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.
Usage
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
ncdf4functions print debugging information as they run?- ...
further arguments, currently ignored
Details
nc.merge Parses multiple netCDF files into one central document for temporal downscaling procedure
See also
Other tdm - Temporally Downscale Meteorology:
gen.subdaily.models(),
lm_ensemble_sims(),
model.train(),
predict_subdaily_met(),
save.betas(),
save.model(),
subdaily_pred(),
temporal.downscale.functions()