wrcc_loadYear: Load WRCC RAWS timeseries object from a local directory
In MazamaScience/RAWSmet: Download and Process data from Remote Automatic Weather Stations

wrcc_loadYear

R Documentation

Load WRCC RAWS timeseries object from a local directory

Description

Loads WRCC station metadata and data from the rawsDataDir. If the data is not in this directory, this will download and save the data.

Usage

wrcc_loadYear(
  wrccID = NULL,
  meta = NULL,
  year = NULL,
  newDownload = NA,
  password = NULL,
  baseUrl = "https://wrcc.dri.edu/cgi-bin/wea_list2.pl",
  verbose = TRUE
)

Arguments

`wrccID`	RAWS station identifier (will be upcased)
`meta`	Tibble of WRCC station metadata.
`year`	Year to access station data for.
`newDownload`	Logical flag specifying whether or not to download and override existing data.
`password`	Password required for access to archival data.
`baseUrl`	Base URL for data queries.
`verbose`	Logical flag controlling detailed progress statements.

Value

Timeseries object with 'meta' and 'data'.

Note

The 'newDownload' parameter has three possible settings:

NA – Download data if it is not found in rawsDataDir
TRUE – Always download data, overwriting existing data in rawsDataDir. This is useful for updating data files with more recent data.
FALSE – Never download data. This is useful when working with wrcc_loadMultiple and archival data to avoid continually requesting data for stations which have no data over a particular time period.

References

Program for Climate, Ecosystem and Fire Applications

Examples

## Not run: 
# Fail gracefully if any resources are not available
try({

library(RAWSmet)

setRawsDataDir("~/Data/RAWS/")

wa_meta <- wrcc_loadMeta(stateCode = "WA")
rawsObject <- wrcc_loadYear(
  wrccID = "waWENU",
  meta = wa_meta,
  year = 2020,
  password = MY_PASSWORD
)

dplyr::glimpse(rawsObject)

}, silent = FALSE)

## End(Not run)

MazamaScience/RAWSmet documentation built on May 6, 2023, 6:57 a.m.