Build a bias-corrected daily baseline for a climate-scenario workflow

Applies a fitted fit_met_bias_correction() to a full hourly reanalysis record, aggregates to daily and regenerates the dependent variables, so the result is ready to be handed to a delta-change routine such as AEME's climate_shift() as the baseline meteorology.

Usage

bias_correct_daily_baseline(
  era5,
  bc = NULL,
  lat = NULL,
  lon = NULL,
  elev = 0,
  tz = NULL,
  expand = TRUE,
  min_frac = 0.5,
  verbose = TRUE
)

Arguments

era5

hourly reanalysis met, from extract_era5_lake_met().

bc

a met_biascorr from fit_met_bias_correction(); NULL to aggregate without correcting.

lat, lon, elev

lake position; taken from the attributes of era5 when NULL.

tz

timezone for day boundaries and solar geometry; defaults to the tz attribute of era5, else "UTC".

expand

regenerate the dependent variables with expand_met() (default TRUE).

min_frac

minimum fraction of a day that must be present for that day to be kept, passed to met_to_daily().

verbose

print progress.

Value

daily data frame with Date of class Date and MET_* columns, carrying a biascorr attribute describing the correction.

Details

The rainfall column is always populated from the corrected record, so that downstream code which special-cases an all-zero MET_pprain (as climate_shift() does, by substituting inflow-derived rainfall) does not take that branch unintentionally.

See also

scenario_workflow for the full delta-change pipeline and vignette("scenario-workflow", package = "metscale").

Examples

if (FALSE) { # \dontrun{
era5 <- extract_era5_lake_met(lake_poly, path = nc_dir, method = "area",
                              years = 1980:2024)
obs  <- prepare_obs_met("obs/rotorua_buoy_met.csv", resample = "hour")
bc   <- fit_met_bias_correction(era5, obs)

baseline <- bias_correct_daily_baseline(era5, bc, elev = 279)

## hand to AEME's delta-change routine
inp <- AEME::input(aeme); inp$meteo <- baseline
AEME::input(aeme) <- inp
} # }