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Working with Daily Climate Model Output Data in R and the futureheatwaves Package.

G Brooke AndersonColin EasonElizabeth A Barnes
Published in: The R journal (2017)
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.
Keyphrases
  • climate change
  • machine learning
  • big data
  • artificial intelligence
  • heat stress
  • data analysis