Create CalAdapt Download Functions for LOCA downscaled CMIP-5 #3446
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…, and factored out validation functionsdata(periods, package = "caladaptr", envir = environment())
dlebauer
changed the title
| @@ -24,6 +24,7 @@ Imports: | |||
| amerifluxr, | |||
| assertthat, | |||
| arrow, | |||
| caladaptr, | |||
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Recommend making caladaptr a "suggests" since it's only used by one function outside of the core workflow
| #' out_dir = "data" | ||
| #' ) | ||
| #' } | ||
| download_caladapt_loca_raster <- function(sf_obj, |
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I get the reason for accepting a sf_obj instead of just lat/lon, which is non-standard for PEcAn met files, but beyond that I'd highly recommend doing everything else you an to adhere to workflow norms and patterns. These include naming the function download. and having the required inputs start with (outfolder, start_date, end_date), followed by spatial information, followed by product-specific variables. This order is also consistent with R norms of having variables that have defaults AFTER those that don't have a default (start/end). To that end, I'd recommend dropping the default on outfolder (what you call outdir) and renaming start_year and end_year to start_date and end_date
| period = period, | ||
| start_year = start_year, | ||
| end_year = end_year, | ||
| raster = rast_file |
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Are you planning on writing separate functions convert the raster to netCDF CF and extract info from it?
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yep download --> met2cf --> met2model
but next step is to write the download functions for the WRF downscaled CMIP-6. Hopefully (🤞🏻) met2cf.caladapt will work on both.
Description
Adds
download_caladapt_locato download Cal-Adapt LOCA downscaled CMIP5 rasters inputs that can subsequently be used for data extraction. Acceptssf,sfc, andSpatVectorobjects.Motivation and Context
To support CCMMF project #3445
support for WRF-downscaled CMIP6 data will be added in a separate PR
Types of changes
Checklist: