This is the 1st function for the tdm (Temporally Downscale Meteorology) workflow. The nc2dat.train function parses multiple netCDF files into one central training data file called 'dat.train_file'. This netCDF file will be used to generate the subdaily models in the next step of the workflow, generate.subdaily.models(). It is also called in tdm_predict_subdaily_met which is the final step of the tdm workflow.

nc.merge(outfolder, in.path, in.prefix, start_date, end_date,
  upscale = FALSE, overwrite = FALSE, verbose = FALSE, ...)

Arguments

outfolder

- directory where output will be stored

in.path

- path of coarse model (e.g. GCM output)

in.prefix

- prefix of model string as character (e.g. IPSL.r1i1p1.rcp85)

start_date

- yyyy-mm-dd

end_date

- yyyy-mm-dd

upscale

- Upscale can either be set for FALSE (leave alone) or to the temporal resolution you want to aggregate to

overwrite

logical: replace output file if it already exists?

verbose

logical: should ncdf4 functions print debugging information as they run?

Details

nc.merge Parses multiple netCDF files into one central document for temporal downscaling procedure

See also