The GSOD or 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. 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 web server, reformats them and returns a data
frame.
reformat_GSOD() - this function takes individual
station files from the local disk and re-formats them returning a 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 in order from nearest to
farthest.
update_station_list() - this function downloads the
latest station list from the NCEI’s 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 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 get_GSOD() or
reformat_GSOD(), all units are converted to International
System of Units (SI), e.g., inches to millimetres and
Fahrenheit to Celsius. File output is returned as a
data.table object, 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 calculated
using the improved August-Roche-Magnus approximation (Alduchov and
Eskridge 1996).
For more information see the description of the data provided by NCEI, https://www.ncei.noaa.gov/data/global-summary-of-the-day/doc/readme.txt.
A stable version of GSODR is available from CRAN.
install.packages("GSODR")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 remotes package, available from CRAN. We strive to keep the main branch on GitHub functional and working properly.
if (!require("remotes")) {
install.packages("remotes", repos = "http://cran.rstudio.com/")
library("remotes")
}
install_github("ropensci/GSODR")There are several other sources of weather data and ways of retrieving them through R. Several are also rOpenSci projects.
The GSODTools by Florian Detsch is an R package that offers similar functionality as GSODR, but also has the ability to graph the data and working with data for time series analysis.
The gsod package from DataBrew aims to streamline the way that researchers and data scientists interact with and utilise weather data and relies on GSODR, but provides data in the package rather than downloading so it is faster (though available data may be out of date).
rnoaa, from rOpenSci offers tools for interacting with and downloading weather data from the United States National Oceanic and Atmospheric Administration but lacks support for GSOD data.
stationaRy, from Richard Iannone offers hourly meteorological data from stations located all over the world. There is a wealth of data available, with historic weather data accessible from nearly 30,000 stations.
riem from rOpenSci allows to get weather data from Automated Surface Observing System (ASOS) stations (airports) in the whole world thanks to the Iowa Environment Mesonet website.
weathercan from rOpenSci makes it easier to search for and download multiple months/years of historical weather data from Environment and Climate Change Canada (ECCC) website.
clifro 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.
Users of these data should take into account the following:
The data summaries provided here are based on data exchanged under the World Meteorological Organization (WMO) World Weather Watch Program according to WMO Resolution 40 (Cg-XII). This allows WMO member countries to place restrictions on the use or re-export of their data for commercial purposes outside of the receiving country. Data for selected countries may, at times, not be available through this system. Those countries’ data summaries and products which are available here are intended for free and unrestricted use in research, education, and other non-commercial activities. However, for non-U.S. locations’ data, the data or any derived product shall not be provided to other users or be used for the re-export of commercial services.
Please report any issues or bugs.
License: MIT
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 the GSODR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Alduchov, O.A. and Eskridge, R.E., 1996. Improved Magnus form approximation of saturation vapor pressure. Journal of Applied Meteorology and Climatology, 35(4), pp. 601-609 DOI: 10.1175/1520-0450(1996)035<0601:IMFAOS>2.0.CO;2.