R package lpjmlkit, version 1.7.3

A collection of basic functions to facilitate the work with the Dynamic Global Vegetation Model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) hosted at the Potsdam Institute for Climate Impact Research (PIK). It provides functions for performing LPJmL simulations, as well as reading, processing and writing model-related data such as inputs and outputs or configuration files.

LPJmL Runner only supports Unix-based operating systems that have an LPJmL version >= 4 installed.

• ✍ write_config() write config.json files using a data frame with parameters to be changed and a base configuration file
• 🔍 check_config() check if generated config.json files are valid for LPJmL simulations
• ▶ run_lpjml() run LPJmL directly (e.g. single cell simulations) or 🚀 submit_lpjml() to SLURM (e.g. global simulations)

• read_io() read LPJmL input and output as a LPJmLData object, containing the data array and LPJmLMetaData

  • 📈 plot() the data or get insights via summary() and other base stats
  • 🔁 transform() it to other time and space formats
  • ✂ subset() the underlying data
  • 📦 as_array(), as_tibble() and as_raster() / as_terra() to export into common R data formats

• read_meta() read meta or header files as LPJmLMetaData object

• calc_cellarea() to calculate the area of LPJmLData objects underlying grid or for other objects latitudes
• functions to handle LPJmL file headers, read_header() read the header of LPJmL files, get_headersize() get the size of a file header or create_header() to create a header object for writing input files
• get_datatype() get information on the data type used in different LPJmL files
• asub() functionality of the subset method to be used on a base array, also to replace data
• ... more functions via library(help = "lpjmlkit")

For installation of the most recent package version an additional repository has to be added in R:

options(repos = c(CRAN = "@CRAN@", pik = "https://rse.pik-potsdam.de/r/packages"))

The additional repository can be made available permanently by adding the line above to a file called .Rprofile stored in the home folder of your system (Sys.glob("~") in R returns the home directory).

After that the most recent version of the package can be installed using install.packages:

install.packages("lpjmlkit")

Package updates can be installed using update.packages (make sure that the additional repository has been added before running that command):

update.packages