This function is an alternative to importNOAA(), and provides access to the
"Lite" format of the data. This a subset of the larger importNOAA() dataset
featuring eight common climatological variables. As it assigns the nearest
measurement to the "top of the hour" to the data, specific values are likely
similar but different to those returned by importNOAA(). Read the
technical document
for more information.
importNOAAlite(code = "037720-99999", year = 2025, quiet = FALSE, path = NA)Returns a data frame of surface observations. The data frame is
consistent for use with the openair package. Note that the data are
returned in GMT (UTC) time zone format. Users may wish to express the data
in other time zones, e.g., to merge with air pollution data. The
lubridate package is useful in this
respect.
The identifying code as a character string. The code is a
combination of the USAF and the WBAN unique identifiers. The codes are
separated by a “-” e.g. code = "037720-99999".
The year to import. This can be a vector of years e.g. year = 2000:2005.
If FALSE, print missing sites / years to the screen, and show
a progress bar if multiple sites are imported.
If a file path is provided, the data are saved as an rds file at
the chosen location e.g. path = "C:/Users/David". Files are saved by
year and site.
If you are importing a lot of meteorological data, this can take a long
while. This is because each combination of year and station requires
downloading a separate data file from NOAA's online data directory, and the
time each download takes can quickly add up. importNOAA() and
importNOAAlite() can use parallel processing to speed downloading up,
powered by the capable {mirai} package. If users have any {mirai}
"daemons" set, these functions will download files in parallel. The
greatest benefits will be seen if you spawn as many daemons as you have
cores on your machine, although one fewer than the available cores is often
a good rule of thumb. Your mileage may vary, however, and naturally
spawning more daemons than station-year combinations will lead to
diminishing returns.
# set workers - once per session
mirai::daemons(4)# import lots of data - NB: no change in importNOAA()!
big_met <- importNOAA(code = "037720-99999", year = 2010:2020)
Jack Davison
Note the following units for the main variables:
Date/time in POSIXct format. **Note the time zone is UTC and may need to be adjusted to merge with other local data.
Latitude in decimal degrees (-90 to 90).
Longitude in decimal degrees (-180 to 180). Negative numbers are west of the Greenwich Meridian.
Elevation of site in metres.
Wind speed in m/s.
Wind direction in degrees. 90 is from the east.
Air temperature in degrees Celcius.
The sea level pressure in millibars.
The dew point temperature in degrees Celcius.
6-hour precipitation in mm.
1-hour precipitation in mm.
Sky Condition Total Coverage Code.
The data are returned in GMT (UTC). It may be necessary to adjust the time
zone when combining with other data. For example, if air quality data were
available for Beijing with time zone set to "Etc/GMT-8" (note the negative
offset even though Beijing is ahead of GMT. See the openair package and
manual for more details), then the time zone of the met data can be changed
to be the same. One way of doing this would be attr(met$date, "tzone") <- "Etc/GMT-8" for a meteorological data frame called met. The two data sets
could then be merged based on date.
getMeta() to obtain the codes based on various site search
approaches.
Other NOAA ISD functions:
getMeta(),
getMetaLive(),
importNOAA()
if (FALSE) {
heathrow_lite <- importNOAAlite(code = "037720-99999", year = 2025)
}
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