The CRU CL v. 2.0 data are a gridded climatology of 1961-1990 monthly means released in 2002 and cover all land areas (excluding Antarctica) at 10 arcminutes (0.1666667 degree) resolution (New et al. 2002) providing precipitation, cv of precipitation, wet-days, mean temperature, mean diurnal temperature range, relative humidity, sunshine, ground-frost, windspeed and elevation. While these data have a high resolution and are freely available, the data format can be cumbersome for working with. Four functions are provided by getCRUCLdata that automate importing these data into R (R Core Team 2016). All of the functions facilitate the calculation of minimum temperature and maximum temperature, and format the data into a tidy data frame (Wickham 2014) in a tibble (Wickham, Francois, and Müller 2017) object or a list of raster stack objects (Hijmans 2016) for use in R or easily exported to a raster format file for use in a geographic information system (GIS). Two functions, get_CRU_df() and get_CRU_stack() provide the ability to easily download CRU CL v. 2.0 data from the CRU website and import the data into R and allow for caching downloaded data. The other two functions, create_CRU_df() and create_CRU_stack() allow the user to easily import the data files from a local disk location and transform them into a tidy data frame tibble or raster stack. The data have applications in applied climatology, biogeochemical modelling, hydrology and agricultural meteorology (New et al. 2002).
Recommended citation: getCRUCLdata: Use and Explore CRU CL v. 2.0 Climatology Elements in R. Adam H Sparks. The Journal of Open Source Software 2.12 (Apr. 2017). The Open Journal. DOI: 10.21105/ joss.00230