gcam_agprodchange

Remaps country-level yield shocks to GCAM-required spatial scales (e.g., region, basin, and intersections), based on harvested areas, and aggregates crops to GCAM commodities. This function applies the projected shocks to GCAM scenario agricultural productivity growth rates (the unit used to project future yields in GCAM) and creates ready-to-use XML outputs for GCAM.

Usage

gcam_agprodchange(
  data = NULL,
  gcamdata_dir = NULL,
  climate_model = "gcm",
  climate_scenario = "rcp",
  member = "member",
  bias_adj = "ba",
  gcam_version = "gcam7",
  gcam_timestep = 5,
  cfe = "no-cfe",
  base_year = 2015,
  diagnostics = TRUE,
  output_dir = file.path(getwd(), "output")
)

Arguments

data

Default = NULL. Output data frame from function yield_shock_projection, or similar format of data

gcamdata_dir

Default = NULL. String for directory to the gcamdata folder within the specific GCAM version. The gcamdata need to be run with drake to have the CSV outputs beforehand.

climate_model

Default = 'gcm'. String for climate model name (e.g., 'CanESM5')

climate_scenario

Default = 'rcp'. String for climate scenario name (e.g., 'ssp245')

member

Default = 'member'. String for the ensemble member name

bias_adj

Default = 'ba'. String for the dataset used for climate data bias adjustment

gcam_version

Default = 'gcam7'. String for the GCAM version. Only support gcam6 and gcam7

gcam_timestep

Default = 5. Integer for the time step of GCAM (Select either 1 or 5 years for GCAM use)

cfe

Default = 'no-cfe'. String for whether the yield impact formula implimented CO2 fertilization effect.

base_year

Default = 2015. Integer for the base year (for GCAM)

diagnostics

Default = TRUE. Logical for performing diagnostic plot

output_dir

Default = file.path(getwd(), 'output'). String for output directory

Value

A data frame of formatted agricultural productivity change for GCAM