The R Journal: article published in 2017, volume 9:1

Working with Daily Climate Model Output Data in R and the futureheatwaves Package PDF download
G. Brooke Anderson, Colin Eason and Elizabeth A. Barnes , The R Journal (2017) 9:1, pages 124-137.

Abstract Research on climate change impacts can require extensive processing of climate model output, especially when using ensemble techniques to incorporate output from multiple climate models and multiple simulations of each model. This processing can be particularly extensive when identifying and characterizing multi-day extreme events like heat waves and frost day spells, as these must be processed from model output with daily time steps. Further, climate model output is in a format and follows standards that may be unfamiliar to most R users. Here, we provide an overview of working with daily climate model output data in R. We then present the futureheatwaves package, which we developed to ease the process of identifying, characterizing, and exploring multi-day extreme events in climate model output. This package can input a directory of climate model output files, identify all extreme events using customizable event definitions, and summarize the output using user-specified functions.

Received: 2016-04-18; online 2017-06-08
CRAN packages: futureheatwaves, ggplot2, ncdf4, RNetCDF, ncdf4.helpers, PCICt, ncdf4.helpers, RCMIP5, wux, ggplot2, Rcpp, leaflet
CRAN Task Views implied by cited CRAN packages: Graphics, Phylogenetics, Spatial, SpatioTemporal, HighPerformanceComputing, NumericalMathematics
Bioconductor packages: ncdfFlow

CC BY 4.0
This article is licensed under a Creative Commons Attribution 4.0 International license.

  author = {G. Brooke Anderson and Colin Eason and Elizabeth A. Barnes},
  title = {{Working with Daily Climate Model Output Data in R and the
          futureheatwaves Package}},
  year = {2017},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2017-032},
  url = {},
  pages = {124--137},
  volume = {9},
  number = {1}