The GSOD or [Global Surface Summary of the Day (GSOD)]https://data.noaa.gov/dataset/dataset/global-surface-summary-of-the-day-gsod/) data provided by the US National Centers for Environmental Information (NCEI) are a valuable source of weather data with global coverage. However, the data files are cumbersome and difficult to work with. GSODR aims to make it easy to find, transfer and format the data you need for use in analysis and provides five main functions for facilitating this:
get_GSOD() - this function queries and transfers files from the
NCEI’s FTP server, reformats them and returns a tidy data frame in R
or saves a file to disk
reformat_GSOD() - this function takes individual station files
from the local disk and re-formats them returning a tidy data frame
nearest_stations() - this function returns a vector of station IDs
that fall within the given radius (kilometres) of a point given as
latitude and longitude
update_station_list() - this function downloads the latest station
list from the NCEI’s FTP server updates the package’s internal
database of stations and their metadata.
get_inventory() - this function downloads the latest station
inventory information from the NCEI’s FTP server and returns the
header information about the latest version as a message in the
console and a tidy data frame of the stations’ inventory for each
month that data are reported.
When reformatting data either with
all units are converted to International System of Units (SI), e.g.,
inches to millimetres and Fahrenheit to Celsius. File output can be used
in an R session as a
tibble(), saved as a Comma Separated Value (CSV)
file or in a spatial GeoPackage (GPKG) file, implemented by most major
GIS software, summarising each year by station, which also includes
vapour pressure and relative humidity elements calculated from existing
data in GSOD.
Additional data are calculated by this R package using the original data and included in the final data. These include vapour pressure (ea and es) and relative humidity.
It is recommended that you have a good Internet connection to download the data files as they can be quite large and slow to download.
For more information see the description of the data provided by NCEI, http://www7.ncdc.noaa.gov/CDO/GSOD_DESC.txt.
A stable version of GSODR is available from CRAN.
A development version is available from from GitHub. If you wish to install the development version that may have new features or bug fixes before the CRAN version does (but also may not work properly), please install the devtools package, available from CRAN. We strive to keep the master branch on GitHub functional and working properly.
#install.packages("devtools") devtools::install_github("ropensci/GSODR", build_vignettes = TRUE)
GSODR’s main function,
get_GSOD(), downloads and cleans GSOD data
from the NCEI server. Following is an example of its capabilities, for
more detailed examples of its capabilities, please see the GSODR
## ## GSOD is distributed free by the U.S. NCEI with the ## following conditions. ## 'The following data and products may have conditions placed ## their international commercial use. They can be used within ## the U.S. or for non-commercial international activities ## without restriction. The non-U.S. data cannot be ## redistributed for commercial purposes. Re-distribution of ## these data by others must provide this same notification. ## WMO Resolution 40. NOAA Policy' ## ## GSODR does not redistribute any weather data itself. It ## only provides an interface for R users to download these ## data, but it does redistribute station metadata in the ## ## package.
tbar <- get_GSOD(years = 2010, station = "955510-99999") tbar
## # A tibble: 365 x 48 ## USAF WBAN STNID STN_NAME CTRY STATE CALL LAT ## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> ## 1 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 2 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 3 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 4 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 5 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 6 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 7 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 8 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 9 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## 10 955510 99999 955510-99999 TOOWOOMBA AIRPORT AS <NA> <NA> -27.55 ## # ... with 355 more rows, and 40 more variables: LON <dbl>, ELEV_M <dbl>, ## # ELEV_M_SRTM_90m <dbl>, BEGIN <dbl>, END <dbl>, YEARMODA <date>, ## # YEAR <chr>, MONTH <chr>, DAY <chr>, YDAY <dbl>, TEMP <dbl>, ## # TEMP_CNT <int>, DEWP <dbl>, DEWP_CNT <int>, SLP <dbl>, SLP_CNT <int>, ## # STP <dbl>, STP_CNT <int>, VISIB <dbl>, VISIB_CNT <int>, WDSP <dbl>, ## # WDSP_CNT <int>, MXSPD <dbl>, GUST <dbl>, MAX <dbl>, MAX_FLAG <chr>, ## # MIN <dbl>, MIN_FLAG <chr>, PRCP <dbl>, PRCP_FLAG <chr>, SNDP <dbl>, ## # I_FOG <int>, I_RAIN_DRIZZLE <int>, I_SNOW_ICE <int>, I_HAIL <int>, ## # I_THUNDER <int>, I_TORNADO_FUNNEL <int>, EA <dbl>, ES <dbl>, RH <dbl>
There are several other sources of weather data and ways of retrieving them through R. Several are also rOpenSci projects.
bomrang, from rOpenSci provides functions to interface with Australia Government Bureau of Meteorology (BoM) data, fetching data and returning a tidy data frame of précis forecasts, current weather data from stations, agriculture bulletin data, BoM 0900 or 1500 weather bulletins or a raster stack object of satellite imagery from GeoTIFF files. Data (c) Australian Government Bureau of Meteorology Creative Commons (CC) Attribution 3.0 licence or Public Access Licence (PAL) as appropriate. See http://www.bom.gov.au/other/copyright.shtml for further details.
CliFlo from rOpenSci is a web portal to the New Zealand National Climate Database and provides public access (via subscription) to around 6,500 various climate stations (see https://cliflo.niwa.co.nz/ for more information). Collating and manipulating data from CliFlo (hence clifro) and importing into R for further analysis, exploration and visualisation is now straightforward and coherent. The user is required to have an internet connection, and a current CliFlo subscription (free) if data from stations, other than the public Reefton electronic weather station, is sought.
weatherData provides a selection of functions to fetch weather data from Weather Underground and return it as a clean data frame.
The ULMO library offers an interface to retrieve GSOD data using Python.
90m hole-filled SRTM digital elevation (Jarvis et al. 2008) was used to identify and correct/remove elevation errors in data for station locations between -60˚ and 60˚ latitude. This applies to cases here where elevation was missing in the reported values as well. In case the station reported an elevation and the DEM does not, the station reported is taken. For stations beyond -60˚ and 60˚ latitude, the values are station reported values in every instance. See https://github.com/ropensci/GSODR/blob/master/data-raw/fetch_isd-history.md for more detail on the correction methods.
Users of these data should take into account the following (from the NCEI website):
“The following data and products may have conditions placed on their international commercial use. They can be used within the U.S. or for non-commercial international activities without restriction. The non-U.S. data cannot be redistributed for commercial purposes. Re-distribution of these data by others must provide this same notification.” WMO Resolution 40. NOAA Policy
Please report any issues or bugs.
To cite GSODR, please use: Adam H Sparks, Tomislav Hengl and Andrew Nelson (2017). GSODR: Global Summary Daily Weather Data in R. The Journal of Open Source Software, 2(10). DOI: 10.21105/joss.00177.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Jarvis, A., Reuter, H. I., Nelson, A., Guevara, E. (2008) Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database (http://srtm.csi.cgiar.org)
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