getCRUCLdata: 'CRU' 'CL' v. 2.0 Climatology Client

title: 'getCRUCLdata: Use and Explore CRU CL v. 2.0 Climatology Elements in R' authors: - affiliation: 1 name: Adam H Sparks orcid: 0000-0002-0061-8359 output: pdf_document tags: - climate - R - applied climatology - high resolution surface - data affiliations: index: 1 name: University of Southern Queensland, Centre for Crop Health, Toowoomba Queensland 4350, Australia bibliography: paper.bib date: "04 April 2017"

Summary

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 [@New2002] 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-base]. All of the functions facilitate the calculation of minimum temperature and maximum temperature, and format the data into a tidy data frame [@Wickham2014] in a tibble [@Wickham2017] object or a list of raster stack objects [@Raster] 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 [@New2002].