z-logo
open-access-imgOpen Access
getCRUCLdata: Use and Explore CRU CL v. 2.0 Climatology Elements in R
Author(s) -
Adam Sparks
Publication year - 2017
Publication title -
the journal of open source software
Language(s) - English
Resource type - Journals
ISSN - 2475-9066
DOI - 10.21105/joss.00230
Subject(s) - cru , climatology , environmental science , geography , meteorology , geology , precipitation
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 (0.17 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).

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom