Climate and Ecological Data for the GSODR Package
Due to the installed package, >9Mb, this package is only available from GitHub.
Authors: Adam Sparks, Tomislav Hengl, and Andrew Nelson
Maintainer: Adam Sparks firstname.lastname@example.org
Depends: R (>= 3.2.0)
Six data frames of climate data are provided from various sources for GSOD station locations and can be joined with data formatted by the GSODR package using the
CHELSA - Climatic surfaces at 1 km resolution is based on a quasi-mechanistic statistical down scaling of the ERA interim global circulation model (Karger et al. 2016). ESA's CCI-LC cloud probability monthly averages are based on the MODIS snow products (MOD10A2).
CRU_CL_2 - The CRU CL v. 2.0 data-set (New et al. 2002) comprises monthly grids of observed mean climate from 1961-1990, and covering the global land surface at a 10 minute spatial resolution. There are eight climatic variables available, and also the elevations on the grid: diurnal temperature range, precipitation, mean temperature, wet-day frequency, frost-day frequency, relative humidity, sunshine, and wind-speed. Minimum and maximum temperature are also calculated using getCRUCLdata and included in this data set, (see FAQ).
ESACCI - ESA's CCI-LC snow cover probability http://maps.elie.ucl.ac.be/CCI/viewer/index.php.
MODCF - Remotely sensed high-resolution global cloud dynamics for predicting ecosystem and biodiversity distributions (Wilson et al. 2016) provides new near-global, fine-grain (≈1km) monthly cloud frequencies from 15 years of twice-daily MODIS satellite images.
WorldClim_Bio 1.4 - WorldClim Global Climate Data - Free climate data for ecological modeling and GIS (Hijmans et al. 2004) provides freely available bioclimatic variables. These data are freely available for download from http://www.worldclim.org/version1.
WorldClim_Clim 1.4 - WorldClim Global Climate Data - Free climate data for ecological modeling and GIS (Hijmans et al. 2004) provides freely available, average monthly climate data. Current conditions (interpolations of observed data, representative of 1960-1990) are freely available for download from http://www.worldclim.org/version1.
#install.packages("remotes") remotes::install_github("adamhsparks/GSODRdata", build_vignettes = TRUE) library("GSODRdata")
See the GSODR vignette, Working with spatial and climate data from GSODR and GSODRdata, for use and examples.
Keeping GSODRdata updated
With each new release of GSODR, the GSODRdata package is also updated. To keep your local installation up-to-date, please use:
If you find bugs or have an idea to make this package better, please file a report with us.
Code of Conduct
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.
Karger, D. N., Conrad, O., Bohner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., et al. (2016) Climatologies at high resolution for the Earth land surface areas. arXiv preprint arXiv:1607.00217.
Wilson, A. M., Jetz, W. (2016) Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions. PLoS Biol 14(3): e1002415. doi:10.1371/journal. pbio.1002415
Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965-1978.