/ (2.5 GB is unzipped) *Visualize_Rproject.Rproj *R *data *output *README.md GCAM_files/ includes files needed to run GCAM-T (DOI:10.5281/zenodo.4705472) and generate GCAM output database for experiments designed in the paper. The GCAM-T model needs to be downloaded and compiled first. Then copy the two folders, configurations/ and gcamdata_xml/, into the model folder. The configuration files included in the configurations/ folder can be run and generate GCAM output database corresponding to experiments designed in the paper (i.e., E1-E4). Note that Monte Carlo simulations and extreme scenarios under E4 require additional changes of "monte_carlo_logits/ag_trade.xml" in the configuration (an example of positive 2 times SD extreme scenario, ag_tradeposd2.xml, is provided). All data needed are included in the gcamdata_xml folder. Main queries needed are provided in the queries/ folder. Visualize_Rproject/ includes an R project for processing data from GCAM runs and generating figures and tables for the paper. In R/Configuration.R, packages are loaded, data and functions are read. Visualized results can be generated by sourcing R codes and results are saved in output/. Note that GCAM result database was queried into csv results and then converted to RDS files in R by sourcing "R/Source.ProcRDS.R". Note that this part was commented out since RDS files are provided. In case that source csv files are available and RDS files are needed, this script needs to be sourced. The figures and tables are generated by sourcing relevant scripts (the scripts can be modified to generate additional results): Fig & Table Rscript Output folder Fig. 1 "R/Source.ref.3.R" "output/Reference" Fig. 3 "R/Source.ref.1.R" "output/Reference" Fig. 4 "R/Source.ref.3.R" "output/Reference" Fig. 5 & 6 "R/Source.ref.1.R" "output/Reference" Fig. 7 "R/Source.scen.1.R" "output/Scenario_compare" Fig. 8 "R/Source.scen.2.R" "output/Scenario_compare" Fig. 9 & 10 "R/Source.scen.3.R" "output/Scenario_compare" Fig. 11 "R/Source.montecarlo.1.R" "output/MontaCarlo" Table S6 "R/Source.ref.1.R" "output/Reference" Table S7 "R/Source.scen.1.R" "output/Scenario_compare" Table S8 "R/Source.scen.3.R" "output/Scenario_compare" Table S9 "R/Source.montecarlo.1.R" Fig. S1 "R/Source.ref.3.R" "output/Reference" Fig. S2 "R/Source.ref.1.R" "output/Reference" Fig. S5 "R/Source.montecarlo.1.R" "output/MontaCarlo" Fig. S6-11 "R/Source.ref.1.R" "output/Reference" Fig. S12-15 "R/Source.ref.3.R" "output/Reference" Fig. S16-17 "R/Source.ref.2.R" "output/Reference" Fig. S18-24 "R/Source.scen.2.R" "output/Scenario_compare" Fig. S25-27 "R/Source.scen.3.R" "output/Scenario_compare" Fig. S28-29 "R/Source.montecarlo.1.R" "output/MontaCarlo" Fig. S30 "R/Source.agmip.R" "output/Agmip"  
Databáze: OpenAIRE