yield_shock_projection — yield_shock

Project yields for future climate scenarios using regression analysis Using average growing season temperature and precipitation, max and min months

Usage

yield_shock_projection(
  use_default_coeff = FALSE,
  climate_model = "gcm",
  climate_scenario = "rcp",
  base_year = 2015,
  start_year = NULL,
  end_year = NULL,
  gcam_timestep = 5,
  smooth_window = 20,
  diagnostics = TRUE,
  output_dir = file.path(getwd(), "output")
)

Arguments

use_default_coeff: Default = FALSE. Binary for using default regression coefficients. Set to TRUE will use the default coefficients instead of calculating coefficients from the historical climate data.
climate_model: Default = NULL. String for climate model (e.g., 'CanESM5')
climate_scenario: Default = NULL. String for climate scenario (e.g., 'ssp245')
base_year: Default = 2015. Integer for the base year (for GCAM)
start_year: Default = NULL. Integer for the start year of the data
end_year: Default = NULL. Integer for the end year of the data
gcam_timestep: Default = 5. Integer for the time step of GCAM (Select either 1 or 5 years for GCAM use)
smooth_window: Default = 20. Integer for smoothing window in years
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 smoothed annual crop yield shocks under climate impacts